Alert Fatigue Is Killing Your SOC. Here’s What Actually Works in 2026.

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Your SOC received 10,000 alerts yesterday. How many were real threats?

Most SOC teams operate in a constant state of triage. Alerts pour in from dozens of tools, each one demanding attention, each one potentially critical. The reality? Your analysts are making high-stakes decisions about which alerts to investigate based on gut instinct and whatever time they have left in their shift.

This approach worked when SOCs dealt with hundreds of alerts per day. It’s completely unsustainable at 10,000+.

The math is brutal: 59% of leaders report too many alerts as their main source of inefficiency. Your team is burning cognitive energy on noise while sophisticated threats exploit the chaos. Attackers know this. They’re counting on it.

Something has to change. In 2026, it finally is.

The Alert Fatigue Crisis: Why Traditional Approaches Failed

Alert fatigue isn’t about volume alone. It’s about the cognitive load of constantly context-switching between tools, the frustration of investigating the same false positives repeatedly, and the pressure of knowing a missed alert could mean catastrophe.

Research shows that 47% of analysts point to alerting issues as the most common source of inefficiency in the SOC — work that’s repetitive, draining, and prone to human error. When you’re reviewing your 8,000th alert of the day, even critical indicators start to blur together.

The psychological toll is staggering. Analyst burnout rates hit record highs in 2025, with the average analyst only staying in the role 3-5 years

The consequences compound. High turnover means institutional knowledge walks out the door. New analysts take months to ramp up, and meanwhile, attackers keep evolving, and alert volumes keep climbing.

Traditional solutions haven’t solved this. Adding more analysts just distributes the misery. Tuning SIEM rules creates blind spots. Legacy SOAR promised automation but delivered brittle playbooks that break constantly.

The problem isn’t effort. It’s architecture. Modern cybersecurity alert management requires a fundamentally different approach.

What’s Changed: The Rise of Agentic AI in Alert Management

The 2026 SOC looks nothing like its predecessors. 

From rule-based to reasoning-based. Traditional alert management relied on static rules: if X happens, do Y. But threats don’t follow predictable patterns. Agentic AI uses adaptive reasoning to evaluate alerts in context, making decisions based on learning rather than rigid logic.

From triage-only to end-to-end. Legacy tools automated the easiest part — sorting alerts into buckets. Then they handed everything back to analysts. Modern AI SOC platforms handle the full lifecycle: detection, triage, investigation, containment, and remediation. Autonomously.

From single-tool to cross-environment. Attacks pivot across email, endpoint, cloud, and identity. Effective cybersecurity alert management requires correlating signals across your entire stack simultaneously — something humans can’t do at scale, but multi-agent systems can.

From black-box to explainable. Early AI security tools made decisions nobody could understand or trust. Today’s platforms show their work. Every action is logged, auditable, and reversible. Analysts can see exactly why the AI made each decision.

How AI-Powered Alert Management Actually Works

The best way to understand modern alert management is to follow an alert through the system.

Step 1: Intelligent Ingestion

An alert fires from your SIEM: suspicious login from an unusual location. In a traditional SOC, this joins a queue of hundreds waiting for human review.

With Torq, the alert is immediately ingested and enriched. The system pulls context automatically: the user’s normal login patterns, endpoint health, recent authentication history, and threat intelligence on the source IP.

Step 2: Automated Investigation

Torq’s Multi-Agent System deploys specialized AI Agents to investigate in parallel. One checks identity logs. Another queries the endpoint. Another correlates with recent phishing attempts targeting this user. All simultaneously.

What would take an analyst 30-45 minutes of manual pivoting happens in seconds.

Step 3: Contextual Decision-Making

The AI evaluates the evidence: This user normally logs in from the US. The login came from Eastern Europe. But the user also submitted a travel request last week for a conference in Prague. The endpoint shows no signs of compromise. Recent MFA challenge was successful.

Verdict: legitimate travel, not a threat. The alert is suppressed with full evidence retained.

Step 4: Autonomous Action or Escalation

For confirmed threats, the AI takes immediate containment action — isolating endpoints, revoking sessions, blocking IPs — all within seconds. For ambiguous cases, it escalates to analysts with a complete investigation summary and recommended next steps.

The analyst doesn’t start from scratch. They review the AI’s work and make the final call.

Step 5: Continuous Learning

When analysts correct or confirm AI decisions, the system learns. Accuracy improves over time. The AI adapts to your specific environment, your risk tolerance, and your organizational patterns.

This is what modern cybersecurity alert management looks like. Not humans racing against an endless queue, but humans and AI working together, each doing what they do best.

8 Criteria for Choosing the Right Alert Management Solution

Not all SOC automation is created equal. When evaluating alert management platforms for 2026, demand answers to these questions:

  1. Does it eliminate, not just reduce, false positives? Look for solutions that achieve false positive reduction rates above 90%. Anything less still leaves analysts buried.
  2. Can it handle your alert volume today and tomorrow? Scalability isn’t optional. The system should process alerts at machine speed regardless of volume spikes.
  3. Does it integrate natively with your existing stack? Pre-built integrations with your SIEM, EDR, cloud security tools, and ticketing systems are non-negotiable. Custom API work shouldn’t be required.
  4. How transparent is the decision-making process? Black box AI erodes trust. Choose platforms that explain why alerts were prioritized, escalated, or dismissed.
  5. Can analysts teach it what matters to your organization? The best systems learn from feedback. Every analyst decision should improve the model.
  6. Does it automate response, not just detection? Alert management should trigger automated containment, isolation, or remediation for known threat patterns.
  7. What’s the time to value? Deployment shouldn’t take months. Modern platforms deliver measurable impact within weeks.
  8. Can it prove ROI? Demand concrete metrics: hours saved, MTTR improved, and analyst capacity freed up.

How AI SOC Platforms Actually Solve Alert Overload

The shift from traditional SOAR to AI SOC platforms represents a fundamental change in how organizations manage security operations. Instead of forcing analysts to adapt to rigid playbooks, modern solutions like Torq adapt to how your team actually works.

Here’s what sets AI SOC platforms apart:

Agentic AI that reasons, not just executes: Traditional automation follows if-then logic. AI agents reason through problems. When an alert fires, Torq’s AI Agents don’t just check a playbook — they investigate, correlate signals across your entire stack, and determine what the alert actually means for your specific environment. An authentication failure from a known test account gets automatically dismissed. That same failure from a privileged user at 3am triggers immediate escalation with full context.

Multi-agent systems that work together: Torq’s Multi-Agent System deploys specialized AI Agents that collaborate autonomously. A Case Management Agent handles triage and prioritization. Enrichment Agents gather context from threat intelligence, asset inventories, and user behavior analytics. Investigation Agents perform automated analysis. Response Agents execute containment. All working in concert, without human intervention, at machine speed.

Context that evolves with your environment: Static rules become obsolete the moment threats evolve. Torq Hyperautomation™ continuously adapts to analyst decisions, threat intelligence, and your environment’s behavior patterns. The system gets smarter every day, automatically adjusting prioritization as your threat landscape shifts.

Cloud-native speed and scale: Legacy SOAR platforms can’t keep pace with cloud-speed threats. Torq’s cloud-native architecture processes alerts at machine speed regardless of volume spikes. When your environment generates 50,000 alerts during a campaign, Torq scales instantly — no performance degradation, no missed threats.

Real Results: Organizations Transforming Alert Management

Agoda: End-to-End Phishing Automation

Online travel platform Agoda needed to scale security operations with a lean, distributed team during a major cloud migration.

With Torq, employees report suspicious emails with one click. The platform automatically enriches data, analyzes attachments, classifies threats with AI, and responds to users, all without human intervention. 

“Torq completely removes manual intervention for phishing,” says Laksh Gudipaty, Security Incident Response Manager at Agoda. “It’s now end-to-end automated on a 24×7 basis.”

Results: 47% reduction in missed SLOs for cloud security and incident reports generated in 30 minutes instead of 7 hours.

Valvoline: 7 Analyst Hours Saved Daily

Valvoline‘s security team was cut in half during a divestiture. Their legacy SOAR was code-heavy, and only a few people could maintain it.

Torq transformed their phishing workflows — previously consuming up to 12 hours daily — into fully automated processes. An integration their legacy SOAR couldn’t complete after hundreds of hours was running in under a week.

“My team is in love with the product,” says Corey Kaemming, Senior Director of InfoSec at Valvoline. “Sometimes, I have to tell them to stop having so much fun.”

Results: 6-7 analyst hours saved per day and operational ROI within 48 hours.

Global Money Transfer Platform: Day-Long Tasks in 3 Minutes

This financial services company was drowning in manual alert management. Their in-house tool couldn’t scale with alert volumes or integrate with their security stack.

Torq was implemented in days, not the months their previous system required. The vast majority of alerts are now automatically identified, analyzed, and remediated.

Results: 30% time savings across the security team and IAM tasks reduced from a full day to 3 minutes.

Your 90-Day Roadmap to Autonomous Alert Management

Organizations successfully transforming their alert management with Torq follow this proven 90 day approach.

Month 1: Foundation Building 

In the first 30 days, the focus is on standing up the platform, connecting your stack, and shipping quick wins. Guided by a dedicated Torq team, your SOC enables SSO and role mapping, lights up core integrations like M365/Defender, Okta/Entra, CrowdStrike, Slack, Jira, and AWS, and launches the first workflows — phishing triage, EDR alert handling, or cloud misconfiguration detection.

Your builders are trained on workflow design, testing, and debugging. By the end of the first month, automations are live, Tier-1 alert noise is already dropping, and analysts are reclaiming hours once lost to swivel-chair triage.

What to Measure:

  • First workflows deployed and delivering value
  • Tier-1 analyst workload beginning to decline
  • Platform familiarity achieved across the builder team
  • Baseline MTTR and alert volumes documented

Month 2: Process Optimization 

The next 30 days focus on scaling and simplifying. A second wave of workflows expands coverage into IAM offboarding, IOC enrichment, login anomaly detection, and user behavior signals. Socrates, Torq’s AI SOC Analyst, is deployed to handle Tier-1 triage, enrichment, and case summaries.

Teams tune thresholds, implement deduplication and correlation rules, and adopt modular subflows and templates to accelerate workflow reuse. Automation KPIs like MTTR, suppression rate, and analyst touches per case are established to measure impact.

What to Measure:

  • Automation coverage tracking (percentage of Tier-1 alerts handled end-to-end)
  • Suppression rate (false positives automatically identified and closed)
  • Builder teams creating workflows independently
  • Alert fatigue reduced through smarter case thresholds

Month 3: Full Autonomy 

By the end of three months, your SOC begins operating as an autonomous system with human-in-the-loop guardrails. Socrates orchestrates the entire case management lifecycle from ingestion through enrichment, correlation, decision, response, and documentation. Analysts only step in for escalated incidents.

Standard operating procedures and runbooks are finalized, intake and closure criteria are standardized, and before-and-after benchmarking is completed to prepare for the first quarterly business review.

What to Measure:

  • Up to 90% of Tier-1 alerts automated end-to-end
  • MTTR drops by 60%+ on core use cases
  • Analyst touches per case approaching zero for Tier-1 incidents
  • Analysts shift from reactive case handling to proactive oversight and threat hunting
  • Tool consolidation savings documented (legacy SOAR licenses retired)

The Future of Alert Management Is Here

Cybersecurity alert management has been broken for years. The answer was never more analysts, more tools, or more rules. It was a fundamental shift in how alerts get processed — from human-speed to machine-speed, from manual triage to autonomous resolution, from reactive firefighting to proactive defense.

That shift is happening now. Organizations running AI SOC platforms are achieving what seemed impossible just two years ago: 95%+ Tier 1 automation, 60%+ MTTR reduction, and analysts who actually want to stay in their jobs.

The technology exists. The results are proven. The only question is how long you’ll wait while your competitors make the leap.

Torq is the enterprise-grade autonomous SecOps platform that combines adaptive agentic insights and automation to triage, investigate, and remediate your most critical threats. The platform streamlines every step from alert through fix, working alongside your SecOps staff to transform overwhelming alert volumes into manageable, prioritized action.

The future of security operations is autonomous. The platform is Torq. The timeline is 90 days.

Get the 90-Day Roadmap to see exactly how Torq customers achieve SOC autonomy in three months.

FAQs

What is alert fatigue in cybersecurity?

Alert fatigue occurs when SOC analysts become desensitized to security alerts due to high volumes and frequent false positives, leading to missed threats and analyst burnout.

How does AI improve alert management?

AI-powered systems use agentic reasoning to automatically classify, prioritize, enrich, and investigate alerts at machine speed, dramatically reducing false positives while accelerating response to genuine threats.

What's the difference between traditional SOAR and AI-powered alert management?

Traditional SOAR relies on static playbooks and rule-based automation. AI-powered platforms use adaptive reasoning that learns from context, evolves with threats, and handles complex scenarios without predefined rules.

How quickly can organizations see ROI from automated alert management?

Leading platforms deliver measurable impact within 2-4 weeks, with most organizations achieving 70%+ false positive reduction and significant MTTI improvements in the first 90 days.

Can small security teams benefit from AI-powered alert management?

Absolutely. AI-powered automation is a force multiplier for lean teams, enabling 2-3 analysts to manage alert volumes that would typically require 10+ people using traditional methods.

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Todd Willoughby, Director

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“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

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“The only limit Torq has is people’s imaginations.”

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“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

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“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

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Best AI SOC Platforms for 2026: ​​How to Choose the Right One

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If you are evaluating security platforms in 2026 based on which one has the best chatbot or can write a slightly better Python script for you, you’re fighting the last war. 

Attackers are already using AI to scale their operations with speed and precision. If your “AI SOC platform” is just a co-pilot that summarizes tickets while humans do all the work, you’re behind.

The modern SOC is shifting from automated (static playbooks and scripts) to autonomous — an AI SOC platform powered by agentic AI that can reason, plan, and act within explicit guardrails.

We break down what the best AI SOC platforms actually need to deliver, how leading architectures differ, and why platform choice now is really an architecture decision.

What Sets Top AI SOC Platform Architectures Apart in 2026

To operate at machine speed, defend against AI-enhanced adversaries, and eliminate manual work, a next-generation AI SOC platform must deliver five core capabilities. These capabilities map directly to where legacy systems fail: data sprawl, slow investigations, brittle automation, and siloed case management.

