90 Days to SOC Autonomy: How Torq Customers Get There

By Torq

September 16, 2025

8 Minute Read

The 90-Day Path to SOC Autonomy

30 Days: Kickoff, Connect, and Ship Quick Wins

In the first 30 days with Torq, 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, AWS, etc, and launches the first workflows — phishing triage, EDR alert handling, or cloud misconfiguration detection.

During this phase, your builders are also 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.

60 Days: Scale Coverage, Standardize, and Measure

In the next thirty days, the focus shifts to 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 — especially valuable for MSSPs managing multiple tenants. Automation KPIs like MTTR, suppression rate, and analyst touches per case are established to measure impact. At this stage, broader automation coverage reduces false positives, alert fatigue decreases, and builders independently ship new workflows.

90 Days: Autonomous with Humans on the Loop

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 (QBR).

The outcomes are transformative: up to 90% of Tier-1 alerts are automated end-to-end, MTTR drops by more than 60% on core use cases, and analysts shift from reactive case handling to proactive oversight, threat hunting, and strategic improvements.

What to Measure in the First 90 Days of Your AI SOC

Adopting Torq isn’t just about improving detection and response; it’s about proving measurable business impact within the first 90 days. Here are the key metrics to track:

MTTR/MTTI: Compare before-and-after times across common use cases to demonstrate immediate efficiency gains.
Automation coverage: Track the percentage of Tier-1 alerts that Torq fully handles end-to-end. Mature customers often see ~90% automation coverage by day 90.
Suppression rate: Measure how many false positives are automatically identified, documented, and closed with retained evidence — cutting analyst workload and improving accuracy.
Analyst touches per case: For Tier-1 incidents, the target is near-zero touches. Analysts should only step in for risk-gated actions or escalations.
Onboarding hours per tenant (MSSPs): For managed services, this is a critical margin lever. Track the reduction in time to first value when onboarding new customers.
Tool consolidation savings: Document scripts, point automations, and legacy SOAR licenses retired as Torq unifies orchestration into a single platform.
Audit readiness: With evidence generated automatically in real time, compliance prep shifts from weeks of manual effort to hours of reporting.

Torq ensures customers hit these ROI milestones with a dedicated team, JumpStart implementation accelerators, and the Torq Academy training program. Teams also have 24/7 access to the Torq Knowledge Base for self-service support. This combination of hands-on guidance and self-service enablement ensures both rapid adoption and long-term maturity.

90-Day Autonomous SOC Wins From Torq Customers

Valvoline: Saving Analysts 6–7 Hours a Day

When Valvoline’s security team faced major resource constraints during a corporate divestiture, they needed a platform that could help them do more with fewer analysts. Within just one week of deploying Torq, Valvoline was up and running on its top-priority use cases, including phishing response and EDR alert handling.

Torq’s no-code workflows immediately cut down on repetitive triage work, saving analysts between six and seven hours every single day. A Rapid7 integration that had stalled for months under their legacy SOAR was delivered in just days with Torq, proving the platform’s ability to integrate seamlessly and deliver value fast.

Learn how to easily migrate from SOAR to Torq >

Global Health and Wellness Company: Proving SOC Value with Data in 60 Days

A global health and wellness company needed a way to bring visibility and maturity to its in-house SOC. With Torq, they stood up full end-to-end case management in just six weeks, consolidating data across SIEM, cloud, and identity tools. Within two months, the team had automated 89% of cases and reduced MTTR by 60%.

Beyond efficiency gains, Torq’s case taxonomy and structured workflows gave this organization the ability to present clear, data-driven ROI narratives to executives, transforming the SOC from a reactive cost center into a proactive value generator.

HWG Sababa: Doubles SOC Output Without Adding Headcount

Italian MSSP HWG Sababa serves customers across Europe, the Middle East, and Central Asia. Before Torq, their analysts were drowning in manual Tier-1 tasks, struggling to meet customer SLAs without expanding headcount. By deploying Torq Hyperautomation™, HWG Sababa automated 55% of their monthly alerts within weeks. MTTR dropped by 95% for low- and medium-priority incidents and by 85% for high-priority threats.

This surge in security automation nearly doubled the SOC’s operational capacity, allowing analysts to focus on advanced investigations and strategic work while still delivering faster, more consistent outcomes to customers.

Global Online Money Transfer Platform: Cuts Alert Handling Time by 30%

A leading financial services provider replaced its in-house threat management system with Torq Hyperautomation and saw immediate results. Within days, the team unified its entire security stack — AWS, Microsoft 365, Active Directory, SentinelOne, and more — into Torq’s platform.

The outcome: 30% time savings, 90%+ of alerts automatically investigated and remediated, and IAM tasks reduced from a full day of work to just three minutes. With enterprise-grade, multi-tenant architecture meeting strict regulatory demands, the company now scales security operations efficiently without adding headcount, all while maintaining compliance across global finance regulations.

Why Customers Ramp Up Fast with Torq HyperSOC

Agentic AI (Socrates): At the core of Torq HyperSOC™ is Socrates, our AI SOC Analyst, designed to handle the full case lifecycle for Tier-1 and Tier-2 incidents. Socrates automatically triages incoming alerts, enriches them with context from threat intelligence and internal data sources, documents every step, and even remediates routine cases without human intervention. By offloading repetitive triage and investigation tasks, Socrates drastically reduces MTTR while ensuring every action is logged, auditable, and defensible. Analysts are only engaged when higher-value judgment or escalations are required.

No-code/low-code and AI workflow builder: Torq empowers both analysts and engineers with a no-code/low-code and AI workflow builder, while still offering full-code capabilities for team members who want to go deep. Teams can design and deploy complex workflows in hours instead of weeks using a drag-and-drop canvas. Reusable subflows and golden templates accelerate scale, while audit-ready logging ensures every action is captured for compliance and accountability. This approach eliminates the need for scarce developer resources while allowing security teams to easily adapt and expand their automations as threats evolve.

300+ prebuilt integrations: Torq connects to virtually any tool in the modern SOC ecosystem, with hundreds of prebuilt integrations covering SIEM, EDR/XDR, IAM, cloud platforms, ITSM systems, email and chat, and threat intelligence sources. Torq offers containerized and custom connectors for niche or proprietary tools to ensure nothing is left out. This deep integration library makes Torq the connective tissue of your SOC, breaking down silos and ensuring every system can work together in real time.

Built for scale: Unlike legacy SOAR, Torq is designed for modern enterprise and MSSP scale. Its multi-tenant, event-driven architecture supports seamless onboarding across multiple environments without duplicating infrastructure. Workflows execute in parallel at massive scale, enabling real-time enrichment and response even in the face of thousands of daily alerts. Enterprise-grade role-based access control (RBAC) and single sign-on (SSO) provide the governance and security compliance needed to run automation at scale across complex organizations and managed service environments.

Get Your SOC Autonomous in 90 Days

If you’re building a modern SOC, you don’t need more dashboards — you need outcomes.

In 90 days, Torq HyperSOC turns “too many alerts, too little time” into a repeatable, autonomous system: ~90% of Tier-1 handled end-to-end, MTTR slashed, and analysts freed up for threat hunting and strategy. Socrates drives the case lifecycle, the no-code and AI workflow builder scales your best practices, and 300+ integrations make your entire stack work as one.

Stop fighting backlog with headcount. Start operationalizing automation with guardrails, evidence, and real ROI your leadership can see by the next business quarter.

Get the 90-Day Roadmap

Torq for MDRs: Increase Margin and Onboard Customers Faster

By Torq

September 10, 2025

6 Minute Read

Managed detection and response (MDR) providers faceskyrocketing demand and rising stakes. The MDR market is projected to grow to $11.8 billion by 2029 (up from $4.1 billion in 2024), a 23.5% compound annual growth rate driven by the intensifying landscape of advanced threats and sophisticated attacks, as well as ongoing cybersecurity talent shortages.

But as demand surges, security operations teams within MDRs are challenged to scale efficiently, deliver consistent SLA-backed services, and preserve razor-thin margins — all too often while relying on legacy security orchestration, automation, and response (SOAR) systems that crumble under cloud workloads and multi-tenant complexity.

To thrive in this new era, MDRs need a security automation platform that helps them scale efficiently, deliver measurable outcomes, and protect profitability. MDRs, meet Torq Hyperautomation™.

What is MDR and Why It Matters for Enterprises

Managed detection and response (MDR) is a security service model where organizations outsource their cyber threat monitoring, detection, and incident response to a dedicated provider.

Unlike traditional managed security service providers (MSSPs), which often focus on alerting, MDRs deliver hands-on investigation and active remediation — making them a critical lifeline for enterprises facing resource constraints, nonstop cyberattacks, and the need for stronger endpoint protection.

For enterprises, security operations through an MDR deliver three key benefits:

24/7 monitoring and response: Around-the-clock visibility and containment coverage when internal teams can’t keep pace with threat volume.
Access to scarce talent: MDRs provide experienced security analysts in a market plagued by skills shortages.
Faster detection and response: MDRs reduce dwell time by investigating, triaging, and remediating alerts before they escalate into costly breaches.

As enterprises embrace hybrid cloud, SaaS, and remote work at scale, the need for effective MDR solutions has never been greater. But delivering MDR services profitably requires providers to overcome the complexity of multi-tenant environments, tool sprawl, and the relentless flood of Tier-1 alerts.

Legacy SOAR promised to solve these challenges, but it wasn’t built for hybrid cloud or multi-tenant operations, leaving MDRs stuck with brittle playbooks, limited integrations, and endless tickets that drain security analysts instead of protecting customers. Then, security Hyperautomation entered the scene.

MDR Services and Solutions Enhanced by Hyperautomation

Torq Hyperautomation strengthens every cybersecurity service that MDRs deliver, helping providers meet rising demand without sacrificing margin by automating:

Threat detection and triage: Torq automates Tier-1 investigations, eliminating false positives and noise across tenants.
Incident response and auto-remediation: Hyperautomation streamlines workflows so low-level cases close autonomously while security analysts focus on complex cyber threats, ensuring providers can respond faster and consistently remediate incidents across all tenants.
Reporting: Torq creates customer-ready reporting and dashboards to demonstrate SLA performance and ROI, along with cross-tenant workspace reporting capabilities to understand big picture operational performance.

