Hyperautomation Product

Torq + SSDLC: Where Secure Automation Begins

By Torq

July 24, 2025

5 Minute Read

The Evolution from SDLC to SSDLC

Every software application, from mobile apps to intricate enterprise solutions, follows a structured development process called the Software Development Lifecycle (SDLC). SDLC provides a systematic approach, covering requirement analysis, design, coding, testing, deployment, and maintenance. While it allows for systematic steps to ensure software quality and reliability, traditional SDLC often sidelines security until late stages in the software development process.

The growth of sophisticated cyber threats underscores the limitations of traditional SDLC. To address these gaps, the Secure Software Development Lifecycle emerged, embedding security practices at every stage of the development lifecycle. Unlike traditional SDLC, which prioritizes functionality and performance, SSDLC proactively addresses vulnerabilities and significantly reduces risk.

The Importance of Integrating SSDLC into Modern Development

Integrating SSDLC is essential for any organization serious about maintaining digital trust. Cyber threats continue to rise in complexity and frequency, making a security-first approach non-negotiable. The proactive, integrated model of SSDLC dramatically reduces vulnerability risks compared to traditional SDLC methods, which often rely on reactive, late-stage patching and inefficient security tests.

Transitioning to SSDLC signifies more than just a technical shift; it represents an organizational commitment to embedding security deeply into the culture and software development lifecycle, driving resilience, compliance, and long-term trust.

Where Legacy SOAR Fails: Lack of SSDLC Integration

SSDLC ensures that security considerations are seamlessly integrated throughout the entire software development lifecycle and automation workflows, reducing vulnerabilities before they become expensive, high-risk issues in production. However, legacy SOAR solutions typically:

Lack integrated tools and features specifically designed for SSDLC
Require substantial manual effort to verify that workflows meet security and compliance standards
Leave workflows vulnerable to potential security threats due to inadequate built-in security testing and checks

These gaps force organizations to invest considerable resources — both human and financial — to ensure automation workflows remain secure and compliant, resulting in higher operational costs and increased exposure to data breaches.

How Torq Hyperautomation Integrates SSDLC by Design

Unlike traditional SOAR solutions, Torq Hyperautomation™ inherently integrates SSDLC principles throughout its platform, ensuring security is embedded into every aspect of workflow development.

Built-in SSDLC Framework

Torq’s Hyperautomation platform offers a comprehensive framework that covers planning, software development, testing, deployment, and maintenance phases. Embedding secure software development into every step of automation ensures robust, compliant workflows.

Automated Testing and Continuous Validation

With Torq, rigorous automated testing is built into the workflow development process. These comprehensive tests check for:

Vulnerabilities: Continuous scanning and mitigation of security flaws.
Performance assessments: Ensuring security measures don’t degrade functionality.
Compliance adherence: Automatic checks aligned with industry standards and regulations.

Unlike legacy solutions, Torq’s automated tests are ongoing, not isolated to specific phases. This continuous validation ensures all workflow changes and updates remain secure and adhere strictly to best practices. Torq also integrates seamlessly with existing development tools, creating a unified and efficient workflow environment.

Environment Segmentation: Development, Staging, and Production

Torq allows security teams to separate workflow development into clearly defined staging and production environments. This enables controlled testing and refinement before workflows ever touch a live environment. By isolating workflows this way, Torq dramatically reduces the risk of security incidents and ensures smooth deployments.

Torq Hyperautomation also implements robust role-based access control (RBAC) by default. These stringent access controls ensure only authorized personnel can interact with specific functions, preserving workflow integrity and security.

Agile Workflow Development with Enhanced Security

Torq doesn’t just secure your automation workflows — it accelerates their development. Its intuitive, user-friendly interface empowers users of all technical skill levels to prototype, test, and refine workflows rapidly.

Torq’s iterative, agile-driven development process incorporates continuous feedback, ensuring automations remain effective and adaptive to evolving security requirements. This agile process far surpasses the capabilities of legacy SOAR platforms, enabling your organization to respond swiftly and confidently to new threats.

Hyperautomation is Essential for SSDLC

The future of software security demands an integrated, continuous SSDLC approach that seamlessly fits into an organization’s overall development strategy. Traditional SDLC approaches that defer security considerations are no longer viable in today’s rapidly evolving threat landscape.

Organizations adopting Torq’s Hyperautomation platform can confidently build security into the core of their development processes, ensuring their automation workflows remain robust and resilient against evolving threats. This continuous, integrated security approach positions organizations to maintain compliance, build digital trust, and sustainably mitigate risks.

Legacy SOAR solutions simply can’t keep up with modern cybersecurity demands. Their lack of built-in SSDLC support leaves critical gaps, resulting in higher costs, increased risks, and significant manual overhead. In contrast, Torq’s Hyperautomation platform is built from the ground up with security-first principles.

With automated SSDLC support, rigorous security checks, robust environment segmentation, and agile workflow development, Torq ensures automations are secure, compliant, and ready to handle today’s dynamic threat landscape.

Secure your organization’s future with Torq’s integrated SSDLC and Hyperautomation capabilities.

How to Migrate from SOAR to Torq

Security Operations Center Best Practices to Boost Security & Automate Smarter

By Patrick “PO” Orzechowski

July 16, 2025

10 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.

Running a SOC isn’t for the faint of heart. I should know. Late nights, understaffed teams, endless alerts, and jumping from tool to tool — all fueled by a probably unhealthy amount of energy drinks? Yeah, I’ve been right there in the trenches. And let’s face it: the old SecOps playbooks can’t scale in the face of modern SOC challenges.

The SOC best practices below are the hard-won lessons that separate the security operations centers that struggle to keep up from the ones that position themselves as strategic value centers.

Level Up Your SOC: Best Practices to Stay Sharp and Secure

A Security Operations Center (SOC) brings together people, processes, and technology to manage and improve an organization’s security posture. Put simply, it’s the command center for protecting a business from cyber risk and threats.

In a world where a single data breach can cost millions, an efficient SOC isn’t a luxury — it’s a core business function. An effective security operations center can significantly reduce an organization’s risk by identifying, analyzing, and responding to cybersecurity incidents in near real-time, or better yet, finding and mitigating vulnerabilities before they ever become an incident.

When I ask security operations center leaders the “why” behind the way they built their SOC, most mention that it’s to:

Proactively prevent cybersecurity incidents by detecting and fixing vulnerabilities, security monitoring, and gathering threat intelligence on known threats.
Minimize the impact of data breaches by rapidly containing incidents and minimizing their impact on the organization.
Ensure business continuity by protecting critical assets and data so business operations can continue without interruption.

At the end of the day, all of these drive up to the ultimate goal of a SOC: reducing risk to the business.

5 Most Common SOC Challenges

If you run an SOC, these challenges probably keep you up at night. They’re not just headaches — they’re fundamental risks to your security posture.

1. Alert Fatigue

Alert fatigue is more than just “too many alerts” — it’s a soul-crushing onslaught of low-fidelity noise and false positives that buries the critical alerts that matter. While the cybersecurity industry is a bit of a broken record around alert fatigue, it doesn’t change the fact that most teams are still struggling with it — more than half of security teams say false positives are a huge problem, and nearly two-thirds are overwhelmed by sheer data volume. Alert fatigue burns out already stretched-thin SOC teams, delays threat detection and incident response, and increases the risk of missed threats.

2. Tool Overload

Too many security operation centers I see have sprawling security stacks of disconnected tools that don’t play nice. Security analysts waste precious time swiveling between different UIs and even writing clunky PowerShell or Python scripts to gather information, trying to solve a puzzle with pieces from different boxes.

3. Manual Processes

In 2025, there’s simply no need for human SOC analysts to be manually copy-pasting information from one tool to another to build a case. These repetitive, mind-numbing tasks are slow, prone to human error, and a complete waste of your team’s valuable expertise.

4. Talent Shortage

Finding and retaining top-tier security talent is brutally competitive. The shortage is real, and it means you can’t just throw more people at the problem (especially when budgets are lean). You have to make the team you have exponentially more effective. A crucial part of that is keeping your SOC analysts engaged — automating mundane tasks takes tedious work off their plates, which directly increases morale, boosts productivity, and gives your best talent a reason to stay.

5. Scalability Issues

The volume of data from cloud environments, SaaS applications, and distributed endpoints is exploding, and the security perimeter is larger than ever. A SOC built on manual processes and disjointed tools simply cannot scale to meet this demand. As your business operations — and your attack surface — grows, your security coverage will fall further and further behind unless you start automating.

6. The Ransomware Time-Bomb

Today, every organization of any size is a target for ransomware, and ransomware operators are moving at unprecedented speed, with a median time from initial breach to business-ending payload of less than 24 hours. This breakneck pace demands an immediate and flawless response that is nearly impossible to deliver with manual processes.

7 Security Operation Center Best Practices

Since I started at Torq, I’ve heard the same story from CISOs over and over — they’ve finally reached a tipping point with tech sprawl. They’re looking at unwieldy, expensive security stacks and asking the hard questions: Are these dozens of tools actually making us more secure, or are they just burning out our security analysts and our budget?

This is leading to a massive push for real SOC transformation. The smartest leaders I talk to are no longer content with running a reactive cost center that just cleans up messes. They’re determined to build a proactive, data-driven value center that anticipates cyber threats and demonstrates clear ROI, often by replacing ten disjointed tools with three or four that work together. But getting there requires a fundamental shift in strategy.

The following security operations center best practices are the playbook for that transformation.

1. Build a Strong Foundation with the Right People and Processes

Stop hiring bodies and start building a team. Move from generalized security playbooks to methodical runbooks that combine your security analysts’ expertise with strategic automation and AI augmentation.