1. A Unified Operational Data Layer

Legacy architectures assumed that every alert and log file had to be funneled into a SIEM for analysis, creating a massive data bottleneck and a single point of failure. As cybersecurity analyst Francis Odum noted at Torq’s SKO 2025: “Legacy SOAR assumed everything starts in the SIEM. Now, teams connect automation directly to EDR, email, and identity systems”.

A true AI SOC platform must deliver:

  • SIEM-agnostic connectivity: The platform should consume alerts and logs from any SIEM (Splunk, Sentinel, QRadar, Sumo Logic, Elastic) without forcing data migration or lock-in.
  • Native integrations across identity, cloud, SaaS, EDR, NDR, and email security: This includes Okta, Entra ID, AWS/GCP/Azure, CrowdStrike, SentinelOne, Proofpoint, Zscaler, Netskope, and more.
  • Decentralized processing: Instead of aggregating data into a centralized point before taking action, the platform integrates directly with data lakes and tools to create a unified control plane.

When SOC tools and data are disconnected, SOCs suffer higher mean time to respond (MTTR), more context switching, and lower detection quality. The best AI SOC platforms treat unified, real-time telemetry as a non-negotiable foundation.

2. Autonomous Investigation and Response 

In a next-generation SOC, analysts should never have to manually:

  • Enrich alerts
  • Pivot across six browser tabs
  • Copy and paste logs
  • Correlate IPs, hashes, and identities
  • Ask users “Was this you?”
  • Check cloud exposure severity
  • Determine whether an alert is real or noise

A true AI SOC platform takes over these tasks and autonomously executes:

  • Identity enrichment (such as roles, MFA events, privileges, and historic activity)
  • Endpoint posture and behavioral indicators
  • SaaS OAuth scope analysis
  • Network and cloud asset risk context
  • Threat intelligence lookups
  • Log retrieval, summarization, and normalization
  • Evidence collection for case management

This shift significantly improves critical metrics like MTTD and MTTR by removing the latency of manual investigation.

3. Agentic AI Capabilities 

The best AI SOC platforms must include agentic AI, which is AI that can reason, plan, adapt, and take actions within defined guardrails. In a fully realized AI-native SOC, a multi-agent system (MAS) can handle 90%+ of Tier-1 security analysts’ tasks.

Agentic AI enables:

  • Goal-driven planning: Instead of executing a static playbook, the AI determines how to reach an outcome (e.g., “Validate whether this login is malicious”).
  • Dynamic tool use: AI selects which systems to query — SIEM, identity provider, EDR, cloud APIs — based on context.
  • Contextual memory: The AI remembers case details, user signals, prior actions, and earlier investigations.
  • Independent decision-making: Within guardrails, AI decides:
    • Is the alert true or false?
    • Should a user be challenged?
    • Is the cloud resource exposed?
    • Which action mitigates the threat fastest?

The platform must ensure this happens safely, predictably, and auditably — not as “black box” reasoning.

4. Native Case Management 

Traditional ticketing systems were never designed for security investigations. They fragment context, slow down collaboration, and give AI very little structure to reason over.

A true AI SOC platform needs native case management designed specifically for security operations with:

  • Autonomous case generation: Cases should be created automatically from alerts based on severity, correlation, identity risk, or cloud exposure.
  • AI-driven prioritization: AI analyzes blast radius, business criticality, and user behavior to determine which cases matter most.
  • Integrated collaboration: Slack, Teams, email, and ticketing systems (like Jira or ServiceNow) are synced without forcing analysts to leave the AI SOC console.
  • Full evidence timeline: Every alert, enrichment, AI decision, human approval, and automated action must be fully logged.
  • Audit-ready transparency: Compliance and cyber insurance increasingly require AI explainability. Native case management makes this possible.

5. Open Ecosystem + Model Context Protocol (MCP)

Flexibility is the difference between a scalable AI SOC platform and a platform that traps you in inefficiencies.

Top AI SOC platforms must provide:

  • Comprehensive integrations: Hundreds of connectors for identity, cloud, EDR, SIEM, firewalls, ticketing, SaaS, DevOps tools, and threat intelligence solutions.
  • No-code + low-code workflow creation: Analysts should be able to build or edit automation with zero Python dependency.
  • Support for API-first and event-driven architecture: AI should react instantly to events — not wait for cron jobs or polling intervals.
  • Rapid onboarding without professional service or engineering dependency: If it takes weeks of professional services to onboard new integrations, it’s already obsolete.
  • Model Context Protocol (MCP) support: To facilitate reliable communication between AI agents and tools, leading architectures now support MCP, an open protocol that standardizes the way applications provide context to AI agents.

AI SOC Platform Architecture Comparison

Most products marketed as an “AI SOC platform” fall into three architectural categories.

1. AI-Enhanced Platforms 

Many products marketed as AI SOC platforms are better described as AI-enhanced security platforms. Architecturally, these solutions are centralized detection and analytics ecosystems that rely on large-scale data aggregation to improve visibility, correlation, and analyst productivity.

Aggregating and normalizing telemetry across identity, endpoint, cloud, network, and SaaS tools is essential for agentic reasoning at scale. When signals are locked inside individual silos, each tool only sees part of the picture — and understands it in part. Aggregation sets the stage for AI to correlate related activity, assemble the whole picture, and surface real risks that would otherwise remain obscured.

The architectural challenge arises from how that aggregation is implemented.

Platforms like Cortex XSIAM and Microsoft Sentinel require customers to ingest the majority of their telemetry into vendor-owned, proprietary data lakes to unlock their most advanced AI capabilities. While this can improve detection and analytics within the platform, it introduces several structural risks security leaders must evaluate carefully, such as:

  • Vendor lock-in by design: Once large volumes of historical telemetry are stored in proprietary formats, migration becomes costly and operationally disruptive. This creates renewal leverage for the vendor, limiting long-term architectural flexibility.
  • Captive storage economics: Customers are locked into premium ingestion and retention pricing models with limited tiering or external storage options, despite growing data volumes year over year.
  • Integration asymmetry: These platforms typically offer deep, native integrations for tools within their own ecosystem, while providing shallower or less capable integrations for competing third-party security products.
  • Platform-first optimization: The data lake is optimized to retain customers within a single ecosystem, rather than enabling best-of-breed security architectures across vendors.

As a result, the AI experience can initially feel powerful — until teams need to investigate or remediate across tools the vendor doesn’t own. At that point, automation often degrades into brittle connectors, custom engineering, or manual analyst effort. This is what many security leaders now refer to as the ‘integration tax’.

A true AI SOC platform still aggregates and normalizes data, but does so without holding that data hostage. It favors open standards (such as OCSF), vendor-agnostic access, and flexible storage choices. The goal isn’t centralization for its own sake; it’s open, normalized telemetry that empowers agentic AI to reason and act across heterogeneous, multi-vendor environments.

2. Legacy SOAR

Legacy SOAR platforms helped define automation years ago, but they were never architected for autonomous operations or agentic AI. These systems still rely on playbook-driven, script-heavy automation, using Python and operator-defined logic. 

Because SOAR engines were built for manual playbook triggering, not autonomous reasoning, vendors layer generative AI on top rather than rebuilding the stack around it.

Legacy SOAR tools fall short because:

  • Their core automation engine is still script-based, brittle, and infrastructure-heavy
  • AI cannot operate beyond summarizing or accelerating playbook creation
  • They cannot autonomously investigate, correlate, or remediate cases
  • Scalability and maintainability depend heavily on engineering resources
  • AI is bolted on, not built into the core reasoning and execution layer

In short: the AI is a feature, not the engine of the platform.

3. A True AI SOC (AI-Architected)

Torq pioneered the AI SOC category because traditional SOAR couldn’t handle the scale of modern hybrid cloud enterprises.

A true AI SOC platform must:

  • Correlate and reason over multi-vendor, multi-cloud telemetry
  • Generate and prioritize cases automatically
  • Make policy-aware decisions in real time
  • Execute remediation actions safely and autonomously
  • Maintain full auditability and operational control

Torq delivers this through:

  • Generative AI for investigation, summarization, and communication
  • Agentic AI for adaptive reasoning and action
  • Hyperautomation to orchestrate actions across your entire security stack
  • Case Management to unify triage, investigation, and response in a single view
  • Multi-Agent System Architecture for coordinated, parallel execution across tools

Torq’s AI SOC agents, led by Socrates and bolstered by HyperAgents, don’t just suggest actions — they can execute them within your guardrails. For example, they can:

  • Interview users via Slack or Teams to validate activity
  • Investigate alerts across SIEM, EDR, IAM, cloud, and SaaS tools
  • Enrich, correlate, and summarize findings into a native case
  • Remediate threats automatically where policy allows
  • Maintain an immutable, auditable trail of every step

Torq works well for all SOCs, but especially lean teams that want to eliminate backlog, and enterprises that need an AI SOC platform that can scale without inheriting the fragility and maintenance burden of script-heavy legacy systems.

“As new entrants crowd into the space with ambitious roadmaps and evolving terminology, Torq increasingly functions as the reference point others are measured against…. In that sense, Torq is more or less the de facto leader of the AI SOC space. While the category is now being treated as emerging, Torq’s position reflects something closer to incumbency — an established platform in a market that is only just catching up to what it represents.

Forbes, The AI SOC Boom Is Real, But The Work Started Long Before The Buzz

10 Questions to Ask Before Choosing an AI SOC Platform

Ask these ten questions during your next demo to separate the AI SOC platform contenders from the pretenders.

  1. Can the AI autonomously investigate and resolve security cases using predefined runbooks written in natural language?
  2. Does the AI provide structured, evidence-linked case summaries with direct citations to original forensic data?
  3. Can the platform safely execute containment actions with human-in-the-loop approvals and predefined guardrails?
  4. Does the solution integrate natively with your existing SIEM, EDR, IAM, cloud, and SaaS stack without custom engineering?
  5. Does the vendor use customer data to train or fine-tune AI models, or is all data kept isolated?
  6. Is the system compliant with SOC 2 Type II, HIPAA, GDPR, and other major trust frameworks?
  7. Does the solution provide immutable logs of all AI-driven actions, inputs, and outputs for auditing and insurance needs?
  8. Is the AI restricted to act only within explicitly enabled workflows, with no standalone entitlements to IT assets?
  9. Does the architecture support true multi-tenancy isolation for MSSP or multi-business-unit deployments?
  10. How does the AI SOC Analyst license work, and are there extra costs tied to usage, tuning, or model quotas?

How Valvoline Transformed Security with an AI SOC Platform

Valvoline’s experience illustrates what separates a true AI SOC platform from legacy SOAR and point solutions that limit AI capabilities to just the first 30 seconds of triage. When Valvoline’s security team was cut in half during a major divestiture, their legacy SOAR couldn’t keep up. Critical integrations failed, phishing alerts overwhelmed analysts, and investigations stalled under manual workload.

Some vendors claim AI capabilities while stopping at alert classification — telling you which alerts to investigate, then handing everything else back to your overwhelmed analysts. Valvoline needed a platform that handled the entire incident lifecycle: detect, triage, investigate, contain, and remediate. 

Torq transformed that reality in days. Within 48 hours of deployment, Valvoline automated high-volume, repetitive Tier-1 tasks, especially phishing triage, which previously consumed up to 12 analyst hours per day. Torq’s no-code workflows, agentic AI decisioning, and unified case management allowed the team to streamline investigations, accelerate containment, and eliminate manual steps that previously buried analysts.

With Torq, Valvoline now:

  • Saves 6–7 analyst hours every day through automated email and alert triage
  • Executes real-time containment when users click malicious links, including password resets, session termination, and cross-platform isolation
  • Correlates evidence automatically across Microsoft 365, Defender, CrowdStrike, Rapid7, and more
  • Runs workflows built by non-developers, thanks to Torq’s intuitive no-code design
  • Maintains full auditability through native case management with complete evidence timelines

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

– Corey Kaemming, CISO, Valvoline

The Best AI SOC Platform Is an Architecture Choice

The security landscape of 2026 demands more than a slightly faster version of your 2020 stack. It requires a fundamental shift in how your SOC operates.

The future isn’t about who has the prettiest chatbot. It’s about which AI SOC platform architecture gives you:

  • An aggregated and normalized security data lake
  • De-duplicated and correlated telemetry, to reduce noise
  • Transparent agentic triage with guardrails, for clarity and focus
  • Native, auditable case management
  • Autonomous investigation and response actions
  • An open ecosystem that deeply integrates with your security stack

Build an autonomous SOC that fights at machine speed, with humans firmly in control of risk and policy. Get the AI or Die Manifesto to learn how to deploy AI in the SOC the right way.

FAQs

What is an AI SOC platform and how does it differ from traditional security tools?

An AI SOC platform uses artificial intelligence to automate threat detection, investigation, and response across your security stack. Unlike traditional tools that rely on static rules and manual analysis, AI-driven platforms can process thousands of alerts simultaneously, recognize patterns in attack behavior, make contextual decisions about threat severity, and execute dynamic response strategies. 

This enables SOCs to handle enterprise-scale alert volumes without proportionally scaling headcount. Organizations with lean teams have been able to scale through automation with Torq, achieving end-to-end phishing response with zero analyst intervention on a 24/7 basis.

What key features should I look for when evaluating AI SOC platforms?

When evaluating AI SOC platforms, prioritize these capabilities: autonomous triage and Tier-1 remediation that reduces alert fatigue, real-time enrichment with threat intelligence and business context, no-code/low-code workflow building accessible to analysts at all skill levels, extensive pre-built integrations (300+ for enterprise environments), native case management that unifies alerts into coherent narratives, and scalable cloud-native architecture. Also assess deployment speed. With Torq, leading organizations achieve operational ROI within 48 hours, with some launching 100+ workflows in just 3 months without costly professional services.

Can AI SOC platforms work with my existing security tools, or do I need to replace my stack?

Leading AI SOC platforms are designed to integrate with your existing security stack, not replace it. Torq offers 300+ pre-built integrations covering SIEM, EDR, IAM, cloud platforms, ITSM, and collaboration tools through an agentless, API-first architecture. 

What ROI can organizations expect from implementing an AI SOC platform?