Torq consolidates workflows and automates repetitive responses to eliminate ticket fatigue — preventing analyst burnout while ensuring every customer receives consistent, SLA-backed protection. It also unifies operations across tenants so MDR services scale seamlessly, reduce manual burden, and deliver higher-value outcomes that drive stickiness.

Increasing Efficiency and Margin with MDR Security Automation

By ditching legacy SOAR, security MDRs can finally escape the inefficiencies that drain margins and stall growth. With Torq Hyperautomation, MDRs can:

Automate up to 90% of Tier-1 case analysis tasks with an autonomous AI SOC Analyst.
Onboard and provision new customer environments 18x faster.
Handle 5× more security events without increasing headcount.
Deliver higher-value services that reduce churn and increase stickiness.
Meet SLAs more consistently through automation-first response.
Consolidate tooling and integrate disparate systems to lower costs and increase efficiency.

Torq automates large portions of investigation, analysis, and response while also augmenting security analysts with AI-driven case summaries, natural language investigation, and intelligent prioritization. This reduces human time per case, enabling MDRs to process more events with the same headcount while keeping analysts focused on high-value investigations — better protecting both margins and customer outcomes.

Industry leaders have taken notice. IDC and GigaOm both identify Hyperautomation as the future of security automation, while one of the largest MDRs in the U.S., Deepwatch, has standardized on Torq Hyperautomation to drive global efficiency.

“With Torq Hyperautomation, we are significantly increasing productivity and efficiency, ensuring that our customers gain better evidence, analysis, and control over their cybersecurity, while staying protected from external threats and operational risks.”

– Charlie Thomas, CEO, Deepwatch

And because Torq supports no-code, low-code, and full-code approaches on a cloud-native, multi-tenant foundation, MDRs gain the flexibility to scale faster, improve case management with AI, and future-proof their operations.

MDR Cybersecurity: Faster Onboarding and Scalable Operations

Onboarding has historically been one of the biggest pain points for MDR providers, delaying ROI for both the provider and their customers. Torq automates onboarding so new tenants can be provisioned in minutes, not weeks, while repeatable workflows can be shared across environments for faster ramp-up.

10x faster onboarding: Standardize and automate customer onboarding and ramp-up, replicating proven workflows across tenants to onboard customers 18x faster.
Limitless integrations: Connect instantly with every tool in the customer’s stack, expanding value and widening the addressable market.

“New customers are seeing faster onboardings than we’ve ever seen.”

– Micah Donald, Sr. Director of Solutions Engineering, Deepwatch

Torq’s event-driven architecture ensures MDRs scale operations elastically across cloud environments, handle more events per analyst, and maintain SLA-backed performance as customer demand grows.

Choosing the Right Security MDR Provider for Your Organization

When evaluating MDR or managed security service providers, enterprises should look for:

Comprehensive service coverage that spans detection, investigation, and remediation.
Proven automation capabilities that enable faster response, SLA adherence, and cost savings.
Integration flexibility to work seamlessly with diverse and evolving enterprise stacks without lock-in.

By enabling security MDR service providers to automate Tier-1 case work, integrate with any customer stack, and standardize workflows across tenants, Torq not only helps MDRs scale profitably but also strengthens customer loyalty. The result is a service model that delivers consistent SLA-backed protection, measurable ROI, and the kind of resilience that enterprises demand from a long-term, strategic security partner.

The Future of MDR is Hyperautomation

The MDR market is exploding, but growth alone won’t guarantee success. Providers that cling to legacy SOAR will find themselves drowning in alerts, missing SLAs, and watching margins erode.

With Hyperautomation, security outcomes are delivered at machine speed, customers are onboarded in minutes, and undeniable ROI is proven with every engagement. Torq gives managed providers the scale, efficiency, and intelligence they need to thrive in a high-demand, margin-tight market, turning the challenges of multi-tenancy, tool sprawl, and endless Tier-1 noise into opportunities for growth and customer loyalty.

SOAR is dead (like, dead dead) — but it’s still killing managed services. Get the Managed Services Manifesto to see why Torq Hyperautomation is the future of scalable, SLA-ready MDR.

Get the Managed Services Manifesto

FAQs

What is the difference between MDRs and MSSPs?

Managed Security Service Providers (MSSPs) typically focus on monitoring and alerting, notifying customers when threats are detected. Managed Detection and Response (MDR) providers) go further by actively investigating, triaging, and remediating threats on behalf of customers, providing hands-on expertise and faster outcomes.

How does MDR enhance cybersecurity?

Managed detection and response (MDR) enhances cybersecurity by delivering a comprehensive, proactive approach to threat detection and incident response. MDR strengthens defenses by combining continuous 24/7 monitoring, expert threat hunting, integrated endpoint protection, advanced detection, and rapid automated response capabilities.

What types of industries benefit most from MDR services?

Security MDR services can benefit a wide array of industries, but are especially valuable for industries with strict compliance needs or sensitive data — such as financial services, healthcare, government, and critical infrastructure — where faster detection and response are critical.

The Cybersecurity Lifecycle: How Torq Automates Detection, Response, and Recovery

By Torq

September 5, 2025

7 Minute Read

What Is the Cybersecurity Lifecycle?

The cybersecurity lifecycle is the continuous process organizations follow to protect their digital assets, detect and respond to threats, and recover from incidents while improving defenses over time.

Most teams align it to five phases from NIST — identify, protect, detect, respond, and recover — run as an ongoing loop rather than a one-time checklist. The goal is resilience: understand what matters, harden it, spot threats fast, contain them, and restore normal operations while learning from every incident.

Because threats and environments change daily, the cybersecurity lifecycle is iterative: Metrics like MTTD/MTTR, tabletop exercises, red/purple-team findings, and audit results continuously refine each phase, tightening controls, improving detection logic, and streamlining response and recovery.

The 5 Stages of the Cybersecurity Lifecycle Explained

1. Identify: This stage is about visibility. Teams inventory assets, perform risk assessments, and uncover vulnerabilities. Without strong identification, blind spots remain — and attackers exploit what you don’t see.

2. Protect: Once risks are known, organizations deploy defenses: access control, encryption, segmentation, endpoint hardening, and security awareness training. The goal is to minimize the attack surface and prevent intrusions.

3. Detect: Here’s where SIEM, EDR, and XDR platforms generate alerts and identify suspicious activity. Effective detection relies on real-time monitoring, correlation, and threat intelligence to separate signal from noise.

4. Respond: After detection, SOCs must investigate, contain, and remediate incidents quickly. This includes triaging alerts, isolating systems, revoking access, blocking malicious domains, and notifying stakeholders.

5. Recover: The final stage focuses on resilience. Teams restore systems, minimize downtime, and feed lessons learned back into earlier phases — closing the loop for continuous improvement.

Challenges Modern SOCs Face at Each Cybersecurity Lifecycle Stage

Frameworks like NIST make the cybersecurity lifecycle look clean and sequential. But in practice, SOC teams know it rarely plays out that way. Each stage introduces friction — often because of disconnected tools, overworked analysts, and manual, error-prone workflows. Here’s where things break down.

Identification Challenge: Fragmented Asset Discovery

Most organizations rely on a patchwork of vulnerability scanners, CMDBs, and cloud-native tools to inventory assets. The result? Fragmented, incomplete visibility. Shadow IT, unmanaged endpoints, and ephemeral cloud resources slip through the cracks. Attackers thrive on these blind spots, while security teams spend valuable time reconciling spreadsheets rather than closing risks.

Protection Challenge: Uneven Policy Enforcement Across Environments

Policies don’t always travel well in hybrid environments. An IAM control enforced on AWS may not exist in Azure. Endpoint protection might be strong for corporate laptops, but nonexistent for contractors. This creates policy gaps that attackers can exploit while IT and security teams argue over ownership. Without automation, achieving consistent “Protect” controls is nearly impossible at scale.

Detection Challenge: Alert Fatigue from Noisy Systems

SIEMs, EDRs, XDRs, and threat intel feeds generate millions of alerts — but few are truly actionable. Analysts face alert fatigue, struggling to separate signal from noise. False positives clog queues, while real incidents get missed or delayed. Detection is no longer about generating alerts; it’s about enriching them with context and automating the next step — something traditional stacks rarely do.

Response Challenge: Manual, Slow, and Siloed

SOC bottlenecks become most painful during incident response. Analysts must manually triage, pivot across tools, request approvals, and loop in IT or DevOps teams. Every handoff adds hours (or days). Containment delays give attackers more dwell time, increasing breach impact. The gap between detection and remediation remains one of the SOC’s weakest links.

Recovery Challenge: Inconsistent and Poorly Documented

Recovery is supposed to restore operations and strengthen defenses. But in practice, it’s often inconsistent, rushed, and under-documented. Teams restore systems but fail to validate patches. Playbooks aren’t updated. Post-mortems rarely translate into better workflows. This leaves organizations vulnerable to repeat incidents — essentially relearning the same lessons after every breach.

How Hyperautomation Transforms the Cybersecurity Lifecycle

Traditional SOC operations often stop at dashboards, rules, and manual scripts — leaving analysts bogged down by repetitive work and inconsistent processes. Security Hyperautomation acts as the connective tissue across your entire security stack, orchestrating end-to-end action, eliminating bottlenecks, enriching data in real time, and triggering the right responses instantly.

With Torq Hyperautomation, every stage of the cybersecurity lifecycle becomes faster, more reliable, and easier to scale.

Identify with Context

Automated asset discovery and inventory: Torq integrates with CMDBs, vulnerability scanners, and cloud-native tools to maintain always-current visibility of assets and exposures.

Risk mapping: Assets are automatically tagged with ownership, business impact, and compliance requirements, giving context for prioritization.