2. Prioritize Threat Detection and Response to Your Business Needs

It’s key to shift your team’s focus from managing alerts to actively hunting cyber threats. But with the sheer volume of today’s alerts pinging from sprawling stacks and an explosion of endpoints, the only way to free them up is by leveraging automation and AI to handle the majority of your Tier-1 alerts.

3. Automate the Mundane, Focus on the Critical

Automating repetitive and time-consuming tasks allows your limited resource of human expertise to be focused on more strategic activities, such as threat hunting and investigating complex and critical cases.

4. Embrace Continuous Improvement

The most overused wording in cybersecurity think pieces is probably “the constantly evolving threat landscape,” but the truth still stands. To keep up, SOCs must continuously improve their processes and technologies, which means regularly reviewing and updating security policies, tools, processes, and procedures, tracking and reporting KPIs, and being able to slice and dice case data to pinpoint problem areas.

5. Measure Everything

If you can’t measure it, you can’t fix it. Mean time to investigate, respond, and remediate aren’t vanity metrics — they are the vital signs of a SOC. When you can show your CISO that Hyperautomation slashed MTTI from hours to minutes (like this top 30 U.S. bank did), you’re no longer talking about a cost center; you’re talking about tangible, provable ROI.

6. Be Strategic About AI

AI is the biggest buzzword in security right now, with every vendor promising it can solve all of your problems. But it’s not a magic wand — and there’s a whole lot of AI-washed marketing out there right now. The real power of AI in the SOC is leveraging it to automate away the noise and grunt work and accelerate incident response, so your human SOC analysts can hunt cyber threats and handle complex incidents. And if an AI solution can’t prove its logic with evidence, it’s a black box that will kill trust and has no place in your SOC. See how to deploy AI in the SOC the right way.

7. Consolidate and Optimize

True optimization isn’t a “lift and shift” of your old, inefficient workflows to a new platform — it’s about fundamentally transforming your processes. Torq helps customers escape the tech debt of legacy SOAR by replacing dozens of brittle, code-heavy workflows with a handful of powerful and efficient automations built easily in Torq.

When migrating off a SOAR, Torq customers consistently consolidate their processes, achieving the same outcomes with significantly fewer and more efficient automations, often slashing their workflow count by 30% or more. Get the SOAR migration guide.

The Best SOC Tools

You can’t win today’s fight with yesterday’s technology. What’s the core solution you need to build a modern, autonomous SOC?

Torq HyperSOC

HyperSOC™ is the AI-driven platform I wish I had years ago. Designed specifically to crush the biggest challenges SOCs face, HyperSOC uses powerful, no-code automation to become the connective tissue for your entire security stack, so your cases are managed out of a single interface, and agentic AI autonomously handles 90% of Tier-1 case work.

Here’s how HyperSOC incorporates critical SOC best practices, built in:

Automates alert triage: HyperSOC ingests the flood of alerts across your stack, using automation and AI to add context, dismiss false positives, and group related alerts into a single, actionable case. It cuts through the noise so your team only sees what truly matters.
Connects your security tools: Torq has hundreds of pre-built integrations to instantly connect your SIEM, endpoint detection and response (EDR), threat intelligence, ticketing, and communication platforms into seamless, automated workflows.
Uses no-code, low-code, and AI-generated workflows: With Torq, you don’t need a team of developers to build complex automations. Torq’s drag-and-drop and AI-generated workflow-building capabilities mean anyone can create automations to handle everything from phishing investigation to endpoint containment.
Supports human-in-the-loop actions: Any AI deployed in the SOC needs to be transparent to be trustworthy. Torq makes it easy to inject human decision points into any AI workflow. Torq’s AI SOC Analyst Socrates can automatically investigate and enrich a case, then present it to a security analyst in Slack or Teams for a final decision on a critical action.

The Foundation for Transformation: Why SOC Best Practices Matter

The days of running a SOC on manual processes and sheer willpower are over. The only way to win against fast, AI-powered adversaries is to fight back with smarter, faster automation. By following security operations center best practices like prioritizing automation, empowering your team with the right tools, and quantifying outcomes through metrics, you can transform your SOC into a strategic value center.

Torq HyperSOC was designed specifically to automate and orchestrate modern SOC operations at scale. Want to learn more about how HyperSOC can help your security operations center get a whole lot more done, a whole lot faster?

Get the SOC Efficiency Guide packed with insights from my years in the trenches as a SOC leader.

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MTTD vs. MTTR: Definition, Differences, & Why They Matter

By Torq

July 15, 2025

6 Minute Read

When a cyberattack occurs, every second counts. Metrics like Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR) are critical benchmarks in cybersecurity, helping organizations evaluate the effectiveness of their Security Operations Centers (SOCs). But what’s the difference between MTTD vs MTTR, and why do they matter?

Understanding and improving these metrics through strategic investments in security automation can significantly elevate your security posture, minimize damage, and keep your organization safe from threats.

MTTD vs. MTTR in Cybersecurity

Mean Time to Detect and Mean Time to Respond are both fundamental KPIs in cybersecurity, but each measures something distinct.

MTTD (Mean Time to Detect) measures the average time it takes your team to identify that a security incident has occurred. This metric primarily evaluates your monitoring and detection capabilities. A lower MTTD indicates your security stack can quickly recognize anomalies and suspicious activity.
MTTR (Mean Time to Respond) (sometimes called Mean Time to Resolve) tracks the average time required to respond to and resolve an incident fully. Speed matters; a recent SANS survey found that 33% of teams take hours to respond to threats. That’s too long. A shorter MTTR reflects strong incident response procedures and an agile, responsive security team.

MTTR often involves people and a series of steps that are needed to fix the issue. While MTTD may measure how well an automated alert system performs, MTTR often measures both your systems and the people you depend on to jump into action after an incident.

Together, these metrics illustrate your SOC’s maturity and operational effectiveness. Optimizing MTTD and MTTR directly reduces risk and overall damage from cybersecurity incidents.

How Automation Improves MTTD and MTTR

Security automation plays a pivotal role in dramatically enhancing both MTTD and MTTR, empowering security teams to scale detection and response effectively by:

Improving detection: Automated systems like SIEM, EDR, and XDR can swiftly correlate vast data sets, instantly surfacing anomalous activities. Automation reduces reliance on manual log analysis, ensuring immediate, accurate threat identification.
Accelerating response: Automation streamlines and accelerates incident response workflows. Tasks like enrichment, analysis, and containment that typically consume significant analyst time become nearly instantaneous. Automation eliminates the manual “grunt work,” allowing analysts to focus solely on complex or high-risk situations.
Reducing human error: With agentic AI handling the automation, repetitive tasks become consistently executed according to predefined procedures, drastically reducing the potential for mistakes and inconsistencies in handling security incidents.
Seamless integration: Hyperautomation platforms integrate seamlessly with SIEM, EDR, and XDR tools, delivering rapid data exchange, correlation, and enriched context. This tight integration creates an end-to-end, automated security ecosystem.

In short, automation significantly shrinks the time between detecting a threat and mitigating its impact, providing an immediate, measurable boost to your SOC performance.

How to Measure MTTD & MTTR (with Formulas)

Quantifying your incident response effectiveness requires clear measurement methods. Here’s how you calculate each:

Below is some practical guidance for measuring MTTD and MTTR:

Consistent tracking: Record timestamps at every key incident stage (i.e., detection, acknowledgment, investigation, and resolution).
Aggregate metrics: Regularly aggregate these timings to spot trends or inefficiencies in your process.
Benchmarking: Establish baseline metrics to evaluate the impact of new tools, processes, or automation investments.

MTTD and MTTR don’t exist in isolation. They are part of a broader landscape of incident response metrics that security teams should be tracking, including:

MTBF (Mean Time Between Failures): MTBF measures the average time between system failures. It’s useful for evaluating the reliability of security systems and predicting when future incidents might occur. A higher MTBF indicates stable security operations.
MTTF (Mean Time to Failure): MTTF tracks the average lifespan of a security tool or system component before a failure occurs. It’s commonly used to assess product reliability and helps organizations schedule proactive maintenance or upgrades.
MTTA (Mean Time to Assignment): MTTA is the average time it takes for an incident to be assigned to a specific analyst or team member after detection. Lower MTTA reduces response latency and enables teams to tackle threats more efficiently.
MTTI (Mean Time to Investigate): MTTI represents the average time taken from initial detection until the investigation is completed. Faster MTTI means threats can be understood and contained sooner, limiting potential damage.
MTTx (Mean Time to “Anything”): MTTx is a flexible metric used at Torq to track the average time to complete any defined security operation or workflow. It helps SOC teams measure efficiency across custom actions, automations, or specific tasks unique to their security processes.

Understanding these related metrics provides deeper insight into your security operations and helps identify specific bottlenecks or areas for improvement.

Key Incident Response Metrics Explained

Illustration showing MTTD vs MTTR metrics comparison

The Hyperautomation Domino Effect in Incident Response

Improving MTTD and MTTR isn’t just about moving faster; it’s about removing the friction between each phase of the incident response lifecycle. Torq Hyperautomation connects the dots across the entire workflow — from detection to assignment, investigation to remediation — creating a seamless chain reaction of automation that compounds every efficiency. Here’s how that automation domino effect plays out in practice:

Faster detection (MTTD): Torq reduces noise by automatically filtering out low-priority alerts and surfacing real threats faster. This shrinks MTTD and ensures analysts aren’t wasting time chasing false positives.