Organizations implementing AI SOC platforms see measurable ROI across multiple dimensions:

Response Time Improvements:

  • 75% reduction in MTTR for common security incidents
  • 60x faster MTTR — from two hours to two minutes
  • 8.2x faster incident detection-to-containment timelines
  • 50% improvement in Mean-Time-To-Detection (MTTD)

Operational Efficiency Gains:

  • 90% of Tier-1 tickets auto-remediated without human involvement
  • 95% decrease in manual tasks for Tier-1 SOC analysts
  • 80% reduction in alert fatigue
  • 10x faster security operations efficiency
  • 83% decrease in escalations to Tier-2/3 analysts for routine matters
  • 68% reduction in time spent on manual data correlation

Scalability Benefits:

  • 4x capability to handle security alerts with the same size team
  • 3.5x increase in customer-to-analyst ratio without sacrificing service quality
  • 100% of Tier-1 alerts handled by agentic AI
  • 3.8x increase in security coverage across environments

Business Impact:

  • 35% reduction in the probability of a major breach
  • 50% decrease in average cost per incident
  • 41% improvement in customer retention rates
  • 63% reduction in time spent generating compliance reports
  • 4.2x improvement in SLA adherence for critical security events

 

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“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

Compuquip logo in white

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

Fiverr logo in black

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

Carvana logo in black

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

Riskified logo in white

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

The Agentic SOC is Here: Torq Raises $140M Series D to Dominate the Future of Security Operations

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We are witnessing the end of the legacy SOC and the rise of something entirely new.

I’m incredibly proud to announce Torq has closed a $140 million Series D, valuing our company at $1.2 billion. This brings our total funding to $332 million. But let’s be clear: this isn’t just a fundraising milestone. It is a declaration that the Agentic SOC is no longer a future concept — it’s the operational reality for the world’s most advanced enterprises, and Torq is leading the charge.

Rebuilding the SOC with Pure Agentic Capabilities

From day one, our mission wasn’t to build a better SOAR or a faster automation tool. We set out to fundamentally rebuild the SOC around agentic AI.

AI Agents are driving a change in multiple software industries as we speak. Torq shows that the application of this technology to security operations can bring tremendous outcomes and this is what we are after: the opportunity of breaking away from “being an important tool for security professionals” and delivering on our true mission: providing outcomes that revolutionize security operations and make the overall security posture of an organization much stronger then ever before. We plan not only to deliver agentic technologies, but to restructure the whole experience for our customers, focusing on outcomes.

The industry has been stuck with bolt-on automation and legacy tools that require endless tuning and heavy services. That era is over. Torq is delivering pure agentic capabilities — a fully agentic, AI-first security operations platform that works at true enterprise scale.

We are delivering the only end-to-end solution designed for Hyperautomation, intelligent alert triage, and complete operational autonomy. We aren’t just assisting analysts, but liberating them. We are eliminating alert fatigue so security teams can evolve from reactive responders to proactive strategists.

Market Domination: Proven Value, Not Hype

The adoption of Torq AI Agents has been explosive because the value is undeniable. Unlike traditional tools that take months to deploy, Torq provides immediate, measurable impact.

Our agents are now deeply embedded in the SOCs of Fortune 500 leaders like Marriott, PepsiCo, Procter & Gamble, Siemens, Uber, and Virgin Atlantic. They are running millions of agentic security actions every single day — handling everything from complex investigations to rapid response.

The feedback from our customers is the only validation that matters.

“Torq delivers fast, measurable value to Valvoline’s SOC and eliminates the manual tasks that once consumed our analysts’ time,” said Corey Kaemming, CISO, Valvoline. “Within 48 hours of deployment, our team was using Torq’s AI SOC Platform for automating phishing triage, accelerating alert handling, and reducing response times across the board.”

“Our results with Torq were transformative. Analysts reclaimed hours of time, containment actions became automatic, and the security team evolved from reactive responders to proactive strategists. Torq took the vision that was in our heads and actually put it into practice. My team is in love with Torq.”

– Corey Kaemming, CISO, Valvoline

“We’re always innovating our security operations approach at Virgin Atlantic and the Torq AI SOC Platform is driving significant benefits for us,” said John White, CISO, Virgin Atlantic. “Today, innovation stems from an AI-first approach, which Torq excels at. Torq is making our security operations simpler and more efficient, and providing us with complete coverage across our security stack. Torq is now our umbrella platform.” 

This is what Agentic SOC market domination looks like: bottom-up adoption that transforms Torq from a point solution into the beating heart of the modern security stack.

Fueling the Revolution

This funding enables us to accelerate. We’re doubling down on speed, including speed of innovation, speed of go-to-market, and speed of value for customers.

A major focus of this next chapter is expanding into the U.S. Federal and Public Sector markets. We’re ready to navigate the complexities of FedRAMP and bring the power of the Agentic SOC to protect the nation’s most critical infrastructure. The stakes are high, and our platform is proven.

Our Partners in Vision

We’re thrilled to have Merlin Ventures lead this round. As a firm with deep roots in both commercial and U.S. public sectors, they understand exactly where the market is going.

“Torq is redefining security operations,” said Shay Michel, Managing Partner, Merlin Ventures. “They’ve fused automation and human judgment into a new AI SOC Platform built for asymmetric threats and real-world scale. This is why Merlin is leading the investment. Our focus now is speed — accelerating go-to-market, expanding across commercial and government markets, and building the next global category leader in AI security operations.”

It’s also a powerful vote of confidence that every single one of our existing investors doubled down in this round, including Evolution Equity Partners, Notable Capital, Bessemer Venture Partners, Insight Partners, and Greenfield Partners. Thank you for believing in our vision, our team, and the future we are building.

To the Torq Team and Our Customers

To my team: this milestone belongs to you. Your relentless focus and belief that security operations can be radically better is what got us here.

To our customers: thank you for trusting us to protect your organizations.

The Agentic SOC is here. We’re just getting started.

Let’s go!

SEE TORQ IN ACTION

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

Compuquip logo in white

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

Fiverr logo in black

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

Carvana logo in black

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

Riskified logo in white

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

The Best SOC Tools in 2026: Legacy vs Modern Automation

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Security Operations Centers (SOCs) are evolving faster than ever. As cybersecurity threats grow more sophisticated and digital infrastructure expands across cloud, hybrid, and on-prem environments, legacy SOC tools like SOAR are falling behind. Static dashboards, siloed point solutions, and human-dependent processes simply can’t keep up.

Traditional SecOps tools are no longer enough. Modern tools must proactively detect suspicious activities using broad data sources (e.g., threat intelligence, vulnerability databases, etc.) and enable seamless collaboration across teams. Automation is the key SOC tool to scale detection and response efficiently. 

Modern SOCs require automation-first platforms that enable proactive defense, seamless integrations, and high-scale responsiveness. Platforms like Torq — powered by Hyperautomation — represent the next generation of SOC architecture. 

Read on for a breakdown of SOC tools, an exploration of the best tools of 2025, and how automation streamlines security operations.

What is a SOC Tool?

Today’s cybersecurity environments rely on dozens of integrated systems. While powerful, this complexity can create inefficiencies, increase SOC analyst fatigue, and lead to slower threat response times. This is where SOC automation platforms like Torq shine by orchestrating across all tools, streamlining workflows, and accelerating response.

5 Core Capabilities of Security Operations Center Tools

Modern SOCs demand tools built for the cloud’s dynamic, distributed nature. Here are five must-have capabilities your stack needs.

1. Continuous SOC Monitoring

Tools should provide always-on visibility across cloud, hybrid, and on-prem workloads, dynamically adapting to autoscaling and ephemeral infrastructure. Look for platforms that detect real-time anomalies, monitor traffic flows, flag malicious configurations, and help strengthen your cloud security posture with minimal manual effort.

2. Log Collection and Analysis

Log tools enable deep investigation by aggregating decentralized telemetry across services. They help correlate signals across layers, enhancing intrusion detection, root cause analysis, and threat attribution across sprawling cloud environments.

3. Threat Detection

The best detection tools are plugged into real-time threat intel feeds and vulnerability databases. This allows SOC teams to quickly spot indicators of compromise (IoCs), detect novel tactics, and stay ahead of emerging threats with precision.

4. Incident Response

Incident response platforms have prebuilt playbooks and customizable workflows to stop attacks quickly. They can block malicious IPs, isolate compromised assets, and auto-contain threats without human intervention.

5. Automation

Security automation is essential for modern SOCs to operate efficiently at scale. It streamlines repetitive tasks, accelerates incident response, and allows SOC analysts to focus on complex threats instead of manual workflows.

How to Evaluate SOC Tools in a Fragmented Market

Knowing the capabilities is only half the battle. With thousands of vendors on the market, how do you distinguish a future-proof platform from legacy tech? When evaluating your stack for 2026, prioritize these three non-negotiable criteria:

  • Vendor-agnostic integration: Avoid “walled gardens.” Your tools must communicate openly via API. If a SOAR platform only works well with its parent company’s SIEM, it creates a silo, not a solution.

  • Agentic AI capabilities: Look beyond simple chatbots. Modern tools should feature Agentic AI that can autonomously plan, execute, and verify complex remediation tasks—not just summarize alerts.

  • Time-to-value: Can the tool deploy in hours, or does it require a six-month consulting engagement? The speed of implementation is a critical metric for agile SOCs.

The Top 10 SOC Tools in 2025

Specific tools have emerged as foundational to operational success as the SOC landscape evolves. Below are ten must-have SOC software tools and technologies for any security team aiming to stay ahead.

1. Log Collection and Management

Log management tools like Splunk and Elastic gather security logs and telemetry from various sources, including endpoints, network devices, and cloud environments. Proper log management is foundational for threat detection, compliance monitoring, and forensic investigations, making it an indispensable part of the SOC infrastructure.

2. Security Information and Event Management (SIEM)

SIEM platforms provide essential SOC monitoring and event correlation capabilities, helping security teams quickly identify and respond to threats. They are the cornerstone for centralized security operations.

Common examples of SIEM tools include IBM QRadar, Microsoft Sentinel, Splunk Enterprise Security, LogRhythm, and ArcSight. This SOC software correlates data across multiple sources, providing comprehensive threat visibility and efficient event management. 

3. Vulnerability Management

Vulnerability management platforms continuously scan and assess SOC network assets for vulnerabilities, prioritizing them based on severity and business impact. These platforms help SOC analysts proactively address critical issues before attackers can exploit them.

Rapid7 InsightVM, Nessus, Tenable, and Qualys are leading vulnerability management tools that provide actionable vulnerability data, enabling teams to rapidly and effectively patch vulnerabilities. Effective vulnerability management reduces organizational risk, maintains compliance, and prevents attackers from exploiting known weaknesses.  

4. Endpoint Detection and Response (EDR) and Extended Detection and Response (XDR)

EDR tools monitor endpoints, such as laptops and servers, enabling detection of malicious activities and automated response to threats in real time. Extended Detection and Response (XDR) solutions expand this coverage to networks, email, the cloud, and servers, delivering comprehensive security visibility.

EDR solutions like CrowdStrike Falcon and SentinelOne provide forensic capabilities and proactive threat-hunting features. XDR tools like Palo Alto Networks Cortex XDR unify endpoints, SOC networks, and cloud security to offer a holistic view of the threat landscape. 

5. Email Security

Email security tools work by performing detection and response across email, endpoints, and identity systems. They can quarantine malicious messages, remove harmful emails post-delivery, and correlate activity across systems to reveal the full scope of an attack. 

Solutions like Proofpoint and Microsoft Defender provide real-time URL and attachment sandboxing, threat intelligence integration, and automated remediation of compromised accounts. These capabilities not only strengthen threat response but also support compliance by enforcing encryption, archiving, and access controls.

6. Threat Hunting

Threat hunting tools proactively search for signs of malicious activity that evade traditional detection methods. Platforms like Carbon Black and Cisco empower SOC analysts with advanced investigative capabilities to discover and neutralize threats before they cause significant damage.

7. Threat Intelligence

Threat intelligence tools gather and analyze external threat data, providing actionable insights into potential cyber threats. Platforms such as Recorded Future and Anomali enhance a SOC’s ability to predict, identify, and ensure a proactive response to emerging threats, keeping teams informed of global threat trends and attacker tactics.

8. Cloud Security Posture Management (CSPM)

CSPM tools help identify, assess, and remediate misconfigurations and policy violations in cloud infrastructure. These tools continuously monitor cloud environments like AWS, Microsoft Azure, and Google Cloud Platform to ensure compliance with internal security policies and industry standards.

CSPM solutions automatically detect configuration drift, enforce least privilege access, and reduce the risk of data exposure by alerting teams to insecure storage, open ports, or excessive permissions. By offering centralized visibility and continuous compliance assessment, CSPM enables SOC teams to secure cloud workloads at scale while responding faster to evolving risks.

9. Identity and Access Management (IAM) 

IAM tools control and monitor user access to IT resources, ensuring only authorized individuals can reach sensitive systems and data. They encompass technologies like single sign-on (SSO), multi-factor authentication (MFA), privileged access management (PAM), and identity governance. 

In a SOC, IAM is essential for investigating incidents, detecting compromised accounts, and preventing unauthorized lateral movement, making it a cornerstone of a strong security posture.

10. Automation

At Torq, we call this Hyperautomation. Hyperautomation represents the next generation of SOC technology, combining advanced automation and artificial intelligence (AI) into a unified approach that fundamentally transforms traditional security operations. 

Torq integrates seamlessly with existing SOC tools, orchestrating complex workflows across the entire security stack and significantly reducing repetitive, manual tasks. By leveraging GenAI and agentic AI, Torq Hyperautomation dynamically identifies, analyzes, and responds to threats in real time, delivering faster and more consistent incident responses.

This proactive, autonomous approach enables security teams to scale effectively, enhance operational efficiency, and improve accuracy across their security processes. Hyperautomation accelerates response times, reduces SOC analyst workload, and ensures more precise threat detection and remediation. 

How Automation Transforms SOC Tools

Automation transforms traditional SOC operations by connecting disparate tools, streamlining workflows, and enabling rapid, automated responses. Here’s how:

  • Faster detection and response: Automation drastically reduces the time it takes to identify, investigate, and respond to security incidents. What once took hours or days now happens in seconds, minimizing dwell time and damage.

  • Increased SOC analyst efficiency: With Tier-1 alerts automatically triaged (and often auto-remediated) and routine tasks offloaded to automated workflows, SOC analysts can handle a higher volume of cases without burnout. Teams get more done with fewer resources, reducing the need to scale headcount just to keep up.

  • Effortless scalability: As threats grow in number and complexity, automation allows SOC analysts to keep pace without compromising performance. Whether your environment is expanding across clouds or adding new tools, automation scales effortlessly alongside.