Protect at Scale

Policy enforcement at scale: Torq continuously checks and enforces guardrails across IAM, cloud, and endpoint tools — ensuring least-privilege access, encryption, and network segmentation.

Configuration drift detection: Changes in cloud or endpoint configurations automatically trigger workflows to roll back or alert.

Detect Smarter

Real-time, enriched alerts: By connecting SIEM, EDR, and threat intelligence sources, Torq ensures every alert is automatically enriched with context (geo-IP, reputation, past incident history) before analysts ever see it.

Correlation at scale: Related events are automatically linked, reducing alert sprawl and helping analysts spot multi-stage attacks.

Respond Faster

No-code containment playbooks: Torq automatically executes safe but decisive actions like isolating compromised hosts, revoking tokens, resetting user accounts, or blocking malicious domains.

Risk-gated autonomy: Tier-1 threats are remediated fully autonomously, while higher-risk actions require one-click analyst approval — all with complete audit trails.

Recover and Improve

Closed-loop validation: Torq automatically triggers rescans and patch checks to confirm remediation is successful.

Compliance-ready reporting: Every workflow logs artifacts, timestamps, and outcomes, generating structured evidence for frameworks like SOC 2, NIST, HIPAA, and SEC guidelines.

Continuous improvement: Metrics like MTTR, suppression rate, and automation coverage are tracked to refine detection and response over time.

Example Scenario: Phishing Attack Detected in Microsoft 365

Identify: Torq ingests CMDB and Entra ID data, flagging the targeted finance user as high-risk due to elevated privileges.
Protect: Torq validates IAM and mailbox configurations, checking for risky changes like forwarding rules.
Detect: Defender flags a phishing email. Torq enriches the alert with Recorded Future, WHOIS, and VirusTotal intelligence to confirm the domain is malicious.
Respond: Torq quarantines the phishing email, revokes active sessions, resets the user’s password, isolates the endpoint, and alerts the SOC via Slack.
Recover: Torq triggers targeted rescans, validates remediation, and auto-generates a compliance-ready incident report with full timeline and audit trail.

Example Scenario: Impossible Travel Detection in Okta

Identify: Torq ingests identity data from Entra ID/Okta and builds user login baselines (geo, device, session history).
Protect: Torq enforces identity guardrails (MFA, conditional access) and flags high-value accounts for closer monitoring.
Detect: A new login event shows physically impossible travel. Torq enriches it with Defender telemetry and IP reputation data.
Respond: Torq challenges the user in real time. If denied or unverified, it forces a password reset, revokes sessions, isolates risky devices, and alerts the SOC.
Recover: Torq validates the remediation with rescans, updates the user’s login history, and generates a compliance-ready audit record.

The Future of the SOC: Hyperautomated Cybersecurity Lifecycles

Legacy approaches to the cybersecurity lifecycle break down under modern attack speed and scale. Hyperautomation gives SOCs the orchestration layer they’ve been missing — one that unifies tools, eliminates silos, and ensures every lifecycle phase flows seamlessly into the next.

With Torq, organizations can:

Accelerate MTTR by automating detection → response → recovery.
Reduce analyst burden by eliminating repetitive triage.
Continuously improve security posture through closed-loop remediation.
Scale effortlessly without adding headcount.

The future of the cybersecurity lifecycle is not more dashboards or rules — it’s an autonomous, adaptive loop that evolves as fast as attackers do.

Torq makes that future real today. See all the ways Torq makes the SOC more efficient for security teams.

Get the SOC Efficiency Guide

FAQs

What is lifecycle management in cybersecurity?

Lifecycle management is the continuous governance of the cybersecurity lifecycle — identify, protect, detect, respond, recover — run as an IT security lifecycle program and measured against a cybersecurity maturity model.

What are the 5 C's of cybersecurity?

The five C’s in cybersecurity are confidentiality, integrity, availability, compliance, and continuity. Teams use them to guide control selection and resilience decisions across the cybersecurity lifecycle.

What are the 5 stages of the cybersecurity lifecycle?

The five stages of the cybersecurity lifecycle are identify, protect, detect, respond, and recover. Organizations run this IT security lifecycle continuously and track progress with a cybersecurity maturity model.

What are the 4 phases of a cyber attack?

A cyber attack lifecycle includes reconnaissance, initial access/exploitation, lateral movement, privilege escalation, and actions on objectives. This sequence aligns with the cyber kill chain.

What are the 5 phases of the cyber kill chain?

In the five-phase cyber kill chain, attacks progress through reconnaissance, delivery/weaponization, exploitation, installation with command-and-control, and actions on objectives. Mapping detections and playbooks to these stages helps close gaps earlier.

Building an AI-Native Culture: How We Ran an AI Hackathon That Stuck

By Konstantin (Kostya) Ostrovsky

August 28, 2025

6 Minute Read

Konstantin (Kostya) Ostrovsky is the Chief Architect at Torq, where he leverages over 18 years of experience in software engineering and architecture. He specializes in cybersecurity, with a background that began with writing Windows Kernel Drivers. Konstantin is also a frequent speaker at software engineering conferences globally.

At Torq, our goal is to be at the cutting edge of technology — both in how we build our products and in how we work day to day. We adopted GitHub Copilot early, rolled out org-wide access to ChatGPT, Claude, and Cursor, and coached PMs and engineers on promptcraft, coding with copilots, and fast iteration.

However, simply providing AI tools or just talking about them isn’t enough. While they might seem intuitive at first, mastering the art of working with AI takes time and practice. It’s a process of learning the tricks and developing an intuition to get the most out of them.

To accelerate adoption, we ran a single-day AI Hackathon designed to turn curiosity into muscle memory — what we call “vibe-coding”: to rapidly and intuitively build cool, product-related features using AI.

How We Ran the AI Hackathon

We gave teams permission to “vibe-code” — move from idea to working prototype in hours — without the friction of day-to-day priorities. The goals were simple: use as much AI as possible, build something useful or delightful, and learn repeatable patterns you can bring back to your sprint.

Sourcing and Filtering Ideas

We opened the floor to everything — product features, internal back-office tools, developer experience (DX) improvements, or anything else our teams could dream up. In a week, we collected nearly 40 ideas. We sat down with our colleagues from the Product Management team, who helped us filter the list by half, prioritizing ideas that were both fun to work on and valuable to our product roadmap. The R&D team selected the remaining ideas focused on internal tooling, DX, and other engineering priorities.

Forming Teams

With the list narrowed to 20 projects, we asked our engineers to vote for the ones they’d most like to work on. They could choose any project that interested them, even outside their usual domain. We voted on a few favorites and assembled balanced squads of 3-4 people, intentionally mixing collaborators who don’t often pair.

To help with this, I even vibe-coded a small Hackathon organization app. It optimized team assignments to ensure most engineers were placed on a project they had either suggested or voted for.

Creating the Atmosphere

HR and Finance went all-in: banners, shirts, an endless supply of food and drink, and an afterparty to keep the energy high. In true Hackathon fashion, it was also a competition. A jury of four well-respected representatives from different Torq departments awarded prizes to the top three teams, and a “Crowd Favorite” was crowned from a company-wide vote.

The Hack Day

Energy was high across offices, including Warsaw, where one new engineer who joined Torq the day before was able to contribute significantly and even took second place.

Everyone worked extremely hard and had a ton of fun. I was tracking the token usage on our AI tools, and the activity screen in Cursor and the buzz in the office showed teams working as late as 3am. Interestingly, some of the most active AI tool users were our Product Managers and Team Leads, not just the engineers.

The Big Demo

The next morning, teams got five minutes each to give either a presentation, PoC, or live demo in our preview environment. Some were fully functional projects that were live in our preview environment. The teams’ achievements were mind-blowing. The sheer volume of work, business value, and innovative concepts presented was astonishing. Projects that would normally take weeks were demoed after just 24 hours of focused “vibe-coding.” These weren’t production-grade solutions, but they gave everyone a powerful glimpse of what’s possible when leveraging AI tools effectively.

After the winners were announced, I sent a survey to all participants. The results were unanimous: Everyone had a fantastic time and found the experience incredibly valuable.

How It Went

Start planning early. Looping in the Product team upfront gave us well-thought-out problem statements and tasks, so teams hit the ground running.

We crowdsourced the roadmap. We asked everyone to submit ideas and vote. Ownership increased and teams landed on projects they actually cared about.

Encourage experiments. We explicitly allowed people to try new tools and approaches. The creativity and velocity that followed was off the charts.

Show the score. Mid- and end-event stats (such as progress, token usage, and demos shipped) got everyone pumped up, sparked friendly competition, and kept momentum high.

Next time, we’ll be sure to balance scope across teams. We’ll pre-size projects with a simple complexity rubric and right-size them at kickoff so every team tackles a comparably challenging task.

Want to Run an AI Hackathon at Your Company?

Here’s some tips and best practices I’ve learned from launching this initiative at Torq:

Pick a single day.
Open the funnel for ideas and filter for impact.
Let people choose what they want to work on, then balance teams.
Remove friction (e.g., tools, data, environments).
Timebox. Demo. Celebrate.
Ship the best two or three ideas into a productionization lane.

The cost was minimal for tokens, swag, and food. The ROI showed up immediately: reusable code, better AI workflows, and teams that left with confidence, not just curiosity.

So, what’s the key to driving AI adoption? For us, it was turning conversation into action. Torq’s AI Hackathon provided tangible proof of what our teams could accomplish, transforming abstract potential into mind-blowing demos. It’s the ultimate accelerator, compressing weeks of learning and experimentation into a single, high-energy day.

The challenge is to carry that momentum forward, integrating these new vibe-coding workflows into our regular sprints. This is how a one-day event becomes the foundation for a long-term, AI-native culture.

Love the idea of vibe-coding, AI Hackathons, and building the future of security automation? We’re looking for engineers, PMs, and problem-solvers who want to push the boundaries of AI-native development. Check out Torq’s Careers page and join us in shaping the future of security.