Faster assignment (MTTA): Once a threat is detected, a case is immediately built and assigned to the right resource within Torq’s intelligent case management dashboard. Torq decides in real time whether Socrates — the AI SOC analyst that offloads 90%+ of Tier-1 cases — or a human should take the lead, dynamically reassigning ownership if the threat escalates. That means alerts don’t sit in limbo, waiting to be noticed.

Faster investigation (MTTI): By the time an analyst gets involved, much of the work is already done. Torq HyperSOC automatically enriches and correlates incident data, while AI agents generate case summaries and assign relevant case runbooks. This allows analysts to dive straight into meaningful analysis, not manual triage.

Faster response (MTTR): Response time is reduced by how quickly and efficiently action is taken. Analysts can trigger remediation with a single click or let Socrates respond autonomously in milliseconds. Whether isolating a device, disabling a user, or launching a complex remediation strategy, action happens at machine speed.

Each improvement compounds the next, like dominoes falling one after another. The faster a threat is detected and assigned to the appropriate resource, the faster those resources can be actioned. With Torq Hyperautomation, every second saved is multiplied across the incident lifecycle, delivering exponential gains in speed, accuracy, and scale.

Reduce Your MTTD and MTTR with Torq Hyperautomation

Effectively managing cybersecurity threats requires fast detection and even faster responses. Clearly differentiating MTTD vs. MTTR and understanding related metrics like MTBF, MTTF, MTTA, and MTTI enables SOC teams to target improvements strategically.

The Torq Hyperautomation™ platform offers a proven way to dramatically lower both MTTD and MTTR through real-time incident detection, streamlined automated workflows, and reduced analyst workload. Torq helps organizations minimize alert fatigue, decrease caseload per analyst, and improve overall compliance and efficiency.

Ready to drastically reduce your MTTx? Get practice advice from our Field CISO on how to make your SOC more efficient.

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How AI is Redefining SOC Architecture

By Bob Boyle

July 14, 2025

8 Minute Read

This antiquated SOC architecture model, where every alert and log file is funneled into a Security Information and Event Management (SIEM) solution for analysis, is too slow, too rigid, and creates too many bottlenecks to support today’s exploding security event and data pipeline. Modern SOCs need speed, scalability, and a level of intelligence that legacy architecture simply cannot provide. They need a new approach that is purpose-built for the AI era.

What is AI SOC Architecture?

AI SOC Architecture

AI SOC architecture is a modern, AI-augmented design for SOCs that decentralizes data processing, automates low-level tasks, and enables agentic systems to proactively investigate, triage, and respond to threats.

AI SOC architecture is not just about adding AI to the stack — it’s about re-architecting the stack around AI. The traditional SOC model relies on aggregating data into a centralized point of analysis before taking action. In contrast, the AI SOC places agentic, AI-powered Hyperautomation at the center of operations — integrating directly with data lakes, security tools, and workflows to create a unified, AI-native control plane. This architecture ensures a single source of AI truth, distributed evenly across the entire security stack.

Shifting the SOC Foundation

“Architecture is changing. Automation tools like Torq are being plugged directly into FDR and identity systems — not after the SIEM, but before it.”
Francis Odum, Software Analyst Cyber Research

For years, the SOC has been centered around the SIEM. Disparate security vendor solutions would feed hundreds of thousands of logs, events, and alerts into the SIEM for security analysts to manually parse through, correlate, and eventually return to the respective point solution(s) to begin the remediation process. This model created a lot of friction, leading to several chronic problems, including:

Process debt: This process would cause what we in the biz call “swivel chair syndrome,” as it often isn’t as simple as a single straight line from detection to SIEM to remediation. Instead, the lengthy investigation had analysts swiveling back and forth between the SIEM and security tools several times before reaching a conclusion hours later.
Central bottlenecks: While a centralized approach to security event management once seemed favorable, SIEM solutions were not designed for the volume of data produced by the multi-cloud environments that organizations have built — let alone the deployment of AI to help alleviate the manual filtering of that data. This creates a massive data bottleneck and, worse, a single point of failure for the SOC to rely upon.
Reactive, delayed response: In addition to scalability concerns, this is also a largely reactive approach, requiring analysts to use the SIEM to begin the manual investigation process long after an incident occurs. This slows down critical SOC reporting metrics like Mean-Time-To-Detection (MTTD) and Mean-Time-To-Response (MTTR). Legacy SOAR solutions attempted to solve this problem but did not promise faster orchestration or response times due to limited and inflexible automation playbooks.

Between sifting through an overwhelming amount of logs in a centralized SIEM solution and battling the manual efforts of legacy SOAR automation, security analysts find themselves drowning in disconnected alerts and burning out at an alarming rate.

An AI SOC architecture flips this on its head, shifting the SIEM further left in the security event lifecycle, particularly as many organizations continue to adopt a multi-SIEM strategy to offset increasing storage costs from legacy SIEM vendors.

Gartner’s recent Reference Architecture Brief: SIEM-Centric Security Operations report points out that as the industry largely shifts away from legacy SOAR solutions, it is seeing more advanced capabilities come from platforms centered around AI SOC Analysts, which produce stronger outcomes for analyst augmentation and security automation.

What Does AI-Native SOC Architecture Look Like?

In the same report, Gartner breaks down the Security Operations Center architecture into two distinct components: Security Operations Tools (e.g., SIEM and Detection-as-Code solutions) and SOC Actions (e.g., manual triage, investigation, threat hunting, and response via the SOC Team). Gartner calls out SecOps Workflow Automation, which consists of third-party automation and AI SOC analysts, bridging the gap between these two pillars of the SOC.

This is the heart of the AI-native SOC Architecture — a foundation of agentic AI and Hyperautomation built for the modern cloud-first SOC environment and designed for simplicity, extensibility, and scale.

Torq unifies security tools with AI SOC analysts and Hyperautomated workflows — streamlining triage, case management, and incident response.

Agentic AI

Agentic AI sits at the core of the AI SOC architecture. Rather than burdening human analysts with manually piecing together thousands of logs and events, an AI-native SOC leverages a multi-agent system (MAS) to handle up to 90% of Tier-1 security analysts’ tasks. These specialized AI agents have a deep understanding of the SOC environment, allowing them to plan incident response, make complex decisions, and take remediation actions autonomously.

Hyperautomation

Hyperautomation is the engine that drives autonomous response and the glue that connects agentic AI with the rest of the SOC solutions to bridge the gap between Security Operations Tools and SOC actions. With limitless no-code or AI-generated integrations, the Hyperautomation engine is the delivery system allowing agentic AI to take action, automating anything from simple alert triage to complex, multi-step incident responses.

Enterprise-Grade Security Architecture

Unlike monolithic legacy SIEM and SOAR solutions, an AI-native SOC architecture is built for cloud-first scalability and flexibility. Underpinned by an extensible security architecture, horizontal and elastic scalability allows the SOC to dynamically process and prioritize hundreds of thousands of events from various data sources, ensuring the most critical information is surfaced without interruption.

Torq’s AI SOC Architecture

Torq is built for this moment. It’s not about retrofitting AI into a legacy architecture — Torq is an enterprise-ready, AI-native platform purpose-built from the ground up to solve existential SOC challenges like alert fatigue, tech sprawl, and analyst burnout.

Torq’s AI SOC architecture begins with the ability to integrate with any solution across the entire security stack and beyond — whether it’s EDR, IAM, email phishing, threat intelligence, collaboration and communication tools, and more.

This direct integration enables agentic AI to not only take autonomous remediation actions across Tier-1 and Tier-2 security use cases but also allows AI agents to retrieve and enrich data directly from the source, regardless of what data may be missing (or difficult to find manually) from SIEM logs. As the modern SOC scales to produce tens of thousands of alerts per day, Torq’s AI-SOC architecture can seamlessly handle massive alert volumes without creating single-point bottlenecks.

HyperSOC™

Torq HyperSOC, the AI-powered autonomous SOC solution, was also explicitly designed to support AI deployment across the modern SOC. While legacy SOAR solutions have bolted-on workarounds to handle case management once an analyst has manually pulled the relevant data from a SIEM tool, Torq HyperSOC is comprised of intelligent case management and Socrates, the agentic AI SOC Analyst, embedded directly in each security case. Socrates summarizes key findings, suggests next steps, and analyzes case runbooks for autonomous remediation.

The Multi-Agent System

Socrates coordinates Torq’s multi-agent system, a team of AI Agents that can autonomously handle the vast majority of Tier-1 and Tier-2 use cases, reduce human analysts’ workload by over 95% from initial investigation to final remediation, and enable SOC teams to tackle up to 5x more security cases in a single day without adding headcount.

Socrates leads Torq’s multi-agent AI system, autonomously resolving cases, reducing analyst workload by 95%, and enabling SOC teams to handle 5x more incidents daily.

Model Context Protocol

To help Torq’s system of AI agents communicate reliably across a limitless amount of integrated security tools and other AI solutions deployed in the SOC, Torq’s AI SOC architecture also natively supports Model Context Protocol (MCP), an open protocol designed to standardize how applications provide context to AI Agents to retrieve contextual information from applications and systems.

Human-on-the-Loop AI Guardrails

Finally, this entire AI architecture is designed with the appropriate AI guardrails that provide the explainability, audibility, and control organizations require. These guardrails ensure there is always a human on the loop to avoid AI hallucinations and so SOC teams remain in control of critical decisions.

From AI-Enabled to AI-Architected

Legacy SOC architecture isn’t just outdated — it’s actively holding organizations back. True AI-native SOC architecture, like Torq HyperSOC, breaks through these barriers. It offers immediate, measurable outcomes, dramatically improving analyst effectiveness, reducing costs, and transforming security postures from reactive to proactive.