  • Smarter use of human talent: SOC analysts are too valuable to be bogged down by repetitive tasks. Automation frees them to focus on high-impact investigations, strategic decision-making, and threat hunting, where human judgment and creativity matter most.

  • Reduction in alerts: Automated triage filters out low-priority noise, enriching and escalating only the alerts requiring attention. SOC analysts stay focused on real threats instead of drowning in false positives.

How Torq Hyperautomation Transforms the SOC

Torq HyperSOC™ is the first agentic, AI-powered SOC platform built for autonomous security operations. It transforms your SOC from reactive and overloaded to autonomous and high-performing

Here’s how Torq makes it happen.

Seamless Integration with Your Entire Security Stack

Torq connects instantly to all your SOC tools — SIEM, EDR, CSPM, IAM, SaaS platforms, ticketing systems, and even homegrown apps — without custom code or complex deployments. Whatever you’re running, Torq plugs in and gets to work.

AI Agents That Work Like SOC Analysts

At the heart of HyperSOC is Socrates, Torq’s AI SOC Analyst and omniagent. Socrates orchestrates a team of specialized AI Agents purpose-built for tasks like enrichment, case management, user verification, and remediation. Together, they coordinate end-to-end case lifecycles with precision and speed.

Natural Language-Driven Automation

Security automation doesn’t have to be complex. With Torq, anyone on your team can trigger powerful workflows using plain English. Want to isolate a user, rotate credentials, or escalate a threat? Just ask — Torq handles the rest.

Hyperautomation at Enterprise Scale

Torq’s performance automatically scales to keep up, whether your environment is cloud-native, hybrid, or on-prem. It runs thousands of workflows in parallel, adapts to evolving threats, and ensures no alert slips through the cracks.

Built to Flex with Your Needs

Torq’s open architecture and robust APIs let you fully customize cases to fit your cybersecurity strategy. Build once, reuse anywhere, and adapt fast to new use cases — all without needing a team of developers.

Real-World Use Case: Transforming the SOC from Black Box to Strategic Value

To understand the true impact of modern SOC tools when orchestrated correctly, let’s look at Kenvue, the world’s largest pure-play consumer health company (home to brands like Tylenol and Listerine).

  • The problem: Kenvue relied on an outsourced SOC model. This created a “black box” effect, characterized by limited visibility, inconsistent workflows, and a reactive approach to threats. Analysts were stuck on a conveyor belt of tickets with no way to measure true effectiveness.

  • The solution: Kenvue brought operations in-house and deployed Torq Hyperautomation™ as their central nervous system. They integrated their entire stack (EDR, SIEM, Identity) into Torq to unify case management and standardize response workflows.

  • The result: The transformation was immediate. Kenvue achieved a 60% decrease in MTTR within just two months. They now automate 89% of cases, allowing analysts to stop churning through tickets and start going “ten layers deeper” into complex investigations.

10 Questions for Your SOC Tool Evaluation

  • Does this tool offer open APIs for bidirectional integration with our current stack?

  • Can it handle our projected data volume without performance degradation?

  • Is the pricing model transparent, or are there hidden costs for data ingestion/retention?

  • Does it support “Human-in-the-Loop” workflows for sensitive decisions?

  • What is the average time-to-value for new deployments?

  • Does it utilize Agentic AI to perform autonomous investigations?

  • Can we build and customize workflows without a dedicated coding team?

  • Does it support multi-tenant operations (crucial for scaling teams)?

  • How frequently is the threat intelligence or vulnerability database updated?

  • Does it automatically map detections and responses to the MITRE ATT&CK framework?

Hyperautomation is the SOC Tool You Need Today

As cybersecurity challenges mount, traditional tools are no longer enough. Modern security operations centers require intelligent, automated, and scalable solutions that enable security teams to move faster, act smarter, and deliver better outcomes.

AI-driven Hyperautomation is that solution.

Torq brings Hyperautomation to life, enabling SOC analysts to move beyond fragmented processes and manual triage. Whether you’re a lean security team or an enterprise SOC analyst, Torq empowers you to detect, respond, and remediate with unprecedented speed and precision.

Get the SOC tool you need.

FAQs

What is a SOC tool?

A SOC (Security Operations Center) tool is any software or technology used by security teams to monitor, detect, analyze, and respond to cyber threats. These tools collect data from across an organization’s network, endpoints, and cloud environments to identify suspicious activity and support incident response. Common examples include SIEM, EDR, and vulnerability scanners.

What are the best SOC tools for 2025?

The best SOC tools for 2025 include modern platforms that prioritize automation and integration. Key tools include next-gen SIEMs (like Microsoft Sentinel), EDR/XDR solutions (like CrowdStrike), vulnerability management platforms, and threat intelligence feeds. Leading the list are Hyperautomation platforms like Torq, which orchestrate these diverse tools into a unified, autonomous defense system.

How do modern SOC tools differ from legacy systems?

Legacy SOC tools are often siloed, on-premise, and rely heavily on manual human intervention for triage and response. In contrast, modern SOC tools are cloud-native, API-first, and designed for automation. They seamlessly share data, scale dynamically with cloud workloads, and use AI to reduce false positives and accelerate response times.

What tools are used in a Security Operations Center?

A standard Security Operations Center (SOC) stack typically includes a SIEM for log management, EDR/XDR for endpoint protection, vulnerability scanners for risk assessment, and threat intelligence platforms. Advanced SOCs also utilize Cloud Security Posture Management (CSPM) tools and security hyperautomation platforms to connect and orchestrate these technologies.

Why is security automation important for SOC tools in 2025?

Security automation is critical in 2025 because the volume and speed of cyberattacks now exceed human capacity. Automation allows SOC tools to handle massive alert volumes, reduce response times from hours to seconds, and prevent analyst burnout by offloading repetitive tasks like data enrichment and Tier-1 triage.

Which SOC tools are most effective for cloud environments?

For cloud environments, the most effective SOC tools provide deep visibility into dynamic infrastructure. These include Cloud Security Posture Management (CSPM), Cloud Workload Protection Platforms (CWPP), and Cloud-Native Application Protection Platforms (CNAPP). Tools like Wiz and Orca Security are essential for monitoring configuration drift and runtime risks in the cloud.

How does AI enhance SOC tool operations?

AI enhances SOC operations by enabling autonomous investigation and decision-making. AI-driven tools can analyze vast datasets to identify subtle patterns of compromise, reduce false positives, and power Agentic AI that executes complex remediation workflows — such as user verification and threat containment — without requiring constant human hand-holding.

SEE TORQ IN ACTION

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

Compuquip logo in white

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

Fiverr logo in black

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

Carvana logo in black

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

Riskified logo in white

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

From Security to IT: How Bloomreach Scaled Automation Across the Enterprise

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Most organizations automate pieces of their Security Operations Center (SOC), but true enterprise automation remains out of reach. Across IT, compliance, HR, and business operations, manual processes still dominate. All of it drains time, slows teams, and keeps skilled people locked in low-impact work.

The truth is, automation shouldn’t live in one department. The same intelligence that speeds incident response can just as easily simplify IT workflows, accelerate business processes, and connect systems across the enterprise. That’s the future companies like Bloomreach are building — where enterprise automation is not a security initiative, but an operational foundation.

The Modern SOC Challenge

Even mature SOCs face the same blockers that limit broader enterprise automation:

  • Too many tools, too few connectors: Disjointed systems slow response and duplicate effort.
  • Developer dependency: Traditional SOAR tools demand scripting skills, leaving automation siloed with a few experts.
  • Adoption barriers: Teams outside security rarely touch these tools, limiting ROI and innovation.

Those challenges were clear for Bloomreach, a global technology company known for its AI-driven digital experience platform. Their SOC ran 24×7 — but legacy SOAR tooling kept automation confined to a small group of developers. Other teams saw its potential but couldn’t use it.

To scale automation beyond the SOC, Bloomreach needed an intuitive, flexible, and AI-powered platform anyone could adopt.

Enter Hyperautomation: One Platform for Enterprise Automation

When Bloomreach adopted Torq HyperSOC™, their goal was to modernize the SOC — but it soon became so much more than that. Torq’s no-code, low-code environment meant every analyst could build, test, and launch workflows without a heavy technical lift.

“We wanted everybody on the team, including junior analysts, to be able to build automations — not just developers. With traditional SOAR, that wasn’t possible.”

– Chris Talevi, Deputy CISO, Bloomreach

Within weeks, Bloomreach’s analysts had automated key SOC workflows like phishing triage and user authentication validation. The success sparked something bigger: adoption across departments.

Beyond Security: Bloomreach’s Enterprise-Wide Automation

Torq quickly became more than a SOC tool. Its adaptability allowed Bloomreach to connect workflows across security, IT, and business systems, driving consistency and scale throughout operations.

SOC automation: Phishing triage, identity checks, and threat enrichment now run automatically. With AI assistance from Socrates, Torq’s AI SOC Analyst, alerts are enriched, verified, and prioritized, freeing human analysts to focus on deeper investigation.

IT and help desk workflows: The IT team extended automation to account management — automatically verifying users, resetting credentials, and validating HR data through chat-based workflows. What used to take hours is now resolved in minutes, cutting ticket volume and reducing repetitive support work.

Threat intelligence summaries: Instead of manually parsing reports, Torq aggregates and summarizes global threat feeds using large language models (LLMs), publishing concise updates into Slack for real-time action.

Business intelligence automation: The Business Intelligence team automated Salesforce renewals and order updates, reducing manual follow-up and ensuring smoother handoffs between revenue and operations teams.

“We didn’t want automation to be just for the SOC — we wanted something adaptable across teams. Torq made that possible.”

– Chris Talevi, Deputy CISO, Bloomreach

The Results: Enterprise Adoption, Time Savings, and Scale

Bloomreach’s enterprise automation success reached beyond security:

  • 5+ hours saved per workflow each week
  • 100% of Tier-1 and Tier-2 tasks handled autonomously by AI
  • Three departments (SOC, IT, BI) using Torq with near-total adoption
  • Analysts at every level empowered to build and maintain workflows

What began as SOC automation became a blueprint for company-wide efficiency. Every team now operates more efficiently, with AI handling repetitive tasks and humans focusing on strategic outcomes.

“Torq levels up the type of work analysts can perform. It removes repetitive tasks and gives them time to focus on higher-value work.”

– Chris Talevi, Deputy CISO, Bloomreach

Enterprise Automation Without Boundaries

Enterprise automation shouldn’t stop at the edge of the SOC. The same platform that powers detection and response can power IT operations, business processes, and data workflows across an entire organization.

Bloomreach’s journey shows what’s possible when automation is democratized. By expanding beyond security, they built a connected operational ecosystem — one that is faster, smarter, and more resilient.

With Hyperautomation, enterprises aren’t just defending the business — they’re transforming how it runs.

SEE TORQ IN ACTION

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

Compuquip logo in white

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

Fiverr logo in black

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

Carvana logo in black

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

Riskified logo in white

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

The Future of Security Operations: Automated, Scalable, and Always-On

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Security operations are evolving — because they have to. The old model of human-dependent monitoring, manual ticket creation, and siloed tools is breaking under the weight of cloud complexity and relentless attack volume.

Today’s enterprise requires a new kind of agility. It demands security operations that are context-aware, Hyperautomated, and capable of responding at machine speed. But for many organizations, the reality is still reactive busywork. Teams are drowning in noise, switching between a dozen dashboards, and struggling to scale. 

Torq changes that. By serving as the connective tissue for your entire security stack, Torq Hyperautomation enables smart, automated, and cloud-scalable operations that transform your SOC from a cost center into a resilient, always-on defense engine.

What Are Security Operations?

Security operations (SecOps) is the discipline responsible for monitoring, detecting, analyzing, and responding to cyber threats across an organization. It’s the day-to-day engine that keeps your defenses running.

These functions typically live within the Security Operations Center (SOC), a centralized hub of people, processes, and technology dedicated to protecting the organization’s information assets.

A security operations program manages critical functions, including:

  • Continuous monitoring: Real-time surveillance of networks, endpoints, clouds, and applications
  • Incident response (IR): The structured approach to addressing and managing the aftermath of a security breach or cyberattack
  • Threat intelligence and threat hunting: Proactively searching for threats that evade initial detection
  • Vulnerability management: Identifying, evaluating, treating, and reporting on security vulnerabilities
  • Log analysis and SIEM/XDR management: Collecting, normalizing, and analyzing telemetry to detect suspicious behaviors and patterns

The team behind these functions typically includes:

  • Tier 1 analysts (alert triage and initial investigation)
  • Tier 2/3 analysts and Incident Responders
  • Threat Hunters and Security Engineers
  • SecOps / Detection Engineers
  • A SOC Manager overseeing the day-to-day operations
  • The CISO aligning operations with business risk, compliance, and continuity goals

The Challenges of Traditional Security Operations

Despite massive investment, many SOCs are failing to keep pace. They are hindered by legacy processes that simply cannot scale to meet modern threat volumes.

Alert Fatigue and Triage Overload

Alert fatigue is the single biggest killer of SOC morale and efficiency. Analysts are flooded with thousands of alerts daily from SIEMs, EDRs, and cloud monitors. A large portion of alerts goes uninvestigated, is of low fidelity, or turns out to be a false positive. This forces highly skilled analysts to spend their days manually clicking ‘dismiss’ or chasing ghosts, leading to missed genuine threats amidst the noise.

Siloed Tools and Data Sources

The average enterprise security stack has dozens of disconnected tools — endpoint protection here, identity management there, cloud security somewhere else. This fragmentation makes it nearly impossible to correlate threats or automate workflows effectively. Analysts waste valuable time manually piecing together data from disparate systems to get a coherent picture of an attack.

Staff Shortages and Burnout

The cybersecurity talent gap is real, but burnout is the bigger issue. High-pressure environments, repetitive manual tasks, and the feeling of never being “caught up” drive high turnover rates. Scaling response capacity by simply hiring more bodies is expensive and increasingly ineffective.

Manual Response Processes

In many SOCs, common workflows still look like this:

  1. Alert arrives in one tool
  2. Analyst copies details into another
  3. Analyst opens a ticket in ITSM
  4. Analyst pings someone on Slack or email
  5. Analyst waits for action
  6. Analyst updates the ticket by hand

These manual steps introduce significant latency in both detection and response (MTTD/MTTR), giving attackers more time to move laterally, escalate privileges, or exfiltrate data.

What Does a Modern Security Operations Center Look Like?