See Job Openings

Automating MITRE ATT&CK Analysis with Torq Socrates

By Bob Boyle

August 26, 2025

8 Minute Read

MITRE ATT&CK has become the de facto SOC framework for classifying adversary behavior — and for good reason. It gives SOC teams a common language to describe threats, uncover gaps, and fine-tune detection logic. But let’s be honest: mapping real-world activity to ATT&CK tactics and techniques is still a time-consuming grind.

For analysts, this usually means bouncing between logs, enrichment sources, and documentation, trying to match cryptic telemetry to the right tactics, techniques, and procedures (TTPs). It’s slow, inconsistent, and vulnerable to human error. In high-volume environments, it just doesn’t scale.

MITRE ATT&CK has become a program in itself. But to use it daily across threat hunting, education, or red/blue teaming, you need automation. Torq Socrates, our agentic AI for autonomous investigation and triage, doesn’t just assist analysts. It acts on their behalf, analyzing cases in real time and automatically mapping findings to the MITRE ATT&CK framework with full context.

Manual MITRE ATT&CK Mapping

Here’s what traditional triage often looks like:

You receive an alert, maybe an endpoint flagged a suspicious PowerShell command.
You parse the logs, pull related observables, and try to reconstruct what happened.
You cross-reference those behaviors with MITRE’s matrix to find matching techniques.
You paste your findings into the case record, update the timeline, escalate if needed.

Even if you know the MITRE ATT&CK Framework like the back of your hand, this takes time, 30 to 60 minutes or more per case. That adds up fast. And worse, every analyst does it a little differently, leading to inconsistent documentation and uneven detection tuning downstream.

How Socrates Automates MITRE ATT&CK Analysis

The real challenge with MITRE ATT&CK isn’t understanding it — it’s operationalizing it at scale. SOC teams need to move from enrichment to action, and the only way to do that consistently is through automation.

That’s exactly what Torq Socrates delivers. By ingesting alert telemetry, mapping to tactics and techniques, and automating workflows, Socrates bridges the gap between ATT&CK theory and real-world impact, turning what was once a manual grind into a 30-second process. Users can extend or create their own MITRE-aligned workflows in minutes using Torq’s no-code/low-code environment.

Here’s how Socrates applies the MITRE ATT&CK framework in every case it touches:

Ingests case data: Socrates automatically parses alerts, logs, user inputs, and contextual artifacts from across your integrated toolchain.
Identifies patterns across incidents: Socrates compares TTP fingerprints over time, helping teams correlate seemingly unrelated cases or surface persistent attacker behaviors.
Summarizes behaviors: Using natural language processing (NLP), it identifies key actions and patterns (e.g., command execution, credential access, lateral movement).
Maps to ATT&CK: Socrates aligns those behaviors to tactics and techniques from the MITRE ATT&CK framework.
Annotates the case: It logs its reasoning, links evidence, and updates the timeline with MITRE-aligned insights.
Takes action: Based on policy, Socrates escalates, auto-remediates, or closes the case.

Torq Socrates operationalizes the MITRE ATT&CK framework end-to-end

Torq Workflow: Create MITRE ATT&CK Layer from TTP List

Socrates makes it easy to map TTPs to MITRE ATT&CK in every case automatically. But what if you want to go one step further, turning that mapping into a visual layer for deeper analysis or reporting?

This workflow takes any list of TTPs, whether generated by Socrates, entered manually, or ingested from another system, and automatically builds a shareable ATT&CK layer in both JSON and SVG formats. It’s especially useful for purple team exercises, threat hunting retrospectives, or briefing stakeholders with a visual snapshot of attack coverage.

Here’s what the workflow does:

Ingests a list of Tactics and Techniques from the triggering case.
Enriches input by expanding Tactics into associated Techniques using MITRE’s dataset (if Techniques aren’t provided directly).
Builds a unique list of all Techniques and Sub-techniques.
Generates two output formats: a JSON file for MITRE ATT&CK Navigator, and an SVG image for visualization.
Attaches the outputs directly to the case timeline for easy access and sharing.

The result is a fast, fully automated way to move from raw TTPs to a structured, visual MITRE layer. Just plug this workflow into any investigation where visual context helps drive decisions, and let Torq handle the rest.

Socrates vs. Manual Triage: A Side-by-Side Look

Consider a privilege escalation case triggered by suspicious endpoint behavior. A manual investigation typically takes 30-60 minutes, including log parsing, tactic identification, and evidence documentation.

With Socrates, the entire process is completed in approximately 30 seconds:

Detected behavior: Suspicious PowerShell execution via endpoint telemetry.
MITRE ATT&CK technique identified: T1059 – Command and Scripting Interpreter.
Evidence collected: PowerShell command logs with encoded payload execution, network activity to known malicious IPs.
Automated response recommendation: Endpoint isolation via integrated EDR, notification sent to IAM team for compromised credentials.
Outcome: Accelerated incident response, standardized classification, clear audit trails, and significantly reduced analyst workload.

Manual Approach:

Parse endpoint telemetry
Decode command strings
Match to MITRE techniques
Draft summary and tag case
Escalate and notify IR team
Time spent: ~45 minutes

Socrates Approach:

Auto-ingests alert + context
Detects suspicious use of net localgroup administrators
Maps to T1069.002 – Permission Groups Discovery: Domain Groups
Updates case, isolates host, triggers IAM sync
Time spent: ~30 seconds

Benefits of Automated MITRE ATT&CK Mapping

When Socrates handles MITRE mapping:

Threat classification is consistent across cases, shifts, and teams
Detection tuning improves because you’re measuring coverage by tactic and technique
Cross-case correlation gets easier, especially for threat hunting recurring attacker behavior
Audit and reporting get simpler with standardized documentation
Purple teaming and validation are enhanced by visual, real-time ATT&CK layer generation
Behavioral pattern recognition strengthens your defense posture, as Socrates identifies recurring techniques and stealthy attack strategies across historical cases, supporting more proactive threat hunting and detection refinement.
Visual MITRE ATT&CK heatmaps provide strategic insight, showing which techniques are detected, underutilized, or missed entirely. These insights directly support:
- Purple team planning and retrospective analysis
- Stakeholder and executive briefings
- SOC maturity assessments and coverage evaluations
- Detection engineering prioritization

SOCs that rely on MITRE but analyze it manually leave speed and quality on the table. Socrates gives you full fidelity, with none of the manual effort.

Beyond MITRE ATT&CK: Expanding the Impact of Socrates

Torq Socrates extends its automation beyond MITRE ATT&CK, providing:

Real-time threat enrichment: Socrates enriches every case with live intelligence from integrated sources like VirusTotal, WHOIS, and threat intel feeds, automatically attaching file reputation, IP context, domain history, and known indicators. Analysts gain instant clarity without needing to pivot across tools.

Auto-generated case summaries: Using natural language processing, Socrates produces concise, human-readable case summaries that distill the who, what, and how of each incident, accelerating analyst understanding and review. It’s like having a built-in security note-taker.

Policy-driven remediation: Whether isolating a compromised endpoint, resetting credentials, or disabling user access, Socrates follows automated remediation workflows tailored to your policies. Responses are swift, consistent, and fully auditable.

Seamless analyst handoff: Each case maintains complete context, timeline, and linked evidence, making it easy to escalate or reassign without losing momentum. Transitions between analysts — or even shifts — are frictionless and informed.

Comparing Traditional vs. Torq-Powered MITRE ATT&CK Operations

Capability	MITRE-Agnostic Approach	Torq-Enabled Implementation
Tagging Alerts & Cases	AI or rule-based tagging of detected activity	Torq HyperSOC auto-tags cases with relevant tactics, techniques and sub-techniques based on telemetry and case artifacts
Playbooks / Response	ATT-aligned automation workflows	Templates and playbooks auto-map TTPs, run responses, and visualize ATT layers in JSON/SVG
Continuous Validation	Ongoing technique simulation or control tests	Torq continuously processes detection signals in real-time, enforcing ATT‑aligned workflows per incident
Case Enrichment	Contextual enrichment of alert data	HyperSOC enriches cases with intel, process metadata, threat info, and correlates to prior incidents with same TTPs
Coverage Mapping	ATT matrix dashboards	Visual heatmaps showing TTP coverage across cloud and network based on past case tagging and incident mapping
AI / LLM-Powered Automation	NLP for enrichment and tagging	Torq’s LLM engine ingests guidance and framework documentation to enhance accuracy in triage, tagging, and team notifications
Customization	Scripted solutions	No-code/low-code builder to create custom ATT&CK workflows

Operationalize MITRE ATT&CK at Scale with Torq Socrates

MITRE ATT&CK mapping has long been a necessary but burdensome part of security operations. Torq Socrates changes that by fully automating the process, from parsing telemetry and identifying techniques to enriching cases, generating visual layers, and triggering policy-driven responses. It transforms MITRE from a static reference into a dynamic, real-time engine for smarter, faster, and more consistent security.

With Socrates, SOC teams no longer waste time on repetitive analysis or inconsistent tagging. They gain precision, speed, and visibility at scale, allowing them to focus on proactive defense, strategic initiatives, and continuous improvement.

MITRE ATT&CK doesn’t have to be a manual grind. With Torq Socrates, it becomes your SOC’s most powerful automation ally.

See Socrates in Action

Architecting a Production-Grade Anti-Phishing Defense System with the NVIDIA NeMo Agent Toolkit and NIM

By Konstantin (Kostya) Ostrovsky

August 26, 2025

11 Minute Read

Konstantin (Kostya) Ostrovsky is the Chief Architect at Torq, where he leverages over 18 years of experience in software engineering and architecture. He specializes in cybersecurity, with a background that began with writing Windows Kernel Drivers. Konstantin is also a frequent speaker at software engineering conferences globally.

Phishing attacks have evolved significantly in recent years, rendering traditional, rule-based defenses ineffective against sophisticated threats. Organizations now require dynamic, context-aware defenses that understand and adapt to complex threats in real time.

Torq has delivered a production-grade anti-phishing solution leveraging a multi-agent system built on NVIDIA’s advanced AI infrastructure and the NVIDIA NeMo Agent Toolkit open source library. This initiative provides enterprises with adaptive, scalable security designed to handle evolving cyber threats.