In Francis Odum’s words: “The market is ready for next-gen, AI-powered solutions. These aren’t future-state ideas; they’re delivering real-world results right now.”

The future of cybersecurity isn’t just AI-enabled; it’s AI-architected.

Get the AI or Die Manifesto to learn strategic considerations and evaluation criteria for deploying AI in the SOC from the ground up.

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Tired of Security Alert Fatigue? Stop Burnout with Hyperautomation

By Torq

July 9, 2025

10 Minute Read

Every day, analysts are buried under a mountain of low-value and often meaningless alerts. And they’re expected to triage, investigate, prioritize, and respond to all of them — faster, better, and with fewer people. With this comes cybersecurity alert fatigue, which can lead to missed threats, slower response times, and SOC analyst burnout.

The good news is that SOC analysts don’t have to live like this anymore. Not if you have the right kind of AI working for you. This blog explores what security alert fatigue is, the causes, and how agentic AI can kill your SOC alert fatigue.

What is Alert Fatigue?

Cybersecurity Alert Fatigue

Alert fatigue in cybersecurity refers to the desensitization and exhaustion experienced by security analysts when they are overwhelmed by a high volume of security alerts, many of which are false positives or low-priority events. This can lead to missed or ignored true threats, potentially causing significant security incidents and breaches.

More than half of security teams say false positives are a huge problem, and 62.5% are overwhelmed by sheer data volume. Without effective triage or prioritization, it becomes harder to distinguish real threats from background noise. This leads to slower detection and response, missed incidents, and higher stress on already-stretched SOC teams, which in turn increases risk to the business.

What Causes Cybersecurity Alert Fatigue?

Alert fatigue is the result of too many notifications with too little value. And it’s a problem that only gets worse as security environments become more complex. Here’s what’s driving it.

Excessive False Positives

False positives occur when security systems incorrectly flag benign events as threats. SOC teams inundated with false positives quickly become overwhelmed and stop trusting the alerts altogether. A recent study indicated that more than half of security alerts are false positives, making analysts skeptical about their legitimacy.

Poorly Tuned Detection Rules

Security monitoring tools like SIEM and SOAR platforms rely on detection rules to trigger alerts. When these rules are not properly tuned or regularly updated, they generate an overwhelming volume of irrelevant alerts, contributing significantly to SIEM alert fatigue and SOAR alert fatigue.

Lack of Context in Alerts

Without context, analysts spend valuable time manually investigating alerts to determine their relevance and severity. Contextual information, such as user details, historical activity, and threat intelligence, is essential for quick decision-making — yet many systems fail to provide it.

Manual Triage Processes

Manually sorting through thousands of daily alerts to decide which ones require attention is tedious and error-prone. Human analysts have limits on processing speed and focus, leading to mistakes, missed threats, and inevitable burnout.

Human Limits in Processing Volume and Urgency

Human cognition has inherent limitations. When faced with a high volume of urgent tasks, analysts inevitably experience exhaustion, become less effective, and experience reduced productivity, exacerbating overall security team burnout.

Legacy SOAR

Legacy SOAR is the #1 driver of SOC alert fatigue. It’s a rigid model that treats every alert like a five-alarm fire. It floods analysts with noise, drowns them in contextless data, and racks up costs with every added integration. And because most legacy SOAR platforms are stuck on-prem, they can’t scale or flex with today’s modern security environments.

The Cost of Alert Fatigue in Cybersecurity

Missed vulnerabilities, delayed incident response: When analysts become numb to the constant flood of alerts, critical incidents can slip through unnoticed. Missed threats or delayed responses increase the likelihood of successful cyberattacks, leading to data breaches or significant operational disruptions.

Burned-out analysts and high turnover: Continuous exposure to high stress and repetitive tasks results in analyst burnout. Studies indicate that more than 70% of SOC analysts report burnout, driving skilled talent away and compounding the cybersecurity skills shortage.

Diminished trust in security systems: When false alarms dominate, analysts lose faith in their tools and processes. This lack of trust can lead to negligence or poor decision-making, ultimately undermining your entire cybersecurity posture.

Increased exposure to threats: Ignoring genuine alerts due to fatigue directly translates to higher vulnerability to cyber threats. Attackers exploit this weakness, capitalizing on diminished responsiveness to launch successful attacks.

Wasted resources: Teams overwhelmed by junk alerts often require more headcount. That’s expensive and inefficient.

Reputation damage: When a preventable breach hits the headlines, the fallout can be massive.

Legal and compliance issues: Missed threats can turn into breaches. Breaches mean SEC reporting, fines, investigations, and answering a whole lot of questions.

The average cost of a data breach was $4.9M in 2024, a 10% increase year over year. On the flip side, organizations that fully embraced security AI and automation saved an average of $2.2M compared to those that didn’t, according to IBM.

How Automation Helps You Beat Alert Fatigue

Security automation has become an essential solution for SOC teams to significantly reduce cybersecurity alert fatigue. Here’s how automation addresses the core issues.

Alert enrichment at scale: Automation enriches alerts with relevant context automatically, including threat intelligence data, historical user behavior, and asset criticality, enabling rapid and informed decisions.

Correlation and deduplication: Automation tools correlate related alerts and remove duplicates, drastically reducing noise. Analysts receive fewer but more comprehensive and meaningful incidents, improving efficiency and accuracy.

Routing to the right responder: Automated systems ensure alerts reach the appropriate analyst based on expertise, urgency, or resource availability. This eliminates delays in assignment, balances resource utilization, and improves team responsiveness.

Automated remediation of low-risk threats: Remediating low-risk incidents autonomously significantly reduces repetitive tasks. This allows analysts to prioritize their time and attention on high-severity threats.

Feedback loops for smarter alerting: AI-driven automated systems can learn from past incidents, continuously refining detection rules and processes to reduce false positives and enhance accuracy, minimizing future alert fatigue.

How To Combat Alert Fatigue

While automation is the key solution, here are other best practices your SOC team can implement to reduce alert fatigue further:

Regular optimization: Routinely updating detection rules can somewhat reduce irrelevant alerts.
Prioritization strategies: Clearly define which alerts matter most based on business risk and prioritize accordingly.
Enhanced alert context: Invest in tools providing contextual intelligence so analysts quickly understand the nature of each alert.
Regular training and support: Ensure your team has access to continuous education and training, reinforcing resilience and reducing burnout.
Centralized management: Consolidate alerts into a single case management platform to streamline workflows and reduce duplication.

5 Benefits of Automating Cybersecurity Alert Triage

Automating alert triage doesn’t just address fatigue; it transforms your entire security operation.

80% fewer alerts reaching human analysts: Automation filters out irrelevant alerts, dramatically decreasing the number of notifications analysts need to review, significantly reducing cybersecurity fatigue.
Faster time to detect and respond (MTTD/MTTR): Automation reduces both mean time to detect (MTTD) and mean time to respond (MTTR), allowing analysts to act swiftly and decisively when genuine threats appear.
Reduced analyst burnout and turnover: By offloading repetitive tasks, automation allows analysts to focus on more engaging, complex issues that require critical thinking, significantly reducing burnout and improving job satisfaction.
Higher confidence in escalated alerts: With fewer false positives and enriched context, analysts have more trust in alerts escalated to them, ensuring quick and effective response.
Measurable reduction in false positives: Automated feedback loops continuously improve detection logic, resulting in fewer unnecessary alerts over time, further reducing security alert overload.

How Torq Can Prevent Cybersecurity Alert Fatigue with Automation

Security teams have always relied on automation to streamline repetitive tasks, but traditional automation still requires substantial human oversight and manual intervention. Hyperautomation, however, elevates security operations to an entirely new level by combining advanced deterministic automations with AI-driven non-deterministic automations for real-time adaptive decision-making capabilities.

Unlike basic automation, which crumbles under the pressure of too many complex alerts, Hyperautomation handles volumes that SOAR and other legacy platforms can’t even come close to. It dynamically filters, enriches, correlates, and aggregates alerts at machine speed, ensuring analysts see what actually matters.

Torq HyperSOC™ takes Hyperautomation a step further by integrating agentic AI — an intelligent system capable of autonomous reasoning, decision-making, and iterative planning — to manage security operations at unprecedented speed and scale. Torq HyperSOC dynamically adapts, picking the most appropriate Hyperautomation workflows based on live data and context, enabling autonomous resolution of complex security issues.

Unlike traditional automation, agentic AI iteratively plans and reasons, adjusting actions based on real-time context. It automatically filters noise, enriches data, correlates related alerts, and resolves low-risk incidents without human intervention.

With agentic AI, Torq has replaced repetition with relevance. Our multi-agent system takes on the tasks that drain analysts most — triage, enrichment, correlation, case summaries, even full remediation—and executes them autonomously. Analysts no longer have to sift through countless meaningless alerts because HyperSOC escalates only those that truly require human attention. That means fewer panicked 2 a.m. Slacks and “Why am I still doing this manually?” moments.

“Torq HyperSOC is the first solution we’ve seen that effectively enables SOC professionals to mitigate issues including alert fatigue, false positives, staff burnout, and attrition.”
IDC: Achieving Machine Speed Detection and Response

Torq HyperSOC achieves:

Up to 95% reduction in alert volume: HyperSOC automatically filters, correlates, and prioritizes alerts, drastically reducing noise for analysts.
Real-time incident remediation: Automates end-to-end response, resolving low-risk threats autonomously without human intervention.
Accelerated mean time to detect and respond (MTTD/MTTR): Identifies and addresses critical security incidents in seconds, minimizing potential damage.
Reduced analyst burnout and improved rroductivity: Offloads repetitive tasks, freeing SOC analysts to focus on high-value activities that require human expertise.