To survive in the modern threat landscape, the SOC must evolve. It can no longer be a reactive ticket-taking factory. It must become a proactive, automated nerve center.

Cloud-Native and Tool-Agnostic

Modern SOCs protect hybrid and multi-cloud environments, plus SaaS systems and distributed workforces — not just on-prem networks. They must be:

  • Cloud-native: Able to ingest and act on telemetry from AWS, Azure, GCP, and SaaS platforms
  • Tool-agnostic: Able to integrate with whichever SIEM, EDR, IAM, CSPM, and ITSM tools you already use
  • Flexible: Able to swap or add tools without re-architecting security operations from scratch

Driven by Automation and Orchestration

In a modern SOC, workflows replace manual playbooks. Automation isn’t an afterthought; it is the foundation. Security operations workflows handle the heavy lifting of data ingestion, enrichment, and initial triage, ensuring that human analysts only engage when their expertise is truly required. This moves response from “whenever someone can get to it” to real-time or near real-time.

Continuous Detection and Response

Rather than periodic scans or ad hoc investigations, modern SOCs aim for continuous detection and response in which:

  • New alerts and signals are evaluated immediately
  • Identity, endpoint, cloud, and network context are applied automatically
  • Follow-up actions are orchestrated as soon as risk is confirmed

This isn’t a formal cybersecurity standard like NIST CSF, but a practical operating mode: continuous risk evaluation, continuous enforcement, continuous improvement.

Unified Dashboards and Metrics

You can’t optimize what you don’t measure. SOC leaders need visibility into:

  • Mean Time to Detect (MTTD)
  • Mean Time to Respond (MTTR)
  • Volume of incidents by type and severity
  • Automation coverage (what % of workflows are automated)
  • False positive rates and escalation volumes

Modern security operations utilize unified dashboards to track these metrics and drive continuous improvement — and to show to the board and leadership how investments translate into reduced risk.

How Security Operations Automation Works

Torq acts as the orchestration layer that brings this modern vision to life. But how does SecOps automation actually function under the hood?

Connects to Your Full Stack

Automation starts with connectivity. Torq integrates with virtually everything in your ecosystem, including SIEMs, EDRs, ticketing systems (such as Jira and ServiceNow), identity providers (like Okta and Azure AD), cloud platforms (like AWS, Azure, and GCP), and communication tools (like Slack and Teams). This connectivity eliminates silos and allows data to flow freely between tools.

Ingests and Enriches Events

Instead of dumping raw logs onto an analyst, the Torq platform ingests alerts and immediately enriches them. It automatically queries threat intelligence feeds, checks user directories, and pulls asset information. By the time a human looks at the case, it is already populated with the who, what, where, and when.

Orchestrates Workflows from Alert to Remediation

This is the core of SOC automation. Using no-code visual workflows, Torq can:

  • Automate triage: Classify alerts, suppress known noise, group related events
  • Drive containment: Block IPs, isolate endpoints, disable accounts, reset credentials
  • Notify stakeholders: Message users via Slack/Teams, alert on-call responders, update tickets
  • Kick off root-cause and follow-up work: Create tickets for IT or DevOps, trigger patching or configuration changes

Complex, multi-step processes that previously took hours of manual coordination can execute in seconds.

Provides Full Auditability and Reporting

Every automated action is logged. The system tracks exactly what logic was applied, what actions were taken, and the outcome. This provides full auditability for compliance purposes and rich reporting data to measure automation ROI.

6 Benefits of Automating Security Operations

Why make the shift? The impact of automation on security operations is measurable and transformative.

  1. 10x faster incident response: By removing manual latency, automation allows you to respond to threats at machine speed. Containment actions that used to take 30 minutes can now happen in seconds.
  2. Major reduction in false positives: Automated triage filters out the noise before it ever reaches the queue. Logic-based filtering ensures that known false positives are dismissed automatically, clearing the deck for real work.
  3. Analysts focused on real threats: When you automate the repetitive busywork like password resets and IP lookups, you free up your most valuable resource: your people. Analysts can focus on threat hunting, strategic planning, and complex investigations.
  4. Consistent playbook execution: Automation doesn’t get tired, and it doesn’t skip steps. It ensures that every incident is handled according to your defined security operations best practices, regardless of whether it happens at 2pm on a Tuesday or 3am on a Saturday.
  5. Measurable improvement in MTTD/MTTR: These are the metrics that matter most to the board. Automation directly compresses both detection and response times, shrinking the window of exposure and reducing risk.
  6. Seamless collaboration across IR, IT, and DevOps: Security doesn’t happen in a vacuum. Automation bridges the gap between teams, automatically routing tasks to IT for patching or Engineering for code fixes, fostering true collaboration without the friction of email chains.

How Torq Transforms Security Operations

Torq isn’t just another tool in the stack; it is the automation nerve center for the modern enterprise.

  • Visual workflow builder: Torq offers a powerful, no-code and AI-driven visual builder that makes automation accessible. Anyone on the team — from junior analysts to engineers — can build and maintain workflows without writing complex code.
  • 300+ integrations: With hundreds of out-of-the-box integrations, Torq connects your SIEM, XDR, cloud, IAM, ticketing, and threat intel tools instantly.
  • Real-time execution: Torq enforces security policies and executes playbooks live, reacting to events as they happen, not after the fact.
  • Smart routing: The platform intelligently assigns incidents based on severity, time of day, or analyst skillset, ensuring the right eyes are always on the right problem.
  • Audit trails: Torq monitors all workflows, actions, and outcomes in real time with immutable logs that satisfy even the strictest compliance auditors.

Security Operations Don’t Have to Be Manual or Reactive

Security operations don’t have to be manual, slow, or reactive. The choice is no longer between secure and fast — you can have both. With automation and orchestration, security teams can do more with less — responding faster, reducing burnout, and operating with vastly higher confidence.

Reimagine your SOC. See how Torq modernizes security operations from the inside out.

FAQs

What are security operations?

Security operations (SecOps) encompass the processes, technology, and personnel responsible for continuously monitoring, detecting, investigating, and responding to cyber threats across an organization. It is the operational layer of enterprise security — combining threat intelligence, incident response, vulnerability management, and system monitoring into a coordinated defense function.

What happens in a SOC?

A Security Operations Center (SOC) is the command center for SecOps. Analysts triage alerts, investigate suspicious activity, hunt for threats that bypass detection tools, coordinate incident response, and ensure security controls are working as intended. Modern SOCs also manage cloud telemetry, identity signals, and automation workflows that drive containment and remediation across the environment.

Why is automation important in SecOps?

Automation eliminates the manual, repetitive tasks that slow down detection and response. It filters noise, enriches alerts, executes containment steps, and enforces security policies in real time, reducing MTTR, cutting false positives, and freeing analysts to focus on high-value investigation and threat hunting. In high-volume environments, automation is the only way to maintain 24/7 coverage without scaling headcount linearly.

What is the difference between SecOps and DevSecOps?

SecOps focuses on defending enterprise infrastructure — cloud, identity, endpoints, and networks — through continuous monitoring and response. DevSecOps embeds security into the software development lifecycle, ensuring that code, pipelines, and deployments are secure from build to production. SecOps protects operations; DevSecOps secures development. Both disciplines intersect in cloud-native, API-driven environments, but their missions and workflows differ.

How can I modernize my security operations center?

A modern SOC prioritizes automation, cloud-native telemetry, unified case management, and AI-assisted investigation. Start by consolidating tooling, eliminating manual triage, and automating routine containment steps. Introduce no-code or low-code workflows to standardize response. Deploy AI-driven enrichment and prioritization to reduce analyst load. Finally, build continuous detection and response capabilities that operate across identity, cloud, and endpoint, giving your team real-time visibility and control.

SEE TORQ IN ACTION

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

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“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

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“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

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“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

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“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

Automated Supply Chain Attack Prevention Strategies for 2026

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The modern enterprise is built on a foundation of trust. You trust your cloud provider to secure the hypervisor. You trust your software vendors to secure their build pipelines. You trust your open-source libraries to be free of backdoors. But in the current threat landscape, trust is your biggest vulnerability.

Supply chain attacks have evolved from niche, nation-state anomalies into a commoditised attack vector used by ransomware gangs and opportunists alike. They bypass your perimeter, your firewall, and your endpoint protection because they ride in on the trusted highways you built for business efficiency.

For the strategic CISO, supply chain attack prevention is no longer just about third-party risk management questionnaires or annual audits. It is an operational challenge that demands real-time visibility, automated governance, and the ability to sever connections with compromised vendors at machine speed.

This guide explores the realities of supply chain risks, the necessity of security automation, and how Torq enables enterprises to defend their ecosystem without slowing down innovation.

What Is A Supply Chain Attack?

A supply chain attack occurs when an adversary infiltrates your system through an outside partner or provider with access to your systems and data. This dramatically changes the attack surface. Instead of attacking you directly, the adversary compromises:

  • A build system
  • An upstream open-source dependency
  • Firmware on a critical device
  • A vendor or MSP with network or identity access

From there, they can move laterally into downstream customer environments. These attacks are particularly dangerous because they exploit trust:

  • Signed binaries from known vendors may be whitelisted
  • Updates are assumed to be safe
  • Vendor access paths are often less tightly monitored than internal accounts

A single malicious update or compromised vendor account can deploy malware deep inside an environment before traditional detection fires, if it fires at all.

The 3 Primary Vectors of Supply Chain Compromise

To understand the scope of supply chain compromise, we must look beyond just software.

1. Software Supply Chain Attacks 

This is the most visible and well-publicized vector. Attackers:

  • Inject malicious code into an upstream application or dependency
  • Compromise build systems or CI/CD pipelines
  • Exploit widely used open-source components

When targets consume the compromised artifact (via update, container image, dependency, etc.), they unwittingly deploy attacker-controlled code.

Examples:

  • SolarWinds Orion: Attackers compromised SolarWinds’ build environment and injected a backdoor into legitimate, digitally signed Orion updates. Once customers installed them, the malware gained privileged access inside federal agencies, enterprises, and critical infrastructure.
  • Log4j (Log4Shell): Not a malicious backdoor, but a critical vulnerability in a ubiquitous Java logging library, embedded into thousands of products. It showed how a flaw in a single upstream dependency can trigger an internet-wide scramble to identify and patch exposure.
  • XZ Utils: A near-miss in 2024 where a long-term effort to compromise a critical compression library’s maintainer led to a backdoored version of xz/liblzma. Several major Linux distributions were close to shipping it before the issue was discovered — highlighting how attacker focus is shifting toward open-source maintainers and infrastructure.

2. Hardware and Firmware Attacks 

Hardware and firmware compromise is less common but extremely high impact. Attacks can involve:

  • Tampering with components during manufacturing or distribution
  • Modifying firmware on devices such as network gear, baseboard controllers, or storage devices

Because these operate below the OS, traditional endpoint and application security tools often can’t see them. Successful firmware or hardware compromise can provide long-term, stealthy access.

3. Vendor and Service Provider Compromise 

This is often called island hopping. Attackers compromise a Managed Service Provider (MSP) or a smaller vendor with access to your network and use their credentials to pivot into your environment.

Examples:

  • Kaseya VSA: Attackers exploited vulnerabilities in Kaseya’s remote monitoring and management platform, using its privileged channel to deploy ransomware through MSPs to hundreds of downstream organizations.
  • Target HVAC Vendor Breach: An attacker compromised credentials from a third-party HVAC vendor with network access into Target’s environment. That foothold was used to pivot into payment systems and exfiltrate tens of millions of card numbers.

5 Supply Chain Security Best Practices (Where Automation Becomes Essential)

Effective prevention requires a layered defense that spans the software development lifecycle (SDLC), hardware procurement, and organizational governance. Automation is the only way to apply these controls at the scale of a modern enterprise.

1. Software and Open-Source Controls

Securing the software supply chain requires a shift left — integrating security into the development process rather than applying it as an afterthought.

  • Harden the CI/CD pipeline: Your build server is a prime target. Ensure that access to build tools is strictly controlled and monitored. Use ephemeral build environments that are spun up for a job and destroyed immediately after, preventing persistence.
  • Enforce provenance: Implement standards such as SLSA (Supply Chain Levels for Software Artifacts). You must verify that the code running in production is the exact same code that was committed to the repository and built by the trusted pipeline. Code signing is non-negotiable.
  • Curate dependencies: Developers should not pull libraries directly from the public internet. Use an internal artifact repository that acts as a proxy. Scan every package for known vulnerabilities and malware before it is added to the internal repository.

2. Hardware and Firmware Security

Hardware risks are challenging to detect but crucial to mitigate, particularly in critical infrastructure and high-security environments.

  • Verify root of trust: Utilize Trusted Platform Modules (TPM) and hardware roots of trust to ensure that the system has not been tampered with before the OS even boots.
  • Secure firmware updates: Firmware updates should be digitally signed by the vendor and verified by the hardware before installation. Disable the ability to downgrade firmware to prevent attackers from rolling back to vulnerable versions.
  • Physical tamper evidence: For critical hardware shipments, use tamper-evident packaging and separate shipping channels for the hardware and the authentication keys required to activate it.

3. Governance and Vendor Management

Governance must evolve from a static contract to a continuous operational state.

  • Contractual security SLAs: Contracts must mandate notification timelines for breaches. If a vendor is breached, you need to know within hours, not days.
  • Right to audit: Include clauses that allow you to review the vendor’s security posture or receive independent audit reports (SOC 2 Type II) regularly.
  • Continuous monitoring: Use third-party risk management platforms to monitor the external security posture of your vendors. 

4. Zero Trust Network Access (ZTNA)

The days of the trusted site-to-site VPN for vendors are over. A vendor should never have broad network access.

  • Least privilege access: Vendors should only access the specific applications they need to service.
  • Identity verification: Enforce strict Multi-Factor Authentication (MFA) for all external access.
  • Session recording: For high-risk access, record the session. If a vendor creates a backdoor, you need the forensic tape.

5. Automated Asset Discovery

You cannot patch what you do not know you have. Shadow IT and forgotten assets are fertile ground for supply chain attackers. Automated asset discovery tools must run continuously to identify unknown software and hardware on the network, reconciling them against the authorized inventory.

Detection, Response, and Resilience Beyond Prevention

Prevention is the goal, but resilience is the requirement. A determined nation-state actor may eventually find a way into your supply chain. Therefore, your strategy must include capabilities to detect the compromise and minimize the damage.