Why Torq Built on NVIDIA AI

Today’s phishing threats are engineered to bypass even the most sophisticated rule-based detection systems. They exploit context, urgency, and behavioral nuance in ways that traditional security architectures were never designed to handle.

Torq set out to solve this problem not with another static filter, but with a dynamic, production-grade product built on a multi-agent system that works like a modern SOC: distributed, specialized, and collaborative. To do that, we needed a framework built for a modular, efficient AI platform that could scale, adapt, and be trusted in real-time enterprise environments.

That’s why we’re collaborating with NVIDIA and built this system using their NeMo Agent Toolkit and NVIDIA NIM microservices.

The NeMo Agent Toolkit enables rapid development of complex, multi-agent workflows using intuitive YAML-based configuration, plug-and-play tool integration, and support for custom large language models. Through built-in profiling and telemetry, developers gain complete visibility into agent performance, latency, and cost, making it ideal for both development and production deployments.

The NeMo Agent Toolkit works side-by-side and around existing agentic frameworks, customer enterprise frameworks, and simple Python agents. It complements any existing agentic framework or memory tool you already use, allowing you to easily integrate your existing code base into the framework.

With NVIDIA NIM, we get high-performance, containerized inference endpoints for the latest AI models from NVIDIA and the community. It’s what lets us serve different LLMs for different tasks, optimize for latency and throughput, and swap in newer models as threats evolve.

Together, these technologies let us build an autonomous decision-making engine that’s explainable and built for production from day one.

Inside the Torq Phishing Defense Architecture with NVIDIA

The multi-agent phishing defense architecture comprises specialized AI agents working collaboratively. Each agent addresses specific aspects of email analysis, mirroring the workflows used by human security operations teams for comprehensive threat assessment.

The Torq Phishing Defense architecture with NVIDIA includes:

SecurityAnalystAgent: Acts as the system’s first touchpoint, ingesting raw email data and parsing it into headers, body content, and attachments. Based on the email’s contents, each element is routed to the appropriate specialist agent for deeper analysis, effectively kicking off the investigation workflow.
HeaderAnalysisAgent: Focused on the metadata and dissects email headers to detect spoofing or forgery. It verifies SPF, DKIM, and DMARC records, tracks anomalies in the mail relay path, and identifies mismatches between sender fields and the authentication records.
ExternalResourcesAgent: Hunts for malicious links, cross-referencing URLs against both external threat intelligence sources (like VirusTotal) and internal threat databases. Each URL is scanned and ranked by risk score. File attachments, both unprotected and password-protected, are also scanned using 3rd party vendors to detect malware. Often, phishing emails contain password-protected files with the password casually embedded in the email’s body. This is easily detected by a human, but requires a lot of engineering effort to extract and detect. Nowadays, thanks to LLMs, we can easily identify passwords and perform proper scanning on password-protected assets.
ScreenshotAnalyzerAgent: The email is rendered in a sandboxed environment, and then a screenshot is taken. We then use VLMs with image analysis support to identify any potential signs of a phishing email, such as broken logos, mixed font colors, and other indicators that a trained expert could only identify in the past. Nowadays, we can achieve that using out-of-the-box foundational models or models fine-tuned for phishing email data.
ContentClassifierAgent: Uses a LLM to analyze the email’s tone, urgency, and intent. It flags psychological manipulation cues (like fake deadlines or impersonation), often hidden from traditional filters.

Example prompt snippet:

# Social Engineering Tactics:

– Urgency and time pressure (“Act now!”, “Limited time!”, “Expires today!”)

– Authority impersonation (pretending to be from banks, government, IT support, executives)

– Fear-based manipulation (account suspension, security breach, legal action threats)

– Emotional appeals (charity scams, personal emergencies, romantic deception)

– Curiosity exploitation (mysterious packages, secret information, exclusive offers)

– Trust exploitation (fake testimonials, false credentials, friendship pretense)

# Content Analysis:

– Requests for sensitive information (passwords, SSN, account details, verification codes)

– Suspicious links or attachments mentioned in the text

– Generic greetings vs. personalized communication

– Grammar, spelling, and language inconsistencies

– Mismatched branding or logos mentioned

– Unusual payment methods (gift cards, cryptocurrency, wire transfers)

# Behavioral Indicators:

– Instructions to bypass security measures

– Requests to keep communication secret

– Pressure to act without verification

– Unusual communication channels suggested

– Requests to download software or click links

– Inconsistent sender identity or story

# Technical Red Flags:

– Shortened URLs or suspicious domain names mentioned

– Requests to disable security software

– Instructions to enable macros or run executables

– Phishing kit indicators (template text, placeholder content)

– URL analysis for typosquatting or suspicious domains

# Language Pattern Analysis:

– Inconsistent tone or writing style

– Translation artifacts suggesting non-native speakers

– Copy-paste indicators from legitimate sources

– Formatting anomalies or HTML artifacts

– Mixed font styles or encoding issues

VerdictAgent (The SOC Lead): Compiles all findings, weighs conflicting signals, and delivers a contextual risk score with a clear explanation. Acting as the decision-making layer, it mimics a senior analyst’s judgment to determine whether the email poses a threat. In addition to a verdict, it also provides the reasoning behind the decision and the investigation.

This sophisticated logic requires a powerful, reliable execution engine. The NVIDIA NeMo Agent Toolkit provides:

Framework-agnostic orchestration: Integrates existing Python libraries and agents seamlessly. Using it allows us to build multi-agent flows with ease.
YAML-driven workflows: Uses declarative YAML files for defining agent behaviors, workflows, and model configurations and prompts, simplifying deployments.
Built-in profiling and evaluation: Offers detailed telemetry to optimize latency, performance, and resource usage. This is extremely handy during the development phase. Using the profiling and evaluation data helps to select the right model for the job, either a cloud-hosted one provided by one of the vendors or a locally running one powered by the NVIDIA NIM containers.

Complementing the toolkit, NVIDIA NIM delivers high-performance, containerized inference endpoints for model flexibility. Using NIM containers allows easy, single-click model swaps without infrastructure complications.

Orchestration in Practice with config.yaml

At the center of this phishing defense system is a declarative NeMo Agent Toolkit configuration file that defines every component of the multi-agent architecture within a single YAML file. This makes the system highly extensible, developer-friendly, and production-ready.

The NVIDIA NeMo Agent Toolkit enables this orchestration by configuring each tool, model, prompt, and agent as composable, callable components. Here’s a conceptual breakdown of how it all comes together.

1. Tools and Agents Defined as Functions

The YAML configuration begins by defining individual tools: custom Python functions, API lookups, and Retrieval-Augmented Generation (RAG) pipelines. These are then mapped to specialized AI agents like HeaderAnalysisAgent and URLScannerAgent. Each agent uses a specific LLM and toolset to complete its role within the overall phishing analysis.

2. LLMs Powered by NVIDIA NIM

Two distinct LLMs are served via NVIDIA NIM containers: one for general reasoning and ReAct-style logic, and another fine-tuned for phishing content classification. With just a few lines of config, you can swap out or upgrade models.

3. VerdictAgent as the Final Judge

The workflow culminates in the VerdictAgent, implemented as an agent that reviews the results of the investigator agents to complete the analysis. It generates a verdict based on the assessment results generated by the investigative agents, summarizing their conclusions and calculating a risk score based on their findings.

Here’s what makes this approach powerful:

Modularity: Each agent is an independent component, making updates and testing seamless.
Flexibility: Swapping models, tuning prompts, and adding or removing tool logic are a matter of changing the agent’s configuration in the configuration YAML.
Explainability: The VerdictAgent aggregates signals from diverse sources, enabling human-readable reports and confidence scoring.

Spear-Phishing Detection in Action

By utilizing NVIDIA’s rich LLM ecosystem, Torq delivered a system uniquely capable of identifying high-risk spear-phishing campaigns targeting executives. These attacks typically include password-protected malware attachments with credentials shared in the email body. While traditional tools overlook this context, the AI agents in the system understand intent and behavior.

The results speak for themselves: LLM-based security systems dramatically outperform traditional rule-based engines, reducing incident response times from hours to under ten minutes for critical threats. These systems also demonstrate superior resilience against AI-generated phishing attacks, maintaining accuracy even when sophisticated rephrasing techniques are employed — showing only a 3-4 percentage point decline compared to 5-9 points for traditional models.

Perhaps most importantly, intelligent event correlation tackles alert fatigue head-on, reducing alert volume by up to 87% while ensuring security teams can focus on genuine threats rather than managing false positives.

Real-World Impact

Leveraging Python as a unifying language, the NeMo Agent Toolkit for rapid development, Torq was able to build an agentic AI-based phishing email detection feature quickly. This effectively addresses advanced phishing tactics, including password-protected malware attachments. It understands the nuanced context within phishing emails, resulting in:

Accelerated incident response: Agents collaboratively analyze threats, drastically reducing the mean time to respond (MTTR) up to 92% faster compared to manual investigation.
Fewer false positives: Context-aware agents ensure precise detection, minimizing alert fatigue.
Stronger threat correlation: Agents correlate seemingly unrelated phishing attempts, uncovering hidden threat patterns and bolstering overall security posture.
7-15x More Effective at Catching Missed Phishing Emails: Our initial testing shows that our product is able to detect a significant number of malicious emails that have already been scanned and deemed “safe” by traditional gateways like those in Microsoft 365 or Google Workspace.

Building AI Security That Learns and Scales

Phishing threats continue to evolve, demanding smarter, adaptive solutions. The collaboration between NVIDIA and Torq shows how multi-agent AI systems can redefine phishing defense.

Customers can plug our advanced phishing detection feature directly into their Torq workflows; it is available as a Step in their Builder’s Toolbox. This feature enables real-time analysis of emails, attachments, URLs, and headers using multiple specialized AI agents, delivering highly accurate threat detection without manual tuning. By embedding this capability into automated workflows, security teams can rapidly identify and mitigate phishing attempts while continuously adapting to new threat patterns.