With HyperSOC, SOC analysts can finally shift from constantly firefighting false positives to focusing their expertise on high-impact threats that demand human ingenuity.

Legacy SOAR vs. Torq HyperSOC™: Solving Alert Fatigue

Here’s how Torq HyperSOC™ stacks up compared to legacy SOAR systems when it comes to solving cybersecurity alert fatigue.

Legacy SOAR	Torq HyperSOC
SOC alerts are treated like a five-alarm fire, with no intelligent prioritization	Agentic AI triages and prioritizes alerts with semantic, episodic, and procedural memory
Inflexible, SIEM-dependent pipelines for noise reduction and enrichment	Hyperautomation eliminates SIEM dependency and enriches data on the fly
Manual alert triage leads to SOC burnout and delays	AI-driven triage, investigation, and remediation reduce analyst burden
Rigid, on-prem architecture limits scalability and flexibility	Cloud-native architecture scales effortlessly with your environment
Siloed tools and alerts lack unified context	Multi-agent system correlates alerts into unified incidents with full context
Slower response times due to disconnected systems and workflows	End-to-end automation delivers sub-minute response times
High analyst turnover from alert overload and frustration	AI offloads repetitive work, reducing burnout and improving retention

By taking over the repetitive, time-consuming tasks that drive SOC burnout, agentic AI lets analysts do the work that actually matters. You know, the reason they got into security in the first place.

Hyperautomation is the Answer to Cybersecurity Alert Fatigue

The constant flood of alerts compromises response times, erodes analyst trust, causes burnout, and directly increases your organization’s cyber risk. Without addressing cybersecurity alert fatigue, your security strategy is fundamentally flawed.

Hyperautomation, driven by advanced AI, provides a decisive answer to alert fatigue. By automating routine, repetitive tasks and prioritizing real threats, it drastically enhances SOC efficiency and resilience. Torq’s HyperSOC, with its innovative agentic AI, stands at the forefront of this solution, empowering teams to work smarter, not harder.

Ready to take control of your alerts and eliminate SOC burnout once and for all? Learn how to kill your SOAR.

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What is a Cloud-Native Security Automation Framework? Benefits & Use Cases

By Torq

July 3, 2025

9 Minute Read

This blog explores cloud-native security automation, why traditional methods no longer work in modern cloud-native environments, and how teams can transition from reactive security measures to proactive Hyperautomation. Let’s explore the transformative benefits and essential strategies for implementing cloud security automation effectively.

Cloud-Native Security 101

Before you can automate cloud-native security, you need to understand what makes cloud-native security fundamentally different.

In a cloud-native security model, security is integrated from the start, woven directly into both applications and infrastructure, not tacked on later. It relies on automated controls, DevOps alignment, and security teams equipped to navigate complex, fast-moving environments. The objective is to defend against the unique risks of cloud architectures while maintaining continuous compliance with evolving standards and regulations.

What is Cloud-Native Security?

Cloud-native security is an approach that embeds security into every layer of the cloud-native stack, from infrastructure to application code. Rather than adding security as a bolt-on, it’s integrated into the DevOps lifecycle using automated tools and policies. It addresses the unique risks of dynamic, distributed, and containerized environments.

The concept is structured around the 4Cs of cloud-native security:

Cloud: The foundational infrastructure provided by cloud vendors
Clusters: The orchestration layer (e.g. Kubernetes) or other orchestrators managing containers
Containers: The isolated runtime environments housing applications
Code: The actual application logic and configurations deployed across the stack

Key use cases of cloud-native security include identity management, access control, vulnerability scanning, runtime monitoring, and automated response. Together, these create a holistic, resilient security posture that protects organizations at every level of their cloud infrastructure.

A cloud-native security automation framework is a structured set of technologies, workflows, and best practices that automatically detect, prioritize, and respond to threats across cloud-native environments. It integrates security throughout the cloud stack — cloud, clusters, containers, and code.

Manual Cloud Security is Broken: Key Challenges

Traditional security operations can’t keep up with the pace and scale of cloud-native infrastructure. Human analysts struggle to keep pace with rapidly scaling environments and managing cloud-native applications, making manual methods prone to error and inadequate against modern threats. Here are some critical issues:

Bottlenecks: Manual processes delay threat detection and response, increasing exposure to potential breaches. Each delay amplifies the damage from vulnerabilities that attackers can exploit.
Security team burnout: Analysts overwhelmed with alerts face burnout, lowering efficiency and morale, and increasing the likelihood of missed threats. This persistent stress leads to higher staff turnover and reduces overall team productivity.
Inconsistencies: Manual security procedures are difficult to replicate consistently, causing varied security effectiveness across deployments. This inconsistency can leave critical assets exposed and vulnerable to attacks.
Diagnostic difficulties: Manually correlating events across disparate tools and environments leads to slow and often incomplete investigations. Without automated analytics and correlation, incidents are frequently misunderstood or missed entirely.

Automation addresses these manual shortcomings by significantly increasing efficiency, ensuring consistent and accurate enforcement of security policies, and substantially reducing human error, especially critical in complex and rapidly evolving cloud environments.

5 Benefits of Cloud Security Automation

Cloud security automation addresses these challenges, transforming security operations into proactive, efficient, and scalable processes. Here’s why you should automate everything.

1. More Efficient Operations

Automated processes dramatically speed up threat detection, response, and remediation, reducing operational friction and freeing analysts for strategic tasks. With automation, teams can shift focus from repetitive tasks to strategic, value-adding activities. This is especially crucial in Kubernetes-based, serverless environments where threats move fast.

2. Ensure Compliance

Automation helps consistently enforce security policies, compliance standards, and best practices, ensuring your infrastructure continuously meets regulatory requirements like HIPAA, SOC 2, and PCI-DSS. Automated audit trails and compliance checks further simplify adherence to industry standards.

3. More Accuracy

Automation reduces human error, delivering precise, reliable responses to security vulnerabilities every time. Automated security processes significantly decrease false positives and misconfigurations, improving the reliability of your security operations.

4. More Consistency

Automations ensure standardized security responses, reducing variability and improving overall security posture across every container and workload. This ensures a stable security posture — regardless of scale or complexity.

5. Scalability

Security automation scales seamlessly with your infrastructure, ensuring continuous protection as your organization grows. Automation tools effortlessly handle increased workloads, ensuring continuous security coverage even during rapid scaling.

How to Automate Cloud-Native Security: 12 SOC Use Cases

A cloud-native security automation framework doesn’t just respond to threats; it transforms the way SOCs operate. Below are key use cases that demonstrate how automation accelerates security operations across cloud environments.

1. Identity and Access Management (IAM)

Automate user provisioning, access approvals, and credential rotation across cloud-native applications to minimize manual errors, prevent unauthorized access, and maintain compliance at scale.

2. Automated Threat Hunting

Continuously scan cloud workloads, Kubernetes clusters, and logs for indicators of compromise. Enrich findings with threat intelligence and behavioral analytics to detect and respond to advanced threats proactively.

3. Cloud Security Posture Management (CSPM)

Monitor multi-cloud environments for misconfigurations and policy drift. Automatically trigger remediation workflows that maintain a strong security posture and ensure compliance across dynamic cloud-native infrastructure.

4. Email Security

Integrate with cloud-based email and endpoint platforms to instantly detect phishing campaigns, quarantine malicious messages, and update protection rules, without SOC analyst intervention.

5. Self-Service Chatbots

Deploy chatbots in platforms like Slack or Teams to handle common security tasks, such as password resets or access revocations. Reduce SOC workload while improving speed and user experience.

6. Incident Response Automation

Automatically triage alerts, contain threats, execute auto-remediation, and notify stakeholders. Every step — from detection to documentation — is orchestrated for speed and accuracy across cloud-native systems.

7. Application Security Automation

Integrate with CI/CD pipelines to detect vulnerabilities and misconfigurations early. Automate fixes or escalate issues directly in tools developers already use, enabling secure cloud development without delay.

8. Phishing Detection and Response

Correlate email, endpoint, and identity signals to identify phishing attempts. Automate investigation, response, and user notifications to neutralize threats quickly and consistently.

9. Continuous Vulnerability Management

Scan containers, serverless functions, and cloud-native applications for known risks. Prioritize and remediate vulnerabilities using contextual insights, before attackers can exploit them.

10. Threat Intelligence Enrichment

Automatically enrich findings with threat intel: IP geolocation, known malware hashes, adversary infrastructure, and MITRE ATT&CK mappings. Boost detection fidelity and decision-making confidence.

11. Suspicious User Behavior

In real time, detect anomalous user activity — like impossible logins or privilege escalations. Instantly respond with MFA challenges, session termination, or account lockdown.

12. Sensitive Data Access Controls

Enforce zero trust access controls for critical assets by automating policy checks, alerting on anomalies, and verifying user actions across containerized and multi-cloud environments.

Hyperautomation: The Future of Cloud Security Automation

Looking ahead, cloud security automation will increasingly use AI to enhance detection, reduce false positives, and predict potential threats. AI-driven SOC solutions will automate complex decision-making, streamline compliance, and dynamically adapt security measures, ensuring organizations maintain resilient defenses even as threat landscapes rapidly evolve.

The future of cloud security also involves empowering non-technical stakeholders through SOC automation platforms like Torq. This democratization of security allows everyone to contribute to security practices, fostering a broader organizational security culture.

Torq HyperSOC^TM is a cloud-native security automation tool, offering comprehensive, no-code solutions that enable teams to easily automate their security operations, including advanced container security, efficient management of serverless and microservices, and full integration with CNAPP capabilities.