Anomaly Detection

When prevention fails, behavior is the only tell. If a trusted software update process suddenly starts beaconing to an unknown IP address in a hostile nation, that is a supply chain attack in progress.

Enterprises need runtime security that monitors the behavior of applications and vendor accounts. Establish a baseline of normal activity. Any deviation — such as a printer trying to access a domain controller or a payroll software spawning a command shell — should trigger an immediate, high-severity alert.

Forensic Readiness

In the event of a suspected supply chain breach, time is critical. Incident response teams need immediate access to logs, artifacts, and memory dumps. Forensic readiness means having the telemetry enabled and the retention policies set before the incident occurs.

Kill Switches

You need the ability to sever the connection to a compromised vendor instantly. This isn’t about sending an email to the firewall team. It means having an automated playbook that can block a vendor’s IP range, revoke their certificates, and disable their accounts across the entire enterprise with a single authorization.

How to Detect Supply Chain Attacks with Torq

Traditional SOAR platforms and generic risk management tools struggle with supply chain attacks because they are siloed. They see the alert, but they cannot see the context, and they certainly cannot touch the infrastructure to fix it.

Torq HyperSOC serves as the connective tissue between your governance, development, and security operations.

Automating Intake and Triage for New Supply Chain Risks

When a new zero-day vulnerability in a common library (like Log4j) is announced, the first question every CISO asks is: Where are we vulnerable?

Manual discovery takes weeks. Responding to an incident with Hyperautomation is faster.

Torq automates this in minutes:

  • Ingestion: Torq ingests vulnerability data from threat intel feeds.
  • Correlation: It automatically queries your CMDB, cloud security posture management (CSPM) tools, and code repositories to identify every asset running the vulnerable version.
  • Context: It enriches this data with business context. A vulnerable server exposed to the internet is prioritized over a vulnerable air-gapped test machine.

Orchestrating Response Across the Stack

Torq integrates with over 300 enterprise tools, allowing it to take action across the entire stack.

  • Vendor isolation: If a vendor is compromised, Torq can trigger workflows to revoke their IAM access, block their IPs at the firewall, and suspend their VPN sessions instantly.
  • Automated patching: For software vulnerabilities, Torq can trigger patching workflows via your endpoint management systems or open tickets in Jira for developers with the specific upgrade instructions attached.
  • Communication: Torq creates a dedicated war room channel in Slack or Teams, inviting the relevant stakeholders and posting real-time updates from the investigation.

Applying Agentic AI for Vendor Risk

Torq Socrates — the AI SOC Analyst — takes vendor management to the next level. It can parse incoming vendor security emails, identifying notifications of breaches or updates. It can autonomously reach out to vendors to request updated compliance documents or status on vulnerability remediation, parsing their responses and updating the risk register without human intervention.

By automating the tedious work of verification and the critical work of isolation, Torq allows security teams to move faster than the supply chain contagion.

From Blind Trust to Automated Verification

The era of trusting the ecosystem is over. Verification is the new standard. Supply chain attack prevention is not a box to check; it is a continuous operational discipline that requires deep visibility, rigorous governance, and the ability to act instantly.

Checklists and questionnaires are artifacts of the past. The future of supply chain security belongs to SOC automation. You need a platform that can map your risks, monitor your vendors, and enforce your controls at the speed of code.

Stop relying on trust. Start relying on verification and automation.

Reimagine your defenses. Explore Torq for SOC resilience in our Don’t Die, Get Torq manifesto.

FAQs

What is a supply chain attack, and why are enterprises so vulnerable to them?

A supply chain attack occurs when an adversary compromises a trusted vendor, service provider, or upstream software component to infiltrate downstream environments. Because these pathways rely on trust, they bypass traditional controls — making supply chain attack prevention a core requirement for modern enterprises.

What are the main types of supply chain attacks organizations should be prepared for?

The most common types of supply chain attacks include software supply chain compromise, hardware or firmware tampering, and vendor access breaches. Each requires different controls, from provenance enforcement to continuous vendor monitoring.

What are the best supply chain security best practices for enterprises in 2026?

Effective supply chain security best practices include hardening CI/CD pipelines, enforcing code provenance, verifying hardware integrity, continuously monitoring vendor risk, enforcing least privilege access, and automating asset discovery. Automation ensures these controls operate at scale.

How do you mitigate risk in the supply chain when attackers target upstream software and vendors?

Enterprises can mitigate risk in the supply chain by combining automated vulnerability correlation, real-time vendor access governance, anomaly detection, and rapid isolation playbooks. Platforms like Torq automate discovery, prioritization, and containment across the entire stack.

What are some real-world software supply chain attack examples, and what can we learn from them?

High-impact software supply chain attacks — such as SolarWinds, Log4j, and the XZ Utils backdoor — show how a compromise in a single upstream dependency can cascade across thousands of organizations. These supply chain attack examples underscore the need for automated detection, provenance validation, and fast response mechanisms.

Are there any industry standards for supply chain attack prevention?

Yes, several frameworks provide industry standards for supply chain attack prevention. Key standards include NIST SP 800-161 (Cybersecurity Supply Chain Risk Management), ISO/IEC 27036 (Information Security for Supplier Relationships), and SLSA (Supply-chain Levels for Software Artifacts), which focuses specifically on securing software build pipelines. Adopting these standards helps organizations establish a baseline for vendor governance and software integrity.

Can you explain the main warning signs of a possible supply chain attack?

The main warning signs of a possible supply chain attack often appear as anomalies in trusted channels. Indicators include unauthorized configuration changes by service accounts, unexpected outbound traffic from updated software to unknown IP addresses, sudden spikes in resource usage after a vendor patch, or login attempts from vendor accounts at unusual times. Detecting these signs requires continuous behavioral monitoring and automated anomaly detection tools.

SEE TORQ IN ACTION

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

Compuquip logo in white

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

Fiverr logo in black

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

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“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

Riskified logo in white

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

The Best Incident Response Tools & How to Automate Them with Torq

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If you ask ten security architects to draw their incident response stack on a whiteboard, you will get ten different diagrams that all share one common feature: chaos.

The modern SOC is a museum of standalone best-of-breed tools. Endpoint tools excel at process behavior, SIEMs aggregate vast log volumes, cloud security platforms surface exposure and misconfigurations, and identity systems track user activity, each operating in its own domain and language. The challenge isn’t the tools themselves, but the operational sprawl that emerges when these systems run independently, forcing analysts to manually stitch together partial views of the same incident.

Effective incident response isn’t just about having the right tools; it’s about making them talk to each other. The traditional approach of buying more dashboards to solve the problem of too many dashboards is over.

This blog breaks down the essential incident response tools you actually need and, more importantly, how to use Torq to turn that disconnected jumble of software into a coordinated, autonomous defense system.

What Are Incident Response Tools?

Incident response tools are the specialized software and platforms security teams use to detect, investigate, contain, and recover from cyber incidents. They sit across the incident response lifecycle — supporting detection, analysis, containment, eradication, and recovery.

At their core, these SOC tools help you:

  • Detect when something is wrong (suspicious activity, malware, policy violations).
  • Investigate quickly (who, what, where, when, and how)
  • Respond and recover (contain the threat, remediate, and restore normal operations)

Without them, you’re flying blind. With them, you have visibility — but often so much data and so many consoles that you struggle to turn information into action.

Incident Response Lifecycle Placement

Different tools own different parts of the NIST or SANS frameworks. Typical incident response tools map to them like this:

  • Preparation: Threat intelligence platforms, vulnerability scanners, configuration management, incident response runbooks, and playbooks
  • Detection & analysis: SIEM, EDR/XDR, cloud monitoring tools, email security, UEBA
  • Containment, eradication & recovery: Firewalls and gateways, IAM tools, EDR isolation, sandboxing, patch and configuration management, ticketing/ITSM systems
  • Post-incident activity: Case management, reporting and dashboards, evidence archiving, and analytics on incident response procedures (MTTR, first-pass resolution, automation coverage)

Gaps in Traditional Tooling

The industry secret: most incident response tools were designed to be operated manually, one at a time, by humans.

  • Manual handoffs: An alert in the EDR doesn’t automatically trigger a firewall block. A human has to read the alert, log into the firewall, and type the rule. This latency is where attackers live.
  • Alert overload: Tools are incentivized to be noisy. A SIEM that generates zero alerts looks broken, so it generates thousands. This creates alert fatigue, where analysts miss the signal because of the noise.
  • Siloed context: Your Identity provider knows who the user is. Your EDR knows what the process is. But neither tool talks to the other to ask, “Should this user be running that process?”

That’s why modern SOCs are moving beyond tools alone toward security Hyperautomation — using automation and orchestration to stitch all of this together.

5 Types of Incident Response Tools Used by Security Teams

To build a functional stack, you need coverage across four distinct categories. Here is the breakdown of the tools typically found in a mature SOC.

1. Detection and Alerting Tools

These platforms collect telemetry and generate alerts when something suspicious occurs.

  • SIEM (Security Information and Event Management): The central aggregation and correlation layer for logs and events.
    • Splunk, Microsoft Sentinel, Datadog
  • EDR (Endpoint Detection and Response): Agents on endpoints and workloads that monitor process execution, file changes, and behavioral indicators.
    • CrowdStrike Falcon, SentinelOne, Microsoft Defender for Endpoint
  • NDR (Network Detection and Response): Observes network traffic to detect anomalies and threats missed at the endpoint.
    • Corelight, Darktrace
  • Cloud Monitoring Platforms: Cloud security posture and runtime monitoring for public cloud environments.
    • Wiz, Orca Security, Lacework

2. Investigation and Enrichment Tools

These tools help validate alerts and gather additional context. Is this IP bad? Is this hash known malware?

  • Threat Intelligence: Provide external intelligence on IPs, domains, file hashes, and attacker TTPs.
  • Log Analysis: Tools (often your SIEM or data lake) that allow deep queries over raw logs and telemetry.
  • Case Management: Systems of record for investigation and incident response procedures.
    • Jira, ServiceNow

3. Containment and Response Tools

These tools enable rapid containment and remediation.

  • Firewalls/SASE: Block malicious IPs, domains, and traffic patterns as part of containment.
    • Palo Alto Networks, Zscaler, Check Point 
  • Access Controls (IAM): Revoke sessions, enforce MFA, reset credentials, and adjust group memberships.
    • Okta, Azure AD (Entra ID), Duo
  • Endpoint Isolation: Network-isolate a compromised host, kill malicious processes, and remove persistence.
    • EDRs like Crowdstrike Falcon and Microsoft Defender

4. Communication and Reporting Tools

Incident response is a team sport. You need to talk to IT, Legal, and HR.

  • Collaboration Platforms:  Real-time “war room” coordination across SecOps, IT, Legal, and leadership.
    • Slack, Microsoft Teams, Zoom 
  • Dashboards: Visualization tools that show the CISO the current threat status.
  • Documentation: Store runbooks, incident response steps, and post-incident reports.
    • Wikis or knowledge bases like Confluence

5. Hyperautomation 

These platforms orchestrate the entire incident response lifecycle end to end. Instead of analysts stitching tools together manually, Hyperautomation connects detection, enrichment, containment, and communication into one cohesive flow.

How Automation Transforms Incident Response Workflows

Traditional incident response is linear and human-dependent. An alert fires, a human looks at it, a human investigates, and a human remediates. This model fails at scale.

Security Hyperautomation transforms this process from a relay race into a unified, autonomous machine.

From Reactive to Autonomous

The shift is from static playbooks to dynamic, automated workflows.

  • Static: “If malware is detected, analyst logs into Okta and suspends user.”
  • Dynamic: “If malware is detected, Torq immediately suspends the user via API, creates a Jira ticket, messages the manager on Slack, and isolates the endpoint — all in less than a minute.”

Torq workflows can also adapt based on context. For example:

  • Check the user’s role (is this a privileged admin or an executive?)
  • Check asset criticality (is this a production database or a test VM?)
  • Adjust the incident response steps based on risk (e.g., require approval for high-impact actions)

Role of Security Hyperautomation

Hyperautomation is the concept of automating everything that can be automated. Torq’s platform serves as the connective tissue. It uses API-first integrations to ingest alerts from any detection tool and orchestrate actions in any response tool. It’s no-code, meaning security architects can build these complex flows visually without waiting for software engineering resources.

Key Benefits for Security Teams

  • Faster response times: We are talking about reducing MTTR from days or hours to seconds. Automation moves at machine speed.
  • Reduced manual work: By automating the Tier-1 triage and containment tasks (the boring stuff), you free up your analysts to do actual threat hunting and critical thinking.
  • Improved consistency and scalability: A workflow never gets tired, never forgets a step, and never calls in sick. Whether you have 10 alerts or 10,000, the process execution is identical.

Orchestrating Incident Response Tools with Torq: Real-World Use Cases

Let’s look at how this works in practice. Here are three common scenarios where Torq turns disconnected tools into a unified response capability.

Automated Phishing Response

Phishing is a high-volume, low-fidelity problem that drowns SOC teams.

With Torq:

  • User reports a suspicious email (via phishing button or ticket).
  • Torq ingests the event from email security or the mailbox.
  • Torq automatically:
    • Extracts URLs, attachments, and headers.
    • Checks them against Recorded Future, VirusTotal, and other threat intel tools.
    • If malicious, deletes messages across all affected inboxes (via M365 or Google Workspace API).
    • Triggers IAM actions like forcing a password reset or revoking sessions.
    • Posts a full summary and evidence to a dedicated Slack or Teams channel.

What used to take many minutes per email now completes in seconds, and analysts only step in for edge cases.

Coordinated Ransomware Containment

Ransomware moves laterally in minutes. Human response is too slow.

With Torq:

  • Torq receives the detection alert via webhook or SIEM. It Immediately:
  • Commands the EDR to isolate the host from the network.
  • Adds temporary firewall rules to block traffic from the affected IP or subnet.
  • Revokes the user’s active sessions via IAM.
  • Opens a high-severity incident in ServiceNow or Jira
  • Spins up a “war room” channel in Slack or Teams and notifies the on-call IR team.

By the time an analyst joins the call, initial containment is done and they can focus on deeper investigation and recovery instead of scrambling through manual steps.

Enrichment and Triage at Scale

Alert fatigue comes from a lack of context. SIEM alerts like impossible travel or suspicious login are common — but without context, they’re hard to triage.