See how AI-driven security operations transform detection, response, and scale across your entire environment.

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AI SOC Market Landscape 2025: Torq Leads With Hyperautomation

By Dallas Young

August 25, 2025

5 Minute Read

Other Vendors Build Features. Torq Builds the Foundation.

According to Francis Odum and Rafal Kitab from Software Analyst Cyber Research’s survey of 300+ CISOs:

Enterprises are battling over 3,000 alerts per day, across 28+ tools
40% of alerts go uninvestigated
61% of teams have ignored alerts that turned out to be critical
The average investigation time is 70 minutes
Meanwhile, phishing breaches succeed in under 60 minutes

The takeaway is that you don’t need another AI assistant. You need a system that executes. The winners in the AI SOC space won’t be the ones with the flashiest chat UI — they’ll be the ones that reduce MTTR, scale across fragmented environments, and adapt faster than threats evolve.

That’s Torq.

AI is Only as Useful as Where It Lives

Francis Odum and his team break the AI SOC market into several architectural approaches: black-box overlays, workflow emulators, and Integrated AI SOC Platforms. Only a handful of vendors made that top-tier designation. Torq is one of them.

Here’s what that means in practice:

Agentic AI works inside your environment. It uses hundreds of APIs, headless modes, and Slack/Teams interactions to collect context and execute actions.
The platform is horizontally scalable, with active monitoring by engineering for peak load performance.
Time to full operation is measured in weeks.
- Day 1–3: Core setup and integrations
- Day 4–7: Early automation with templates
- Weeks 2–3: Advanced workflows and AI agent deployment
- Weeks 3–4: Full operational status

Why does that matter? Because AI on the outside can only suggest. AI on the inside can act. Agentic AI has massive potential, but it’s only as powerful as the system it operates in.

Most Vendors Promise Outcomes. Torq Delivers Infrastructure.

The AI SOC space is crowded. As the SACR report points out, most vendors are chasing the same three problems: alert triage, investigation acceleration, and co-pilot-style assistance. These are necessary, but not enough.

Unlike black-box platforms, Torq provides full visibility and control over every AI-driven decision.

1. AI decisions are explainable.

AI decisions are explained with the what, when, impact, key indicators, and next steps.

2. Human feedback is instantly integrated.

Human feedback or instructions written in natural language is instantly integrated.

3. Automation logic is entirely customizable via a visual no-code editor.

In the report, Francis Odum stated that Torq “exceeds expectations for features that AI SOC platforms typically bring.” That’s because we’re not just building features; we are the central nervous system of your security operations, designed to:

Consolidate fragmented workflows across identity, cloud, endpoint, and email
Trigger and scale real-time responses
Integrate agentic decision-making into every step
Operate in hybrid, cloud, and air-gapped environments

As Odum and Kitab note, integrated platforms like Torq are the only architecture that delivers both control and execution at scale.

Enterprise-Grade Infrastructure That Goes Beyond Detection and Response

The SACR report evaluated vendors across operational metrics that matter: investigation speed, alert validation, explainability, contextual enrichment, and performance at scale. Torq stood out because we’re operationally mature and built for enterprise SOCs and MSSPs.

Odum and Kitab’s deep dive surfaced more of Torq’s infrastructure-level advantages, including:

300+ out-of-the-box integrations
Hybrid, on-prem, and air-gapped deployment options
Support for BYOC (Bring Your Own Container)
Log storage, threat hunting, and artifact analysis baked in
Multi-tenancy, full governance, and deletion controls for MSSP and enterprise use
Support for all major compliance frameworks

Not Another Tool — A True Operating Layer

When the report highlighted Torq’s “broad capabilities” in the market, they weren’t just referring to feature count. They were pointing to depth — to a platform that can power CSPM, IAM, threat hunting, email security, incident response, and more, from a single, configurable foundation.

Modern SOCs aren’t one-size-fits-all. Whether you’re running an internal team or an MSSP serving 50 clients, you need a platform that:

Operates autonomously, not in isolation
Handles governance, not just generative reasoning
Executes decisions, not just recommends them

Torq’s Brittney Zec sits down with Francis Odum to get the low down on the SACR 2025 report.

Choose the Platform That Makes AI Work

There’s a lot of noise in this market. Most vendors are in the early innings — or worse, locked in pre-packaged black boxes that leave you with no customization, transparency, or control.

Torq’s take is simple: AI isn’t the product. AI is the engine. The product is the system that runs it. So if you’re still comparing AI SOC tools by which one has the slickest co-pilot or the prettiest chat interface, you’re playing the wrong game.

An autonomous SOC requires three key components: Hyperautomation, SOC-specific AI agents, and enterprise-grade security architecture.

You should be asking:

Does this platform give me executional control?
Can I modify logic and workflows without code?
Is the AI embedded — or sitting on the sidelines?
Can it handle my real-world scale, load, and compliance needs?
Can I trust what it does — and see how it got there?

If the answer isn’t “yes” across the board, it’s not built for where SOCs are headed.

Torq is. And now, thanks to SACR’s 2025 report, the industry knows it too.

Build the execution-first SOC the SACR report points to: transparent, scalable, and enterprise-ready. Read our Don’t Die, Get Torq Manifesto to learn more.

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Top Vulnerability Management Tools and How Torq Automates Remediation

By Torq

August 22, 2025

8 Minute Read

What Are Vulnerability Management Tools?

Vulnerability Management Tools

Vulnerability management tools are software solutions designed to identify, assess, and report security weaknesses in networks, systems, applications, and cloud environments.

The vulnerability management lifecycle generally includes:

Discovery: Finding assets and identifying vulnerabilities.
Assessment: Scoring and analyzing the risk of those vulnerabilities.
Prioritization: Determining which issues to fix first based on severity and business impact.
Remediation: Applying patches, configuration changes, or mitigations.
Verification: Confirming the vulnerability is resolved.
Reporting: Measuring performance to refine processes and increase efficiency.

The challenge? Even with great tools, scale, speed, and complexity make it hard to move from vulnerability identification to closure — especially without automation.

How Torq Automates Vulnerability Management

Most vulnerability management platforms excel at finding problems — but not at fixing them quickly. The result is a growing backlog of unresolved issues, missed SLAs, and heightened risk exposure. Torq delivers end-to-end, autonomous vulnerability remediation that not only identifies and prioritizes vulnerabilities but also orchestrates their resolution and verification at scale.

Built on Torq’s Hyperautomation platform, this approach connects every tool in your remediation chain — scanners, patching platforms, configuration managers, ITSM systems, and communications channels — into one coordinated, closed-loop workflow.

Automating Vulnerability Prioritization & Alert Enrichment

Raw scan results are noisy, and without context, it’s impossible to know which vulnerabilities truly matter. Torq automates this step by ingesting alerts from your vulnerability scanners (Qualys, Tenable, Rapid7, etc.) and enriching them in real time with:

Asset criticality from configuration management databases (CMDBs) and asset inventories to understand business impact.
Threat intelligence to flag vulnerabilities under active exploitation in the wild.
Business context such as asset owner, operating environment, and compliance relevance (e.g., PCI, HIPAA, SOC 2).

The outcome is dynamic, risk-based prioritization, ensuring that vulnerabilities with the highest likelihood and impact of exploitation automatically rise to the top of the remediation queue.

Orchestrating Remediation Workflows Across Teams

Finding vulnerabilities is one thing; getting them to the right people for remediation is another. Torq removes this bottleneck by:

Automatically routing tasks to the correct team: IT for endpoint patches, DevOps for container images, SecOps for misconfigurations.
Opening and tracking tickets in IT service management (ITSM) tools like ServiceNow, Jira, or Freshservice with full vulnerability details already included.
Triggering patch or config changes via SCCM, Ansible, Tanium, AWS Systems Manager, or other patching/configuration tools.
Notifying stakeholders in real time through Slack, Microsoft Teams, or email to keep everyone aligned.

This means no more manual handoffs, missed assignments, or confusion over ownership; remediation is assigned instantly and tracked from start to finish.

Continuous Verification & Closed-Loop Remediation

Vulnerability remediation doesn’t end when a patch is pushed — it ends when the fix is verified. Torq ensures that no remediation task is left incomplete by automatically:

Initiating a targeted rescan of the affected asset after remediation is applied.
Validating resolution against the original finding, ensuring that the vulnerability no longer exists.
Updating records across systems — closing tickets in ITSM, marking the issue resolved in your SIEM/XDR, and updating compliance dashboards.

With this closed-loop process, there are no lingering “open” vulnerabilities that have been patched but not verified, dramatically improving SLA adherence and compliance posture.

Building a Proactive, Scalable Vulnerability Management Program with Torq

Traditional vulnerability management is reactive — scan, report, repeat — leaving organizations chasing an ever-growing backlog of issues. Torq transforms this approach into a proactive, continuous, and scalable program that not only finds vulnerabilities faster but also remediates and verifies them without manual intervention.

Accelerating MTTR and Reducing Risk at Scale

Speed matters when it comes to vulnerabilities. Every hour a critical common vulnerability or exposure (CVE) remains unpatched increases the window of opportunity for attackers. Torq compresses mean time to remediation (MTTR) from weeks or days to hours or even minutes by:

Automating triage so the highest-risk vulnerabilities are prioritized instantly.
Orchestrating remediation directly across patch management, configuration tools, and ITSM systems.
Initiating real-time verification scans to confirm that vulnerabilities are truly fixed before closing them out.

The result is shorter exposure windows and a stronger overall security posture, all without adding headcount or burdening existing teams.

Empowering Security Teams with Autonomous Vulnerability Management

Vulnerability Management teams often spend the bulk of their time on repetitive, manual processes — parsing scan results, creating tickets, and chasing owners for fixes. Torq’s autonomous vulnerability management workflows eliminate these bottlenecks, allowing:

Analysts to focus on threat hunting, incident investigation, and security architecture improvements.
Engineers to spend more time on proactive hardening and less on reactive firefighting.
Leaders to gain real-time visibility into remediation progress and SLA compliance without chasing updates.