With Torq’s no-code platform, security teams — and even non-technical stakeholders — can define rules, mitigate threats instantly, and ensure consistent security across complex multi-cloud and hybrid cloud environments, significantly reducing vulnerability risks and enhancing overall security posture.

By leveraging Hyperautomation and agentic AI with Torq, security teams can:

Automatically detect, investigate, and remediate threats across all cloud environments
Streamline identity and access management, CSPM, threat intel enrichment, and more
Orchestrate complex workflows across tools like Wiz, Sweet Security, CrowdStrike, SentinelOne, and AWS
Scale effortlessly across cloud-native applications, multi-cloud, or hybrid environments without code or configuration overhead

Cloud-Native Security Automation in Action: Torq + Wiz

To see a cloud-native security automation framework in action, look no further than the powerful partnership between Torq and Wiz. These two platforms combine seamlessly to provide an end-to-end automation solution purpose-built for securing today’s sprawling cloud environments.

Wiz delivers deep visibility into cloud risk — surfacing everything from misconfigurations to toxic combinations of exposure and permissions. Torq turns that insight into instant, intelligent action. Together, they automate everything from detection to remediation, improving cloud security posture, reducing attack surface, and accelerating response without burdening analysts.

With Torq and Wiz, teams can automatically remediate issues like:

Publicly exposed AWS S3 buckets containing sensitive data: Torq receives alerts from Wiz, validates the bucket’s status, and updates access policies automatically, or routes the issue for human-in-the-loop approval via Slack or Jira.
Unencrypted cloud storage: When Wiz detects a storage bucket with encryption disabled, Torq prompts the bucket owner to enable it or does so automatically, ensuring data in the secure cloud stays secure.
Open SSH access on EC2 instances: Torq instantly correlates alerts, confirms owner identity, and applies remediation by removing the risky access rule or prompting the appropriate user to take action.

Together, Wiz Defend and Torq HyperSOC™ form a powerful defense loop for cloud-native security: Wiz delivers deep visibility and precision threat detection across dynamic environments, while Torq transforms those insights into immediate, intelligent, and fully automated response. It’s the fastest path from detection to resolution, built for the demands of modern multi-cloud, serverless, and container-driven architectures.

Ultimately, Torq and Wiz help organizations move beyond traditional security bottlenecks and into a future of truly autonomous, scalable, and resilient cloud-native operations. They are a cornerstone for any organization looking to build or strengthen a modern cloud-native application security automation framework. Watch the demo here.

Don’t Let Manual Security Hold You Back

Cloud-native environments demand cloud-native security. The only way to keep up with the speed of infrastructure — and the speed of attackers — is to automate everything that can be automated.

Go all in with Torq Hyperautomation.

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How Torq and Wiz Power End-to-End Cloud Threat Detection and Response

By Bob Boyle

June 24, 2025

6 Minute Read

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How Wiz Defend Alerts Flow into Torq

Modern cloud environments are dynamic and often opaque to traditional security tools. Wiz changes that by collecting and correlating rich telemetry across the entire cloud stack, not just from infrastructure and workloads, but from identities, repositories, runtime signals, and more.

What makes this powerful isn’t just the data itself — it’s how Wiz transforms that data into high-fidelity alerts that are seamlessly fed into Torq for immediate action.

How Wiz Finds and Detects Cloud Threats

Wiz begins by ingesting telemetry from multiple sources across your cloud footprint, including:

Cloud-native logs: AWS CloudTrail, S3 data events, Azure Diagnostic Logs, and GCP Audit Logs
Identity activity: Okta, cloud IAM policies, and role assumptions
DevOps and Kubernetes tools: GitHub, container registries, and CI/CD pipelines
Runtime sensors for visibility into container and serverless workload behavior

But rather than alerting on every anomalous signal or potentially malicious indicator, Wiz applies correlation logic that groups related signals into what it calls a Wiz Threat — a complete, narrative alert that reflects an unfolding cloud attack path.

Together, these detections are stitched into one high-confidence alert that captures both the technical indicators and the business risk, allowing SOC teams to move faster with greater certainty.

Prioritized, Correlated, and Automated Cloud Threat Detection

Each Wiz Threat is not just a set of log events — it’s a structured object that includes:

Detection metadata: source, time, cloud account, and service, region
Linked findings: secrets, misconfigurations, and vulnerabilities
Enriched security context: tags, asset owners, MITRE ATT&CK tactics, and runtime behavior
Calculated risk severity based on business impact and adversary activity

This comprehensive data is packaged and passed to Torq HyperSOC via webhook or API integration.

What Gets Sent to Torq

Threat name and summary
Affected cloud assets
Event timeline and sequence
MITRE ATT&CK classification
Associated user identities and network exposure
Recommendations from Wiz’s threat intelligence team

How Socrates Automates and Orchestrates the Cloud Threat Response

Once inside Torq, the Wiz Threat becomes a case, a centralized workspace where Torq’s AI SOC Analyst, Socrates, takes over. Here’s how the end-to-end workflow looks.

Step 1: The Wiz Alert Becomes a Torq Case

When the alert lands in Torq, a new case is created and populated with structured context from Wiz Defend. Analysts are immediately presented with a dynamic AI-generated case summary, which adapts in real-time as new signals, observables, or comments are added.

Step 2: Socrates Begins Enrichment and Investigation

With the case live, Socrates, Torq’s AI SOC Analyst, steps in as the first responder. Socrates parses the detection, extracts IPs, hashes, URLs, and related indicators, and enriches them using your chosen threat intelligence providers (e.g., VirusTotal, AlienVault, Recorded Future). Threat enrichment happens within seconds, and the insights are automatically written back into the case file.

Then, Socrates dynamically identifies asset owners based on tags, CMDB entries, or environment metadata — instantly resolving ownership questions that traditionally slow down response times in cloud environments.

Next, Socrates builds a response plan. Using the MITRE ATT&CK tactics mapped from the Wiz alert and a library of security procedures, it proposes a remediation workflow customized to the threat and environment, whether it’s privilege misuse, misconfigurations, or lateral movement attempts.

Step 3: Autonomous Action and Analyst Escalation (If Needed)

Now the case enters automated execution. Socrates follows a runbook tailored to the case type, executing actions such as:

Collecting additional context from Wiz, AWS, and container workloads
Mapping and enriching security groups and cloud configurations
Identifying blast radius and lateral exposure for potential data exfiltration
Capturing a forensic memory dump of the asset to AWS S3
Notifying asset owners and cloud security teams via Slack or Jira
Removing public IP associations from exposed assets
Tagging the case with relevant MITRE ATT&CK TTPs

For cloud threats meeting certain criteria, Socrates can auto-remediate the incident entirely, containing the issue before a human even sees the alert. For more critical threats, the case is escalated to a human analyst with full context, including recommended next steps and suggested actions.

Step 4: Automatic Post-Incident Reporting

Once the threat has been handled, Socrates generates a full post-incident report that includes:

A summary of the detection and context
Enrichment and investigation details
The full remediation timeline
Root cause analysis of vulnerabilities or misconfigurations
Blast radius insights
Analyst performance scoring (if applicable)
Recommendations for continued improvement of cloud security posture

This report is stored as a PDF attachment to the case and accessible as a structured note, ready for audits, compliance, and continuous SOC training.

As the final touch, Torq automatically tags the case with MITRE ATT&CK TTPs used in the attack. This enables teams to build a MITRE ATT&CK heatmap across Wiz, Torq, and other detection sources, giving CISOs and threat hunters strategic visibility into adversary behavior across cloud and hybrid infrastructure.

Why Torq is the Definitive Automation Tool for Your Wiz Environment

Torq is uniquely built to provide the critical automation layer needed to bridge detection to action with unparalleled efficiency and accuracy. Unlike generic automation tools or manual scripting, Torq understands Wiz alerts natively. As soon as Wiz identifies a high-confidence threat, Torq’s built-in workflows are triggered automatically without extra scripting, manual integrations, or complicated setup.

With Torq, Wiz Defend customers experience immediate threat containment asSocrates enriches alerts, performs investigations, and resolves threats independently. This fully autonomous approach significantly reduces MTTR and frees your analysts to focus on complex scenarios and overall SOC strategy.

Torq doesn’t just enhance Wiz cloud alerts — it completes them.

Wiz and Torq: Your Ultimate Cheat Code for Cloud Security Operations

Cloud threat detection is just half the battle. Together, Wiz and Torq close the loop by coupling high-fidelity detections with instant, automated, and intelligent response. By bridging the gap between detection and action, security teams can finally stay ahead of rapidly evolving cloud threats, reduce alert fatigue, and accelerate remediation.

The integration of Wiz Defend’s rich, correlated telemetry with Torq HyperSOC’s autonomous threat handling isn’t just a solution — it’s your SOC team’s ultimate cheat code.

See Wiz Defend and Torq HyperSOC in action together.

The Best SOC Tools in 2025: Legacy vs Modern Automation

By Torq

June 20, 2025

9 Minute Read

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

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

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

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

What is a SOC Tool?

SOC Tools

SOC tools are technologies designed to help security teams detect, investigate, and respond to threats. They support incident resolution by collecting and analyzing data across IT and cloud ecosystems. Each tool plays a vital role in the SOC technology stack.