With Torq:

Torq receives a “suspicious login” alert. It automatically:

  • Checks the user’s recent login history in the IdP.
  • Pulls device posture from EDR.
  • Looks up IP reputation in threat intelligence.
  • Optionally messages the user via Slack, Teams, or email: “Was this you?”

If the user confirms, Torq records the outcome and closes the case. If they deny or don’t respond, Torq escalates the incident, applies containment actions, and routes it to the right analyst with full context.

Choosing the Right Approach: Tools Alone Aren’t Enough

There’s a common trap in cybersecurity: assuming that buying one more “next-gen” tool will fix structural problems in incident response.

It won’t.

What to Look for in a Modern IR Ecosystem

When evaluating incident response tools and platforms, prioritize:

  • Open, well-documented APIs for ingesting alerts and triggering actions
  • Interoperability with your existing stack (SIEM, EDR, IAM, cloud, email security, ITSM)
  • Automation readiness, not just dashboards
  • Flexible deployment that works across hybrid and multi-cloud environments

Don’t Just Buy More Tools, Orchestrate Them

Instead of adding another dashboard to the pile, invest in the layer that sits above them. A Hyperautomation platform like Torq acts as a force multiplier for every other investment you have made. It makes your EDR faster. It makes your threat intel more actionable. It makes your analysts smarter.

Why Torq Is Built for Modern IR Challenges

Torq was built because legacy SOAR (Security Orchestration, Automation, and Response) tools failed. They were too complex, too rigid, and too hard to maintain. In comparison, Torq has:

  • Agentless automation: Deploy in minutes, not months.
  • AI workflows: Use Socrates, Torq’s AI SOC Analyst, to reason through alerts and make decisions, not just follow scripts.
  • No-code customization: Drag-and-drop workflow building that allows you to adapt to new threats instantly.
  • Enterprise scale: Built to handle the millions of events that modern cloud environments generate.

Plug-and-Play with Any IR Stack

Torq is agentless and tool-agnostic:

  • It connects via APIs to your existing incident response tools, including SIEM, EDR/XDR, IAM, firewalls, cloud platforms, ticketing systems, and threat intelligence.
  • It doesn’t require agents on endpoints or rip-and-replace projects.
  • If you swap tools (e.g., move from Splunk to Sentinel), you update integrations in Torq and keep your incident response workflows intact.

That makes your incident response architecture future-proof: your automation logic lives above any single vendor.

Turn Your Incident Response Tools into an Autonomous Defense System

The bad guys are using automation. They are using scripts to scan your network, AI to write phishing emails, and bots to brute-force your accounts. You cannot fight them with manual processes and spreadsheets.

Incident response is no longer about who has the best tools; it’s about who has the fastest, most integrated workflows. Empower your security team by orchestrating your stack with Torq. 

Transform your incident response tools from a collection of noisy, disconnected boxes into a fast, intelligent, and autonomous defense system with Torq. Get the Don’t Die, Get Torq manifesto to learn more.

FAQs

What are the essential incident response tools for a modern SOC?

The essential incident response tools for a modern SOC include Detection tools (SIEM, EDR/XDR, NDR), Investigation tools (Threat Intelligence, Log Analysis), Containment tools (Firewalls, IAM, Endpoint Isolation), and Communication tools (Slack/Teams, Ticketing Systems). Leading the stack is a Hyperautomation platform like Torq, which connects these disjointed tools into a unified, autonomous workflow.

How can I automate incident response workflows effectively?

To automate incident response workflows effectively, implement a Hyperautomation platform that orchestrates actions across your security stack via APIs. Start by automating high-volume, repetitive tasks like phishing triage, user verification, and IOC enrichment. This allows your tools to autonomously detect threats, enrich alerts with context, and execute containment actions (like blocking IPs or suspending users) without manual intervention.

Why do legacy SOAR tools fail at incident response?

Legacy SOAR tools fail because they are often rigid, complex, and reliant on static playbooks that cannot adapt to dynamic threats. They struggle with high alert volumes, lack intuitive integration capabilities, and require significant maintenance overhead. Modern Hyperautomation platforms replace legacy SOAR by offering flexible, AI-driven workflows that scale effortlessly and empower analysts with no-code/low-code building.

What is the difference between automated and manual incident response?

Manual incident response relies on human analysts to detect alerts, switch between multiple dashboards for investigation, and manually execute remediation steps, which is slow and prone to error. Automated incident response uses software to instantly detect anomalies, enrich data, and execute pre-defined containment actions at machine speed, significantly reducing Mean Time to Respond (MTTR) and analyst burnout.

How does Torq integrate with existing incident response tools?

Torq integrates with existing incident response tools through an agentless, API-first architecture. It connects seamlessly with SIEMs (like Splunk), EDRs (like CrowdStrike), Identity providers (like Okta), and communication platforms (like Slack) without requiring custom code. This allows security teams to orchestrate complex workflows across their entire stack and swap tools easily without breaking their automation logic.

SEE TORQ IN ACTION

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

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“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

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“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

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“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

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“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

The 2025 Content Vault: Everything You Need to Automate Your SOC

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2025 marked a significant shift in the security operations landscape. The industry focus moved beyond simple task automation to full-scale autonomy, driven by the adoption of agentic AI and Hyperautomation.

Throughout the year, we documented this transition through technical research, strategic frameworks, and real-world implementation stories. We have compiled our most impactful resources into this single library to help security leaders and practitioners benchmark their progress and plan for the year ahead.

Here is a comprehensive roundup of the case studies, strategic guides, and technical sessions that defined 2025.

Top Blogs of 2025: The Concepts Fueling the Next-Gen SOC

From defining new tech categories to debunking legacy metrics, these were Torq’s hottest reads of the year.

The Year of Agentic AI and The AI SOC

  • Agentic AI in the SOC: Everyone talked about AI in SecOps in 2025, but we defined it. This post cuts through the chatbot hype to explain what agentic AI actually is: autonomous, goal-oriented, and capable of reasoning through threats without a human babysitter. 
  • The AI SOC: The legacy SOC model is broken. This foundational piece lays out the architecture of the future, where data ingestion, analysis, and response happen at machine speed, and humans stop acting like glue for broken tools. 
  • The Multi-Agent System: Why hire one AI Agent when you can have a coordinated team? We break down why a multi-agent system (MAS) is the only architecture robust enough to handle the complexity of the modern enterprise. 
  • Meet Socrates, the AI SOC Analyst: Tired of Tier-1 burnout? This blog introduces Socrates, Torq’s AI SOC Analyst — a digital teammate that investigates, documents, and remediates alerts 24/7/365. 
  • Torq HyperAgents: HyperAgents were a breakout highlight in 2025 — fully goal-driven AI operators that plan, reason, and execute end-to-end security workflows. This post breaks down how they outperform playbooks and why early adopters use them to wipe out Tier-1 workload.

Product and Innovation: What Torq Shipped in 2025

  • HyperSOC 2.0: We took HyperSOC and made it faster, smarter, and more intuitive. If you missed the launch details of HyperSOC-2o, catch up on the specs that are redefining speed. 
  • gRPC-Web in Front-End Applications: For the builders and the engineers, this blog draws back the curtain on the tech stack that powers Torq’s blazing-fast interface. A must-read for anyone who loves engineering excellence.
  • The Model Context Protocol (MCP): Connectivity is everything. We explore the Model Context Protocol and how standardizing AI context exchanges is the key to unlocking truly interoperable security tools. 
  • AI Security Operations Workflows: Static playbooks are dead. This post dives into how dynamic, AI-driven workflows adapt in real-time to the threat context, ensuring you’re never stuck following a rigid script when the situation changes. 
  • Torq Case Management: Unlike ticket-based systems retrofitted with automation, Torq Case Management is AI-native from the ground up — built to ingest millions of events, correlate signals across your entire stack, and drive end-to-end investigation and response without human busywork. This is the future of case management for autonomous SOCs.

Strategy & Best Practices: Modern Frameworks for Modern SOCs

  • The Pyramid of Pain: We explain how Hyperautomation allows you to automate the top of the pyramid, making life miserable for attackers and easier for your team. 
  • MTTD vs. MTTR: Are you measuring activity or impact? Let’s settle the debate on detection vs. response metrics and show you which numbers actually prove ROI to the board. 
  • 10 Best SOC Tools: Your stack is probably bloated. This blog breaks down the essential tools for a modern defense and helps you identify which legacy anchors might be dragging you down.
  • 2025 Cybersecurity Best Practices: The fundamentals, modernized. From Zero Trust to automated governance, this is the checklist for staying resilient in a threat landscape that never sleeps. 

Executive Playbooks: Strategic Guides for CISOs in 2025

This year, we released four major resources designed to give you the blueprint for the Autonomous SOC.

  • Don’t Die. Get Torq. A blunt, data-backed manifesto showing why the legacy SOC model is collapsing and how Agentic AI + Hyperautomation give teams the only viable path to survive rising alert volume, burnout, and budget pressure.
  • The Tomorrow SOC: You can’t fight tomorrow’s threats with yesterday’s architecture. In partnership with Google Cloud, this guide maps out the infrastructure of the future-proof SOC, focusing on resilience, cloud-native scale, and data unity. 
  • Build the Autonomous SOC in 90 Days: Autonomy isn’t a five-year plan. It’s a quarterly objective. We laid out a concrete, week-by-week roadmap to transition your team from reactive ticket-taking to proactive, autonomous defense in just three months. 
  • The Threat Escalation Matrix: Triage is an art, but it should be a science. This resource provides a practical framework for defining exactly when, how, and why an automated alert should escalate to a human, helping you dial in your signal-to-noise ratio. 
Save your SOC with Torq HyperSOC

Customer Case Studies: Real-World Autonomy at Global Scale

See how global organizations applied Torq Hyperautomation™ to solve specific operational challenges.

  • Kenvue: When the world’s largest pure-play consumer health company (the home of Tylenol and Listerine) spun off, they needed a cloud-native security architecture from Day 1. See how they achieved rapid time-to-value and massive scale. 
  • Valvoline: Retail environments are notoriously difficult to secure. Valvoline used Torq to unify a distributed environment, automating the triage that used to bury their analysts and turning their SOC into a business enabler. 
  • Agoda: In the high-velocity world of travel tech, downtime is revenue lost. Agoda leveraged Torq to bring machine-speed response to their SOC, ensuring that security keeps pace with their massive transaction volumes. 
  • Bloomreach: Growth demands scalability. Bloomreach implemented Torq Hyperautomation to eliminate manual bottlenecks, enabling their security team to support rapid business expansion without simply adding more humans to the problem. 

AMP’d Sessions: The Integrations That Made the Autonomous SOC Real

Security is a team sport. Our AMP’d Sessions (Alliance & Momentum Partners) brought together the brightest minds and best tech in the industry to show what happens when best-of-breed tools actually talk to each other.

  • Wiz: Torq turns Wiz’s deep cloud visibility into instant remediation by automatically syncing DevSecOps contexts and closing the loop on critical risks before they become breaches
  • Panther: This partnership enables a seamless AI-to-AI handoff where Torq ingests Panther’s high-fidelity detections and immediately executes complex identity and network remediation at machine speed.
  • Cyera: Cyera’s data insights turn into immediate protection by autonomously revoking public access to sensitive files and verifying user intent in minutes.
  • Reco: Torq operationalizes Reco’s SaaS identity insights by autonomously revoking risky access and enforcing policy across the chaotic sprawl of apps and shadow AI tools.
  • Intezer: By handing Intezer’s verified forensic evidence directly to Torq’s AI SOC Analyst, we unlock true agent-to-agent collaboration that autonomously resolves 95% of Tier-1 threats without a single ticket.
  • Zscaler: When Zscaler Deception lures an attacker, Torq instantly correlates the high-fidelity alert and executes an agentic runbook to verify, isolate, and block the threat in under sixty seconds.
Torq AMP Sessions Ad

For MSSPs and MDRs: The New Playbook for High-Margin, Automation-First Services

2025 was the year MSSPs stopped treating automation as an add-on and started using it to redesign their entire delivery model. 

  • Don’t Die: Managed Services Edition: This manifesto reframes the MSSP challenge. Margins aren’t dying because of attackers — they’re dying from manual work, tool sprawl, and SLAs that no human-only team can sustain. 
  • HWG Sababa Case Study: MSSP HWG Sababa used Torq to increase throughput, shrink response times, and expand customer coverage without expanding headcount.
  • SOAR is Dead Managed Services Manifesto: A strategic guide for MSSPs shifting from “we’ll triage your alerts” to “we’ll deliver outcomes.” It outlines how automation, standardization, and AI-driven service tiers unlock better margins and foster stickier customer relationships.
  • Security MDR Deep Dive: This blog breaks down why MDR is converging with autonomous SOC operations — and why agentic AI will power the next generation of MDR offerings. The message was clear: the future of managed detection and response is automation-led, not analyst-led.
  • 2026 MSSP Trends: The biggest MSSP cybersecurity trends for 2026 — and how Hyperautomation is the only scalable path for managed security providers to meet rising customer expectations, close talent gaps, and deliver true autonomous outcomes across every environment.

Looking Ahead to 2026: The Year Autonomy Goes Mainstream

If 2025 was the year security teams proved that agentic AI and Hyperautomation work at enterprise scale, 2026 will be the year these capabilities become standard. The pressure on SOCs isn’t slowing — alert volume, cloud complexity, and identity-driven threats are all accelerating — and the gap between teams that automate and teams that don’t is widening fast.

The organizations leading this shift aren’t the ones hiring faster. They’re the ones designing for autonomy, unifying their data, and letting AI shoulder the work humans were never meant to do at volume. Torq will continue to invest heavily in multi-agent orchestration, AI-governed case management, and deeper ecosystem integrations so security teams can operate with more speed, clarity, and control.

If your goal in 2026 is to reduce MTTR, eliminate operational drag, and build a SOC that scales without expanding headcount, this library gives you the blueprint. And the next wave of innovation is already in motion.

FAQs

What is agentic AI in security automation?

Agentic AI refers to autonomous, goal-oriented artificial intelligence systems capable of reasoning through security threats without constant human oversight. Unlike traditional chatbots or rule-based systems, agentic AI can independently plan, reason, and execute end-to-end security workflows. In the SOC context, this means AI agents that investigate alerts, document findings, and remediate threats around the clock — functioning as digital teammates rather than simple automation scripts.

How does Hyperautomation enhance SOC capabilities?