Why Hyperautomation is the Future of Vulnerability Management

Torq’s approach combines flexibility, scale, and intelligence into one unified platform:

No-code Security Hyperautomation for rapid deployment, allowing you to quickly build and adapt workflows without relying on development teams.
Frictionless architecture for integration with your existing scanners, patching systems, ITSM platforms, and security tools.
Cross-tool orchestration that unifies every stage of the vulnerability lifecycle — from detection to -remediation to verification — across all environments.
Real-time enforcement that triggers auto-remediation the moment a vulnerability is detected, not days later.
Enterprise-grade scalability capable of handling millions of assets and findings across global, hybrid, and cloud-native infrastructures.

With Torq, vulnerability management shifts from a reactive, report-driven process to a continuous, autonomous security function — one that reduces risk, enforces compliance, and scales effortlessly with your environment.

Vulnerability Management Tool Categories

Vulnerability Scanning and Assessment Tools

Function: These tools are the foundation of any vulnerability management program. They scan systems, networks, applications, and cloud environments to identify known vulnerabilities, misconfigurations, and outdated software. Many also integrate with compliance frameworks to flag violations against standards like PCI-DSS, HIPAA, or CIS benchmarks.

Examples: Tenable Nessus, Qualys, Rapid7 InsightVM, OpenVAS

Strength: Provide broad and deep coverage, identifying vulnerabilities across thousands of assets at scale. They can run scheduled scans, agent-based assessments, and on-demand checks, ensuring visibility into the evolving attack surface.

Weakness: While they excel at discovery, most scanners simply export reports or feed results into dashboards. Without automated triage, these findings often overwhelm security teams, creating large backlogs and slow MTTR.

Software Composition Analysis (SCA) and Application Security Testing (AST) Tools

Function: Focused on the application layer, these tools identify vulnerabilities in source code, open-source libraries, third-party components, and APIs. They help developers and DevSecOps teams catch issues early in the software development lifecycle (SDLC) before they reach production.

Examples: Snyk, Checkmarx, Veracode, SonarQube

Strength: Critical for securing the software supply chain. They integrate into CI/CD pipelines, IDEs, and code repositories to ensure vulnerabilities are addressed during build time, not after deployment.

Weakness: The outputs from SCA and AST tools often remain isolated from broader security operations. If findings aren’t funneled into unified remediation workflows, they can be lost in ticket queues or delayed until the next release cycle.

Vulnerability Intelligence and Prioritization Platforms

Function: These platforms sit on top of scanner outputs, enriching raw vulnerability data with threat intelligence, exploitability context, and asset value. The goal is to move beyond “fix everything” lists and instead direct remediation efforts toward vulnerabilities most likely to be exploited in your environment.

Examples: Kenna Security (Cisco), VulnCheck, ThreatConnect

Strength: Prioritization platforms help teams make smart trade-offs, especially in large organizations with limited patching resources. They can correlate vulnerabilities with known exploits in the wild and align remediation with business-critical assets.

Weakness: While prioritization is a huge time-saver, it doesn’t actually close the loop. Many organizations still need separate workflows and manual coordination to assign, track, and validate fixes — leading to delays in actual remediation.

Patch and Configuration Management Tools

Function: These tools take action on vulnerabilities by deploying operating system and software patches, updating firmware, or enforcing secure configuration baselines. They’re essential for ensuring that identified weaknesses are quickly and consistently addressed.

Examples: Microsoft SCCM, Tanium, Ansible, Puppet

Strength: Directly resolves vulnerabilities by updating systems or locking down insecure settings. Many also support automation, allowing patches to be deployed across thousands of endpoints with minimal downtime.

Weakness: Without direct integration into vulnerability scanning and prioritization tools, patching efforts can become reactive or incomplete. IT teams may focus on routine updates instead of targeting the most critical vulnerabilities first, leaving high-risk exposures unpatched for weeks or months.

From Findings to Fixes — Automatically

The best vulnerability management tools surface what’s wrong; Torq makes it right. By orchestrating scanners, ITSM, patching/configuration platforms, and verification in a single, no-code workflow, Torq turns noisy findings into prioritized, automated remediation with audit-ready proof. The result is shorter MTTR, smaller attack surface, and fewer backlogs, all without adding headcount.

Ready to close the loop on vulnerability management? Get our Don’t Die, Get Torq manifesto to see how to turn vulnerability intelligence into instant resolution.

Get the Manifesto

You’re Just 90 Days Away From a Modern SOC

By Torq

August 21, 2025

6 Minute Read

What is a Modern SOC?

A modern SOC or next-gen SOC (Security Operations Center) is fast, flexible, and autonomous. It doesn’t rely on analysts manually chasing every alert or stitching together siloed tools. Instead, it blends:

AI-powered decision making
Real-time, automated triage and response
Integrated, end-to-end case management
No-code workflows anyone on the team can build

A modern SOC is scalable, sustainable, and proactive. And with Torq, it’s only 90 days away.

30 Days: Build the Foundation

During the first month, your primary focus will be laying the groundwork for SOC transformation. A dedicated Torq team, including a Customer Success Manager (CSM), Solutions Architect (SA), and Professional Services (PS) specialist, will collaborate closely with your team to establish the technical foundation.

You’ll begin by defining success criteria, aligning key stakeholders, configuring SSO, provisioning access, and prioritizing critical workflows such as phishing triage, endpoint detection and response (EDR), and cloud security alerts.

By the end of this initial phase, you’ll have launched your first production-ready automations, significantly reducing analyst workloads. Your team will also learn to navigate the Torq platform, interpret errors, and debug workflows. Integration with essential tools, including Slack, Jira, AWS, and Okta, will ensure a streamlined experience, enabling immediate operational efficiency and stakeholder alignment.

Key Outcomes:

Tier-1 analyst workload begins to decline
First automations deployed and delivering value
Platform familiarity achieved across the builder team
Stakeholder alignment on 90-day roadmap

60 Days: Optimize Processes and Introduce Socrates

In the second month, your automation initiatives will expand to cover advanced cybersecurity use cases, including identity and access management (IAM), threat intelligence enrichment, and monitoring suspicious user behaviors.

You’ll be introduced to Socrates, Torq’s AI-driven SOC Analyst, which orchestrates our team of AI Agents to manage Tier-1 alert triage and case enrichment autonomously. Socrates will help your team reduce noise and false positives by intelligently prioritizing alerts based on severity and context.

Throughout this period, your team will receive targeted training on modular workflow design, advanced automation logic, and effective case management practices. This training empowers your analysts to build, refine, and optimize automation workflows independently. By the end of the month, your SOC will experience faster response times, improved analyst productivity, and significantly reduced alert fatigue.

Key Outcomes:

Builder teams creating and optimizing workflows independently
Alert fatigue reduced through smarter case thresholds
Performance benchmarks established per use case
Socrates contributes measurable value in daily operations

90 Days: Achieve Full SOC Autonomy

By the third month, your SOC will transition fully into a proactive, autonomous model powered by Socrates, which will manage incident lifecycles from initial detection and triage through resolution and documentation. Analysts will shift away from manual, repetitive tasks to strategic oversight, focusing exclusively on high-priority incidents and deeper threat investigations. Performance metrics like MTTD and MTTR will be clearly defined and measurable.

As this transformative phase concludes, your team will finalize Standard Operating Procedures (SOPs), ensuring scalability, sustainability, and continuous improvement within your SOC. We’ll work with you to present a detailed QBR that highlights your measurable achievements and clear ROI to executive stakeholders.

Ultimately, you’ll reach an operational state where 100% of Tier-1 alerts are autonomously handled, significantly enhancing your SOC’s agility, efficiency, and overall security posture.

Key Outcomes:

Up to 100% of Tier-1 alerts fully automated from triage to resolution
Strategic shift in analyst focus — from reaction to oversight
Clear ROI and automation impact communicated to exec stakeholders
Platform maturity with roadmap alignment

With Torq’s AI-powered Hyperautomated workflows, end-to-end case management, and real-time triage and response — any organization can achieve the promise of full SOC autonomy. This 90 day roadmap serves as a baseline, while Torq’s dedicated team of engineers, architects, and customer success managers work with you to build out a customized deployment strategy that fit your goals, environment and needs.

And if 90 days is too long, that’s fine too — just ask Carvana: “Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts and has automated 41 different runbooks within just one month of deployment.”

See how more of Torq customers hit full autonomy in 90 days — or less.

Why Torq is Built for the Modern SOC

Multi-agent system: Torq’s multi-agent system performs autonomous triage, in-depth data enrichment, and automated logging and documentation, accelerating your security operations.

Low-code/no-code Hyperautomation: Torq’s intuitive, drag-and-drop and AI-powered automation builder with visual debugging enables quick, error-free workflow creation accessible to all skill levels.

Immediate integrations: Access 300+ pre-built integrations with security solutions (including SIEM, EDR, threat intelligence feeds, and IAM) that seamlessly connect your existing tech stack, ensuring instant operational value.

Comprehensive customer enablement: Dedicated, hands-on support teams provide guided enablement, weekly sessions, and strategic quarterly reviews tailored to your organization’s specific needs.

7 Core Capabilities of a Modern SOC — Solved by Torq

1. Threat Intelligence

A modern SOC is predictive, identifying threats before they strike by leveraging threat hunting, IOC correlation, and TTP analysis.

Torq automates threat hunting and threat intelligence enrichment across your SIEM, EDR, and threat intelligence platforms, surfacing actionable indicators and accelerating response across every workflow.

2. Continuous Monitoring

A true modern SOC operates 24/7/365, monitoring everything from cloud infrastructure to user behavior.

Torq seamlessly ingests signals across your entire attack surface and ensures nonstop alert intake, correlation, and escalation — without analyst burnout.

3. Proactive Cyber Threat Detection

Modern adversaries hide in plain sight, which is why your SOC must correlate signals across every tool.

Torq’s agentic AI and multi-tool integration capabilities enable proactive detection and response across SIEM, EDR, cloud, IAM, and beyond.

4. Incident Response Automation

Speed is everything in security operations — the longer an incident lingers, the more it costs.

Torq automates every phase of incident response — from alert triage to remediation — with AI Agents like Socrates executing workflows in seconds.

5. Post-Incident Review

Recovery from a breach isn’t enough — your SOC needs to learn, improve, and harden.

Torq automatically documents the full case lifecycle and feeds metrics into structured post-incident reviews, so your SOC evolves with every alert.

6. Reporting and Compliance

Today’s security operations center must deliver visibility and meet compliance requirements without manual effort.

Torq captures real-time data across all workflows and playbooks, outputs audit-ready logs, and maps metrics to standards like NIST, GDPR, and HIPAA.

7. Automation and Orchestration

Automation isn’t optional anymore — it’s how modern SOCs scale.

Torq’s drag-and-drop builder, 250+ integrations, and modular design let your team orchestrate workflows and auto-remediation without writing a single line of code.

Ready to Start Your SOC Autonomy Journey?

Torq is the only platform that can deliver a modern, fully autonomous SOC in just 90 days — and back it with expert support every step of the way.

Get the 90-Day Roadmap

Life in the SOC Sucks. Here’s How HyperSOC Can Save Us

By Patrick “PO” Orzechowski

August 19, 2025

7 Minute Read

Patrick Orzechowski (also known as “PO”) is Torq’s Field CISO, bringing his years of experience and expertise as a SOC leader to our customers. PO is a seasoned security veteran with a deep understanding of the modern security landscape. You can find him talking to SOC leaders and CISOs from major brands at cybersecurity events around the world.

You know the scene. The low hum of the servers in the server room, the cold glow of the SIEM dashboards on a wall screen, and a flood of alerts that never ends. For security teams, the promise of being on the frontlines of digital defense often crumbles into a daily grind of alerts, tickets, and long shifts that leave even the best analysts exhausted. If you’ve ever felt like the job is more about being a cog in a perpetual motion machine than hunting actual threats — you’re not alone.

The good news? Security automation isn’t here to replace analysts. It’s here to make the job worth doing again by taking on the tedious work that burns people out and slows SOCs down.

Below are some of the most common pains in the SOC, and how Torq HyperSOC ™ can make a real difference thanks to advanced case management, Hyperautomated workflows, and a collaborative AI SOC Analyst.

The Seven Levels of SOC Hell (and How to Escape)

“In my opinion, working at a SOC was either a joke or absolute hell with little in between.”

– SOC analyst on Reddit

1. The Eternal Fires of False Positives

The Pain: A recent survey found that nearly 60% of SOC leaders and practitioners simply have too many alerts. You’re forced to chase ghosts — an IoT device beaconing to a Russian IP, a routine software update flagged as a command-and-control server. The system is designed to generate noise, and you’re the human filter.

The Torq HyperSOC Fix:

Automated enrichment adds context to alerts before they ever hit your queue, shutting down the noise at its source.
Automated scoring and filtering ensure you only see what really matters.
Known false positives are closed automatically.

The Result: The ghost alert from the IoT device is auto-closed with a ‘known benign’ tag, a silent monument to a waste of time that never happened. Your existence is no longer defined by chasing shadows — instead, your time is spent investigating and remediating real, critical alerts that arrive in front of you with enrichment and context baked in.

2. Shift Handoffs: The Art of Getting Screwed at 6:59 am

The Pain: Ah, the shift handoff — always leaves you spending more time piecing things together than moving cases ahead. The previous analyst leaves a few vague notes, a trail of breadcrumbs leading to nowhere, and you’re left to figure out where to go next with the incomplete investigation you just inherited. The system rewards individual survival, not collective success.

The Torq HyperSOC Fix:

AI-generated case summaries capture every step of the investigation.
Automated playbooks enforce consistency across shifts.
Socrates, the AI SOC Analyst, provides a clear, factual summary of the overnight events, stripped of human error or forgetfulness, ensuring consistency in perpetuity.

The Result: You arrive at your terminal to an AI-generated summary of every event that clearly shows where every investigation stands and every action taken, so you can get up to speed fast. It’s like having a personal scribe who never sleeps and never forgets.

3. Customer Interactions: Between a Rock and a Clueless Place

The Pain: You are the frontline dealing with customers who don’t know their own networks. You may be the final authority, but you’re forced to babysit interactions with customers who clog up the queue by opening priority one (P1) tickets for their own phishing tests.

The Torq HyperSOC Fix:

AI chatbots act as a faceless, tireless Tier-1 interface, deflecting the mundane back-and-forth.
Context-aware automation automatically suppresses and closes known test alerts, silencing the false alarms before they ever reach your queue and ensuring that your only interaction is with real threats.

The Result: The system identifies a simulated phishing attack and closes the ticket without you ever seeing it. The only time you’re involved is when a confirmed critical issue requires your attention.

4. Alerts Have Names, You Don’t

“Alert fatigue is killing us. We get hundreds of alerts daily and 90% are false positives… The worst part is the one time you ignore an alert, thinking “probably another false positive,” ends up being the real deal. Meanwhile, management keeps asking why we’re not investigating every single alert faster. Like yeah, let me just clone myself real quick.”

– SOC analyst on Reddit

The Pain: You feel like a cog in the machine. Your victories are anonymous, your failures are public, and you feel like you’re always one missed alert away from catastrophe. The system tracks tickets, but it doesn’t track you.

The Torq HyperSOC Fix:

Intelligent dashboards track analyst contributions, making your value visible to leadership.
Generative AI summarizes major incidents and assigns credit, giving you a name for your actions.
Efficiency and accuracy get measured, proving your worth beyond a simple ticket count.

The Result: You crack a complex credential stuffing campaign and, instead of a generic resolution, the AI-generated incident report lists your exact actions. You finally get credit for the work they do — and managers see the value you bring.

5. Death by Ticketing System

The Pain: The ticketing system can feel like a labyrinth designed to slow you down, a complex flow of queues and reassignments that delays real action. You’re trapped in a digital bureaucracy.

The Torq HyperSOC Fix:

Seamless integrations between your ticketing system and detection tools automates the flow of tickets and information.
Tickets are routed efficiently and instantly to the right queue.
AI summarization condenses log evidence into clean notes, eliminating the need for manual record-keeping.

The Result: A misclassified ticket that once took 45 minutes to reassign is now routed in 4 seconds. The system now serves you.

6. Burnout Is a Feature, Not a Bug

The Pain: The constant pressure, the endless stream of alerts, the cognitive fatigue of sorting the signal from the ocean of noise. The system isn’t just prone to burnout — it makes it practically inevitable.

The Torq HyperSOC Fix:

AI-driven triage drastically reduces the number of low-value alerts you have to touch.
Socrates handles 90% of Tier-1 grunt work and auto-remediates 9% of Tier-1 cases — freeing you for more interesting, creative security work.

The Result: A colleague, on the verge of breaking under alert fatigue, now has a system that filters out the low-value noise. Theis gives them breathing room and the bandwidth for engaging, higher-value investigations.

7. So Why Stay? (Or Why You Left)

The Pain: Over half of SOC analysts say stress on the job has made them consider walking away. The promise of a rewarding career became a reality of data overwhelm and endlessly copy-pasting data between windows — and they chose freedom.

The Torq HyperSOC Fix:

Automation doesn’t replace analysts; it removes the parts of the job that made it unbearable.
Automation gives you time to focus on genuine threats and your own career development.
AI empowers you to focus on high-level risk, not the mundane, repetitive tasks.

The Result: You almost left last year, but after Torq HyperSOC was implemented, you now have time to lead threat-hunting sessions. You’re still here — but now you’re a threat hunter, not a human alert filter.

Don’t Die: Get the Manifesto

The SOC grind is real. But there is a way to survive — by using Torq’s AI-driven HyperSOC to regain control. Let’s stop talking about alert fatigue and start redesigning the SOC to be more sustainable and, dare we say, human.

Find out how Torq HyperSOC combats the three core areas of unsustainable pressure in SOCs — across your people, your strategy, and your business impact.

Get the Don't Die manifesto to learn how HyperSOC solves SOC analyst challenges and pain points

Get the Manifesto

Contents

The 90-Day Path to SOC Autonomy

30 Days: Kickoff, Connect, and Ship Quick Wins

60 Days: Scale Coverage, Standardize, and Measure

90 Days: Autonomous with Humans on the Loop

What to Measure in the First 90 Days of Your AI SOC

90-Day Autonomous SOC Wins From Torq Customers

Valvoline: Saving Analysts 6–7 Hours a Day

Global Health and Wellness Company: Proving SOC Value with Data in 60 Days

HWG Sababa: Doubles SOC Output Without Adding Headcount

Global Online Money Transfer Platform: Cuts Alert Handling Time by 30%

Why Customers Ramp Up Fast with Torq HyperSOC

Get Your SOC Autonomous in 90 Days

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What is MDR and Why It Matters for Enterprises

MDR Services and Solutions Enhanced by Hyperautomation

Increasing Efficiency and Margin with MDR Security Automation

MDR Cybersecurity: Faster Onboarding and Scalable Operations

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What Is the Cybersecurity Lifecycle?

The 5 Stages of the Cybersecurity Lifecycle Explained

Challenges Modern SOCs Face at Each Cybersecurity Lifecycle Stage

Identification Challenge: Fragmented Asset Discovery

Protection Challenge: Uneven Policy Enforcement Across Environments

Detection Challenge: Alert Fatigue from Noisy Systems

Response Challenge: Manual, Slow, and Siloed

Recovery Challenge: Inconsistent and Poorly Documented

How Hyperautomation Transforms the Cybersecurity Lifecycle

Identify with Context

Protect at Scale

Detect Smarter

Respond Faster

Recover and Improve

Example Scenario: Phishing Attack Detected in Microsoft 365

Example Scenario: Impossible Travel Detection in Okta

The Future of the SOC: Hyperautomated Cybersecurity Lifecycles

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