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

5 Core Capabilities of Security Operations Center Tools

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

1. Continuous SOC Monitoring

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

2. Log Collection and Analysis

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

3. Threat Detection

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

4. Incident Response

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

5. Automation

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

The Top 10 SOC Tools in 2025

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

1. Log Collection and Management

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

2. Security Information and Event Management (SIEM)

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

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

3. Vulnerability Management

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

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

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

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

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

5. Email Security

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

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

6. Threat Hunting

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

7. Threat Intelligence

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

8. Cloud Security Posture Management (CSPM)

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

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

9. Identity and Access Management (IAM)

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

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

10. Automation

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

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

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

How Automation Transforms SOC Tools

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

Faster detection and response: Automation drastically reduces the time it takes to identify, investigate, and respond to security incidents. What once took hours or days now happens in seconds, minimizing dwell time and damage.
Increased SOC analyst efficiency: With Tier-1 alerts automatically triaged (and often auto-remediated) and routine tasks offloaded to automated workflows, SOC analysts can handle a higher volume of cases without burnout. Teams get more done with fewer resources, reducing the need to scale headcount just to keep up.
Effortless scalability: As threats grow in number and complexity, automation allows SOC analysts to keep pace without compromising performance. Whether your environment is expanding across clouds or adding new tools, automation scales effortlessly alongside.
Smarter use of human talent: SOC analysts are too valuable to be bogged down by repetitive tasks. Automation frees them to focus on high-impact investigations, strategic decision-making, and threat hunting, where human judgment and creativity matter most.
Reduction in alerts: Automated triage filters out low-priority noise, enriching and escalating only the alerts requiring attention. SOC analysts stay focused on real threats instead of drowning in false positives.

How Torq Hyperautomation Transforms the SOC

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

Here’s how Torq makes it happen.

Seamless Integration with Your Entire Security Stack

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

AI Agents That Work Like SOC Analysts

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

Natural Language-Driven Automation

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

Hyperautomation at Enterprise Scale

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

Built to Flex with Your Needs

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

Hyperautomation is the SOC Tool You Need Today

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

AI-driven Hyperautomation is that solution.

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

Get the SOC tool you need.

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The Top 3 Hyperautomation Use Cases for Torq POCs

By Torq

June 16, 2025

5 Minute Read

Many organizations come to Torq when they’ve hit a wall with their legacy SOAR platform. The migration to Torq isn’t just a technology upgrade — it’s an operational overhaul. With Torq, enterprises have replaced hundreds of rigid playbooks in weeks, dramatically reduced time-to-value, and unlocked capabilities that legacy SOAR could never support.

The move to Torq is faster and smoother than you think,thanks to our intuitive workflow design, low-code flexibility, and hands-on migration support. If you’re considering a demo or a proof of concept (POC), these are the top three Hyperautomation use cases we’d start with — the ones that deliver instant value and set your implementation up for long-term success.

Hyperautomation: A SOC Must-Have

Hyperautomation is the current era of security operations — where every repetitive task, manual process, and alert-handling bottleneck gets replaced by scalable, intelligent automation. Unlike traditional SOAR, AI-driven Hyperautomation is agile, dynamic, and driven by real-time context.

In the SOC, this means:

Faster threat response: Alerts are triaged, investigated, and remediated automatically across EDR, IAM, email, and cloud systems.
Massive analyst efficiency gains: Your team spends less time on tedious Tier-1 tasks and more time threat hunting and improving security posture.
Lower operational costs: Hyperautomation eliminates tool sprawl, reduces alert fatigue, and streamlines workflows, making the SOC leaner and more effective.
Scalability: Whether it’s 10 alerts or 10,000, Hyperautomation responds at machine speed.
Immediate ROI: The impact is measurable within days: reduced MTTR, faster MTTD, and happier analysts.

Torq’s Hyperautomation platform makes it easy to deploy, customize, and scale automation across your environment without writing a single line of code.

1. Endpoint Detection and Response

EDR is one of the most common Hyperautomation use cases, and for good reason. Endpoints are often the first line of defense when threats bypass preventative controls. But while EDR platforms like SentinelOne, CrowdStrike, and Microsoft Defender continuously surface alerts, they still rely on analysts for response.

That’s where Torq comes in. By integrating your EDR tools with Torq Hyperautomation, you can:

Instantly isolate compromised hosts and cut off lateral movement
Trigger targeted endpoint scans, triage workflows, and auto-remediation actions
Correlate EDR alerts with identity, network, and threat intel context for smarter decision-making
Auto-generate detailed incident reports with full observability into root cause and system impact

EDR Hyperautomation in Action: Torq and SentinelOne

When SentinelOne detects a threat, it sends event data via webhook to Torq, which triggers a predefined workflow. Socrates, Torq’s AI SOC Analyst, evaluates the threat, retrieves asset details from CMDB, checks for correlated user activity, and executes the appropriate response. The compromised host is quarantined, impacted credentials are flagged, and a full report is auto-generated for the analyst.

Automating EDR response is one of the most powerful first moves in any Hyperautomation POC. It delivers instant value, dramatically reduces MTTR, and frees analysts from constantly chasing endpoint alerts across multiple consoles.

2. Email Security

Phishing remains the #1 attack vector — and one of the most common triggers for Tier-1 security alerts. These alerts are high-volume, high-noise, and easy to miss. Automating phishing response with Torq during a POC delivers fast, visible results that eliminate manual overhead.

Torq integrates with various email security platforms, including Microsoft 365, Gmail, Proofpoint, VirusTotal, Mimecast, Abnormal Security, Barracuda, and Cisco.

With Torq, you can:

Auto-quarantine suspicious emails
Lock user inboxes and enforce password resets for potentially compromised accounts
Extract, analyze, and enrich email artifacts like headers, links, and attachments
Launch phishing investigation playbooks

This automation dramatically reduces the mean time to remediate (MTTR) phishing attempts, and it’s one of the clearest, most repeatable use cases for proving the power of Hyperautomation.

Email Security Hyperautomation in Action: Torq and VirusTotal

Torq integrates with VirusTotal to enhance email threat analysis. A Torq workflow can monitor a designated mailbox (such as Outlook or Gmail), extract URLs, attachments, and header IPs from each message, and submit them to VirusTotal for threat scoring. Based on the results, Torq automatically categorizes the message as malicious, suspicious, or clean, updating labels, alerting stakeholders, and kicking off remediation.

What once took hours (or days) is reduced to seconds. Analysts can investigate real threats instead of triaging false positives. And you immediately prove Hyperautomation’s impact on everyday SOC volume.

3. Identity and Access Management (IAM)

Identity is the new perimeter. Many breaches are caused by compromised credentials, whether through phishing, MFA fatigue, or social engineering. Automating IAM workflows early in your POC helps you immediately reduce access-related risk.

Torq integrates with leading IAM providers, including Okta, Microsoft Entra ID, Ping Identity, Duo Security, JumpCloud, CyberArk, and Auth0.

Integrate Torq with your IAM, and you can:

Detect and respond to suspicious login behavior
Auto-disable accounts after anomalous activity
Automate user provisioning and de-provisioning
Trigger MFA resets and log analysis workflows

IAM Hyperautomation in Action: Torq and Okta

Here’s one way Torq and Okta work together: This workflow monitors for new MFA methods added in Okta, a common sign of account takeover. It checks the source IP with VirusTotal, asks the user to confirm the action, and if suspicious, auto-opens a Jira ticket, spins up a Slack message, and suspends the account if needed.

Integrating IAM with Torq at the start of your implementation reduces security risk and enhances operational efficiency by replacing slow, manual processes with scalable automation.

Fast, Scalable Results… In Days

These three use cases — EDR, email, and identity — are high-impact, high-speed proof of what AI-driven Hyperautomation can do for your SOC.

Our customers routinely:

Cut MTTR and MTTD across critical workflows
Eliminate repetitive Tier-1 analyst work
Prove ROI in days, not weeks

Start with what matters most. Let Torq show you how fast modern SOC can move.

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Squish the Phish: 6 Automated Phishing Response Strategies

By Torq

June 12, 2025

11 Minute Read

And rather than getting better at recognizing phishing emails, humans are seemingly getting worse, in part due to the increasing phishing sophistication and customization at scale that GenAI offers. According to Verizon’s 2024 Data Breach Investigations Report, people are falling for phishing attacks at an alarming rate, taking a median of just 21 seconds to click a malicious link and another 28 seconds to enter their personal data.

Of course, part of the solution lies in educating users to recognize and report phishing. But user education only goes so far — on average, only 3% of users report phishing emails. Strong anti-phishing education may increase that number, but you’re still fighting an uphill battle if you rely on end users as your primary means of defense against phishing.

Instead, modern security teams are turning to automated phishing response. By using security automation to detect and respond to phishing attempts, security teams can stop the majority of phishing messages before they ever reach end users.

Manual Phishing Triage: A Losing Battle for SOC Teams

Manual phishing investigation and response is a relentless, high-volume drain on SOCs. When a potentially malicious email is flagged — either by a security tool or a user — the clock starts ticking.

The analyst must first deconstruct the suspicious email: digging into email headers, verifying sender addresses, analyzing the message body for suspicious language, and identifying any potential Indicators of Compromise (IOCs), such as embedded links or file attachments.
Each potential IOC must then be manually validated. This initiates a tedious cycle of “swivel-chair” analysis, where the analyst copies and pastes information — IP addresses, domains, file hashes, etc. — out of the email and into various threat intelligence platforms and security tools. Juggling these multiple browser tabs and windows is essential to determine if an artifact is truly malicious, but each copy-paste and window hop wastes time while the risk of human error increases.
And this is all before remediation even starts. Once the threat is confirmed, the analyst must then take action to block the sender, initiate a search to delete the email from all other inboxes, and respond to the user who reported it.

This monotonous, repetitive process is not just slow — it’s dangerously error-prone. A single missed detail or misinterpretation can be the difference between a blocked threat and a full-blown incident.

Manual phishing triage and response workflows can take tens of minutes to over an hour for a single case. Multiply that by hundreds of daily alerts, and the challenge of keeping up becomes too big to ignore. However, with anti-phishing automation, all of the grind of phishing triage, investigation, and remediation disappears.

What is Automated Phishing Response?

Anti-phishing automation refers to technology that autonomously investigates, triages, and neutralizes suspected phishing emails. It is designed to replace the slow, repetitive, error-prone grind of manual phishing defense with a consistent machine-speed response that immediately isolates compromised inboxes, revokes access to malicious emails, blocks phishing URLs, and notifies users.

6 Hyperautomated Phishing Response Strategies and Tactics

Torq Hyperautomation™ integrates with several key partners to help organizations prevent and mitigate phishing attacks and avoid costly data breaches — which cost organizations an estimated $4.88 million in 2024. Below are six strategies for leveraging Hyperautomation to fight phishing across your entire security environment.

1. Perimeter Defense: Hardening the Email Gateway

Your first line of automated defense is securing the primary phishing entry point: the email inbox. The goal is to identify and block as many malicious emails as possible before they ever reach a user.

Torq partners with Secure Email Gateway (SEG) providers to enhance their detection accuracy and response by correlating data across leading SEG solutions like Abnormal Security, Microsoft, Proofpoint, Mimecast, and more. Torq then autonomously initiates remediation actions, such as removing malicious emails or adjusting email security controls.

Key tactics:

Filter messages based on multiple attributes: The days are long gone when simply scanning email for strings like “Nigerian prince” guaranteed that you’d catch the phishers. Simple keyword or domain name scanning won’t cut it. Effective anti-phishing automation evaluates every email based on multiple attributes — its content, the domain from which it originated, whether it contains an attachment, the type of attachment, and so on — to build a far more informed assessment than content analysis alone can provide.
Detonate attachments in sandboxes: For suspicious but unconfirmed email threats, automation can instantly “detonate” (i.e. download and open) attachments or links in a secure, isolated sandbox. By evaluating the content’s behavior in a safe environment, the system can detect anomalies or attack signatures that confirm the content is indeed malicious. At the same time, the original email remains quarantined from the user. Pending the results, the workflow can either safely release the back content to the user or block it definitively.
Block sender names and domains automatically: When a phishing attempt is confirmed, automation can instantly block the sender’s name and entire domain across the organization. This prevents subsequent waves of the attack from different accounts on the same infrastructure, disrupting the phisher’s campaign.

2. Identity and Access Control: Protecting Your People

Since credentials are the primary target of most phishing attacks, proactively protecting user identities is paramount. Torq does this by analyzing cloud-based user and entity behaviors to detect anomalies that could be indicative of phishing. And if a phishing attack does occur, Torq integrates with solutions, including Okta, Active Directory, JumpCloud, OneLogin, Ping, and Wiz, to prevent account takeover and limit an attacker’s access.

Key tactic:

Reset credentials automatically: Upon detecting a potential phishing compromise, automation should immediately trigger a security workflow to reset login credentials for impacted users. This includes logging the user out of all active sessions and forcing a password reset to instantly invalidate any stolen credentials.

3. Endpoint Security: Containing the Impact

If a malicious email makes it through and a user clicks a link or opens an attachment, the battle shifts to the endpoint (e.g. the user’s laptop or phone). Working with EDR providers like Crowdstrike, SentinelOne, Microsoft, and others, Torq can correlate endpoint data for a holistic view of a phishing attack’s scope and impact, then rapidly take action to contain and remediate any compromise on the device itself.

Key tactic:

Scan and quarantine affected endpoints automatically: The moment a user is linked to a confirmed phishing attack, automation should trigger the EDR solution to perform an immediate scan of their devices. If malware is found, the endpoint can be automatically quarantined from the network to prevent lateral movement while the threat is removed.

4. The Human Element: Empowering Users as a Line of Defense

Your employees are both a target and a potential ally. Torq’s chatbot integrations with communication tools like Slack, Microsoft Teams, Discord, and email make it quick and easy for users to report threats, providing them with instant feedback and education, and turning users into an active part of your security posture.

Key tactics:

Use chatbots for phishing reporting: Integrating chatbots into communication tools like Slack or Microsoft Teams gives users a simple, immediate way to report suspicious emails. These bots can then kick off automated security workflows based on the report, such as resetting passwords, revoking access, or initiating scans for malware. Chatbots can also provide educational resources and coaching to users on how to avoid phishing and improve their cybersecurity awareness.
Triage user-reported emails automatically: When a user reports a suspected phishing email, automation takes over. It can instantly extract key indicators (URLs, file hashes, headers), analyze them against threat intelligence, and provide the user with immediate feedback, confirming if the email was malicious and has been handled, or if it was safe.

5. Data Protection & Incident Response: Minimizing the Damage

When a breach occurs from a phishing email, the strategy shifts to understanding and minimizing the damage. Automation is critical for rapidly assessing the scope and scale of data loss and ensuring compliance with regulatory requirements for notifications and reporting. Torq partners with providers like Microsoft, Crowdstrike, Varonis, and Symantec to automate these two important pieces of the phishing puzzle.

6. Continuous Improvement: Learning from Every Attack

A strong defense is one that constantly learns and adapts. Understanding the metrics after the fact can help prevent a phishing attack in the future. Torq partners with SIEM, SEG, and EDR providers to use data from past incidents to refine and improve your automated workflows and overall security posture.

Key tactic:

Quantify improvements with automated metrics: Use automation to analyze response times, workflow effectiveness, and incident severity. By leveraging AI in the SOC to automatically categorize incidents and create cases, you can ensure critical threats receive priority and gather insights to continually harden your defenses against future attacks.

Example Automated Phishing Alert Analysis Workflow in Torq

This Torq Hyperautomation workflow automates the initial triage of a reported phishing email. It instantly extracts and aggregates key artifacts like URLs, file hashes, and headers from Outlook messages and attaches to create a structured data set for deeper analysis, following these steps:

Alert trigger: The process begins the moment a potential phishing alert is received from a source like Microsoft 365.
Parallel data extraction: Torq immediately executes multiple tasks in parallel to deconstruct the email:
- URLs: It extracts all unique URLs from the email’s body and within any attachments.
- Attachments: It processes all file attachments to retrieve their details and corresponding file hashes.
- Headers: It retrieves the full message headers using the Microsoft Graph API.
Threat Validation: Torq then leverages integrations with various threat intelligence feeds, such as VirusTotal, to determine if the URLs, attachments, or information pulled from the email headers are flagged as malicious or benign. This helps quickly weed out false positives, or confirms the alert as a true malicious threat before a security case is even created.
Data consolidation and output: All extracted artifacts (URLs, file hashes, and headers) are automatically collected, combined, and formatted into a single, structured output, ensuring all necessary data is ready for the next step.
Initiate case management: If the alert is confirmed as malicious through third-party validation (or reaches a designated suspicious threshold), the structured output is then used to automatically create a new security case or escalate an existing incident with similar IOCs, often triggering a nested workflow for full case management and remediation.

Case Study: Lennar Cuts Phishing Resolution from Hours to Minutes

The security team at Lennar, one of the nation’s leading homebuilders, was swamped by phishing. They spent “hours and hours” remediating phishing attacks due to manual processes and the lack of flexibility and integrations in their existing XSOAR solution.

After switching to Torq Hyperautomation, the time it took Lennar to resolve a phishing attack dropped from hours to just minutes. This freed up their security experts to focus on more important work, like hunting for major threats.

Before we had Torq, we would do a lot of manual phishing remediation, which was a big time-taker. We would spend hours and hours. With Torq, we’ve significantly reduced the amount of time spent on phishing, which allowed us to further refine our other tools and alerts.
Daniel Gross, Senior Operations Analyst, Lennar

Read the full case study >

Win the Phishing War with Automated Phishing Response

Phishers are only going to get better at what they do, especially as they become more sophisticated in their use of AI. The only way for today’s stretched-thin security teams to keep up is with automated phishing response.

Anti-phishing automation eliminates the noise from low-level phishing alerts and frees up analysts to focus on more critical threats. It also enables immediate, consistent, and accurate phishing incident response, reducing human error and minimizing the potential impact of a breach.

A truly effective automated phishing defense relies on the ability to connect and orchestrate every tool in your security stack. With Torq’s limitless integrations, you can automate any phishing tool and process, creating a unified and automated response to neutralize phishing threats across your entire environment.

Want to make your SOC more efficient across the board? Get Torq’s Field CISO’s guide covering practical advice to overcome rising threats, lean teams, and budget scrutiny.

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Contents

The Evolution from SDLC to SSDLC

The Importance of Integrating SSDLC into Modern Development

Where Legacy SOAR Fails: Lack of SSDLC Integration

How Torq Hyperautomation Integrates SSDLC by Design

Built-in SSDLC Framework

Automated Testing and Continuous Validation

Environment Segmentation: Development, Staging, and Production

Agile Workflow Development with Enhanced Security

Hyperautomation is Essential for SSDLC

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Level Up Your SOC: Best Practices to Stay Sharp and Secure

5 Most Common SOC Challenges

1. Alert Fatigue

2. Tool Overload

3. Manual Processes

4. Talent Shortage

5. Scalability Issues

6. The Ransomware Time-Bomb

7 Security Operation Center Best Practices

1. Build a Strong Foundation with the Right People and Processes

2. Prioritize Threat Detection and Response to Your Business Needs

3. Automate the Mundane, Focus on the Critical

4. Embrace Continuous Improvement

5. Measure Everything

6. Be Strategic About AI

7. Consolidate and Optimize

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