Hyperautomation extends beyond basic task automation to enable full-scale autonomy in security operations. It combines multiple technologies — including AI, machine learning, and orchestration platforms — to handle data ingestion, analysis, and response at machine speed. This approach eliminates the need for humans to act as “glue” between disconnected tools, allowing security teams to shift from reactive ticket-taking to proactive, autonomous defense.

What are the benefits of using AI in cybersecurity?

Key benefits include:

  • Elimination of Tier-1 alert fatigue: AI analysts can handle 100% of initial alert triage, freeing human analysts for strategic work
  • 24/7/365 coverage: AI systems investigate and respond to threats continuously without burnout or shift limitations
  • Machine-speed response: Detection, correlation, and remediation happen in seconds rather than hours
  • Scalability without headcount expansion: Organizations can handle increasing alert volumes and cloud complexity without proportionally growing their teams
  • Consistent documentation: Every investigation is thoroughly documented, improving compliance and institutional knowledge
How can security automation improve threat response times?

Automation dramatically reduces both Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR) by:

  • Instantly correlating signals across the entire security stack
  • Executing pre-defined and dynamic response workflows without waiting for human intervention
  • Enabling AI-to-AI handoffs between detection and response platforms
  • Automating verification, isolation, and blocking sequences that previously required multiple manual steps

Organizations using Hyperautomation report response times measured in seconds rather than minutes or hours.

How quickly can organizations implement an autonomous SOC?

Based on structured implementation frameworks, organizations can transition from reactive operations to autonomous defense within 90 days. This involves a week-by-week roadmap covering platform deployment, workflow automation, AI agent configuration, and escalation policy refinement.

SEE TORQ IN ACTION

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

Compuquip logo in white

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

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“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

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“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

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“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

Enhancing Security Operations: A Practical Guide to Human-AI Collaboration in 2026

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Alert volumes are climbing, tool sprawl is paralyzing investigations, and the attack surface  — spanning identity, SaaS, and cloud — expands daily. 47% of SOCs face alerting issues, and a majority of SOCs spend more time maintaining tools than defending threats, according to a recent Splunk study. Security teams aren’t just overwhelmed; they’re outmatched by scale.

AI has arrived as the promised solution, supporting almost every phase of detection and response. But the real question facing CISOs and SOC leaders is this: How do you adopt AI in a way that is fast, safe, transparent, and trusted?

The answer isn’t humans alone, and it certainly isn’t AI alone. The future of the SOC lies in human-AI collaboration — a coordinated model where agentic AI executes high-volume, repetitive reasoning tasks, and humans apply judgment where it matters most.

This guide outlines a practical framework for building collaboration within modern SOCs, ensuring you achieve machine speed without sacrificing human control.

What Agentic AI Means in Cybersecurity (and Why It Matters)

To understand how humans and AI collaborate, we must first distinguish agentic AI from the chatbots and scripts of the past (Generative AI). Traditional automation follows a rigid track: If X happens, do Y. If the data format changes or the API hangs, the script fails. 

Agentic AI is different. It has agency. Agentic AI describes autonomous systems that possess a cognitive architecture capable of “thinking” through a workflow. Instead of just following a script, an agentic system:

  • Perceives: It ingests raw telemetry and recognizes anomalies (“This user behavior deviates from the baseline”).
  • Plans: It breaks a high-level goal (“Investigate phishing”) into a sequence of logical steps.
  • Reasons: It makes decisions based on context. If a tool fails, it doesn’t crash; it attempts an alternative route or query.
  • Acts: It uses “hands”— integrations and APIs — to execute changes in the environment, such as blocking an IP or isolating a host.
  • Reflects: It evaluates the output of its actions to ensure the goal was met.

This shifts the way a SOC works. AI is no longer just a tool you click; it is a digital teammate that handles mechanical work — enrichment, correlation, evidence gathering, and repetitive decision-making — so humans can focus on oversight, interpretation, and policy refinement.

Understanding Human-AI Collaboration in the SOC

A functional human-AI collaborative model depends on a clear division of labor.

Where AI Leads:

  • Alert triage: Eliminating noise, enriching identity context, and grouping related alerts into coherent cases.
  • Deep investigation: Retrieving user login history, mapping device posture, and correlating signals across the stack (SIEM, EDR, IAM).
  • SaaS governance: Discovering shadow AI tools and validating risky OAuth scopes instantly.
  • Cloud assessment: Checking severity, exposure, and potential blast radius across AWS, Azure, and GCP in near real time.

Where Humans Lead:

  • Risk interpretation: Making calls when business impact is ambiguous or context is offline.
  • Exception handling: Approving high-risk access requests or sensitive identity changes.
  • Strategic decisions: Refining detection logic, setting policy guardrails, and managing data privacy.

This division only works when humans trust the AI system’s reasoning. That trust has to be earned.

A Framework for Trust Calibration in AI-Driven SOCs

The biggest barrier to AI adoption isn’t capability; it’s confidence. Trust is earned when AI behaves predictably and transparently. This Trust Calibration Framework can help organizations evaluate and strengthen this relationship.

1. Transparency 

An AI Agent must show its work. It is not enough to present a verdict; the agent must display the chain of thought.

In practice, Torq Socrates includes step-by-step rationale, evidence, and source logs in every case summary. Analysts don’t just see “Blocked IP” — they see the specific threat intel matches and user behavior anomalies that led to that decision.

2. Consistency 

AI should act predictably across environments, identities, and tenants.

This requires agentic AI systems that can reason through adaptive tasks while strictly adhering to defined rules and logic flows. 

3. Guardrails

Humans define the boundaries; AI operates within them. Examples include identity policy limits, restricted actions for sensitive roles (like the C-Suite), and mandatory approval flows for high-risk changes.

Torq builds these guardrails into the core of HyperSOC™, ensuring that speed never comes at the expense of governance.

4. Escalation 

An intelligent agent knows what it doesn’t know. It must be programmed to recognize ambiguity and hand the case to a human.

Typical triggers include legal/regulatory implications, conflicting signals across tools, or access attempts involving sensitive data. This keeps automation aligned with business context.

5. Measurement 

Trust grows through data, not intuition.

Key metrics include: false positive reduction, percentage of autonomously resolved cases, and importantly, the rate of human overrides. If humans are constantly reversing AI decisions, calibration is off.

AI Trust Calibration Framework
PillarGoalHow Torq Delivers This Key Metrics 
TransparencyActions must be visible and auditableTorq provides workflow execution logs and case updates showing each step taken and all data passed between systems.Ability to trace every workflow action in logs
ConsistencyWorkflows should run the same way every timeTorq workflows execute deterministically based on triggers, steps, and conditions defined by the user.Workflow execution success/failure rate
GuardrailsSensitive actions require controlsTorq supports RBAC and workflow approval steps to restrict changes and require human sign-off.Number of workflows requiring approval; compliance with approval paths
EscalationComplex or sensitive events route to humansConditional logic determines when to assign or escalate a case to an analyst.Percentage of cases escalated by workflow conditions
MeasurementPerformance and outcomes must be trackableTorq Reporting dashboards show workflow metrics, case metrics, and execution history.MTTR, workflow success rate, case volume

A Practical Model for Autonomy for AI SOCs

Borrowing from academic research, AI in the SOC should operate on a tiered autonomy scale.

Level 1: AI Assists 

AI recommends. Humans decide.

Example: AI enriches an Okta impossible-travel alert with geo-velocity data, past login history, device posture, and recent MFA failures. It suggests: High-risk login. Recommend MFA reset. The analyst reviews the evidence and performs the action manually.

Level 2: AI Acts With Approval (Human-in-the-Loop)

AI can take action, but only after a human signs off.

Example: A phishing alert enters the SOC. AI pulls message headers, checks the attachment and URL reputation, and proposes: Remove this email from all inboxes and block the sender. The analyst clicks “Approve,” and the automation executes the full remediation workflow.

Level 3: AI Acts With Supervision (Human-on-the-Loop)

AI handles the task end-to-end but alerts a human if something looks unusual.

Example: A cloud alert reports a public S3 bucket containing sensitive files. AI validates exposure, removes the public ACL, notifies the bucket owner, and updates the case. If conflicting metadata appears (e.g., bucket belongs to a high-risk business unit), it escalates to an analyst for review.

Level 4: AI Acts Autonomously in Routine Scenarios

AI handles predictable, low-risk tasks with no human touch unless something breaks.

Example: AI detects a known malicious IP scanning the perimeter across multiple tenants. It automatically blocks the IP across firewalls, updates indicators in the SIEM, logs the action with evidence, and closes the case. No analyst is involved unless the block fails or impacts a critical system.

High-risk tasks stay at lower autonomy. Routine tasks move up the scale. This adaptive model ensures the right balance between speed and oversight.

How to Build This Model With Torq Today

You don’t need to rip and replace your stack to move toward an agentic AI security model. With Torq HyperSOC™, you can layer AI and automation on top of what you already have — starting small, proving value fast, and expanding from there.

1. Start With Tier-1 Autonomy

Begin where the pain is highest: Tier-1 triage. Use Torq workflows to automate the grunt work like enrichment, correlation, and initial routing. In practice, that means:

  • Triggering workflows from SIEM, EDR, email security, or webhook alerts
  • Enriching observables automatically (IPs, URLs, hashes, users) across your tools
  • Creating and updating Torq cases as part of the workflow, instead of forcing analysts to swivel between consoles

You can even use Torq’s AI-powered features to generate the first version of these workflows from a plain-language description, then refine them with your own logic. Once Tier-1 noise is under control, analysts immediately feel the difference: fewer repetitive clicks, more time for real investigations. 

2. Use AI Inside Workflows for Decisions

Next, infuse intelligence into those workflows. Torq’s AI Task operator lets you call large language models directly from any stage of a workflow to summarize evidence, extract observables, or propose next steps — without leaving the automation. 

Instead of a chatbot on the side, AI becomes part of the decision path to:

  • Summarize multi-tool telemetry into a readable case note
  • Draft Slack or email messages to users for verification
  • Propose a severity level or recommended action based on the collected context

Humans still own the final call, but AI does the heavy lifting — exactly what Human–AI collaboration should look like in an AI SOC.

3. Build Human-in-the-Loop Guardrails Where Needed

Not every action should be fully autonomous, and Torq’s AI governance features reflect that. Use workflow approval patterns and access-control templates to hard-code where humans must step in:

  • Add explicit approval steps before sensitive actions like account lockouts, high-risk group changes, or production firewall changes
  • Use Slack or Teams approval flows for identity and access workflows (for example, just-in-time access or group membership changes)
  • Leverage Torq roles so only specific users can publish or modify high-impact workflows

This lets you keep routine automation fast while enforcing strong human guardrails around identity, data movement, and privileged operations. 

4. Unify Case Management and Measurement

Finally, stop scattering decisions across five tools. Use case management as the single place where alerts, context, AI outputs, and actions come together. Workflows can automatically:

  • Create cases when certain alerts arrive
  • Attach enrichment results and AI-generated summaries
  • Update status, severity, and assignees as the investigation progresses

From there, Torq Reporting gives you the dashboards to measure what actually changed: how many cases are auto-resolved, how MTTR is trending, and where humans are still overriding automation. Those metrics are your calibration loop; the data that tells you when to increase, decrease, or reshape autonomy across your security operations workflows. 

Why This Approach Works 

What you get with Torq is:

  • Reliability: Automation always operates in the same manner
  • Transparency: Every decision is logged and visible
  • Scalability: Workflows can automate thousands of alerts or remediation tasks
  • Flexibility: Easy to edit, iterate, and improve workflows without code
  • Control and governance: RBAC, approvals, and auditability keep humans in charge where it matters

Over time, this human-AI collaboration model delivers significant SOC uplift — fewer alerts, faster response, less toil, more focus on true threats.

The Future of the SOC is Human-AI Collaboration

Human-AI collaboration is transforming SOCs across industries. Leading organizations like Carvana and Valvoline are already proving this autonomous SOC model works, using Torq to pair agentic AI with human expertise to drive faster, safer outcomes.

Torq HyperSOC™ is built on this philosophy. We combine the speed of agentic AI with the transparency, guardrails, and governance required for enterprise security. And you don’t need to replace your stack or commit to “full autonomy.” You can start small — automate Tier-1 triage, add AI decisions inside workflows, and scale gradually using the Trust Calibration Framework.

This is how you reduce MTTR, increase resilience, and eliminate the operational drag that cripples most SOCs. And this is how you turn AI from a black box into a trusted teammate.

The future of the SOC is Torq. See how Torq’s Human-AI collaboration model eliminates Tier-1 overload, restores analyst bandwidth, and delivers resilience. Get the Don’t Die, Get Torq manifesto.  

FAQs

What is human-AI collaboration in security operations?

Human-AI collaboration is a security operating model where AI Agents handle high-volume, repetitive tasks — such as alert triage, data enrichment, and initial correlation — while human analysts focus on high-value tasks requiring strategic judgment, risk interpretation, and policy refinement. 

How do you build trust in AI for the SOC?

Building trust requires a Trust Calibration Framework focused on transparency and consistency. AI Agents must display their “chain of thought” (rationale and evidence) for every decision. Additionally, organizations should implement strict guardrails, such as mandatory human approvals for high-risk actions, and predefined escalation paths when the AI encounters ambiguity or sensitive contexts.

What is the difference between AI assistance and agentic AI?

AI assistance (like a standard chatbot) is passive; it waits for a human prompt to summarize data or write code. Agentic AI is active and goal-oriented. It can autonomously reason through a workflow, retrieve context, decide on next steps, and execute remediation actions within defined guardrails, functioning more like a digital teammate than a simple tool.

What are the levels of autonomy in an AI-driven SOC?

Academic research defines four key levels of autonomy for the SOC:

  • Level 1 (Assist): AI recommends actions; humans decide.
  • Level 2 (Approval): AI prepares the action; humans must approve execution (human-in-the-loop).
  • Level 3 (Supervision): AI acts end-to-end but alerts humans for unusual outliers (human-on-the-loop).
  • Level 4 (Autonomous): AI handles routine, predictable tasks entirely without human intervention.
How can legacy SOCs implement human-AI collaboration?

You do not need to replace your entire security stack. Platforms like Torq HyperSOC™ layer over existing tools (SIEM, EDR, IAM) to introduce autonomous capabilities. SOCs can start by automating Tier-1 triage to clear noise, then gradually introduce human-in-the-loop checkpoints for remediation, allowing the organization to scale autonomy as trust in the system grows.

SEE TORQ IN ACTION

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“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

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“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

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“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

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“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

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“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO