To stay ahead of today’s threats, you must do more than keep pace — you need to equip your team with tools that enable smarter, faster responses. For SOC analysts, runbooks in case management systems are essential guides for handling security alerts step-by-step. The prospect of automating these runbooks with AI is enticing, promising to streamline daily operations and free up time for more critical tasks.

However, some are rightfully skeptical. They worry that AI automation could introduce unexpected issues without careful planning and collaboration, potentially hindering productivity and increasing risk. This blog explores how collaborating with AI during planning and setting AI guardrails can enhance predictability, transparency, and trust in AI automation.

The Importance of Runbooks in Security Operations

Runbooks are structured, step-by-step guides enabling SOC analysts to respond to security incidents consistently and accurately. They are particularly crucial for Tier 1 analysts, who often serve as the first line of defense against a high volume of alerts. 

These runbooks provide clear instructions for the following:

• Triaging alerts
• Investigating potential threats
• Determining when to escalate issues

By standardizing responses, runbooks reduce human error and ensure efficient handling of all incidents, even in high-pressure situations. Automating runbooks with AI presents an appealing option for scaling operations, accelerating repetitive tasks, and allowing analysts to focus on more complex, high-stakes cases.

The Need for AI Guardrails in Runbook Automation

While automating runbooks with AI is a game-changer, granting AI too much freedom can quickly backfire. Most runbooks are designed with human readers in mind, presenting step-by-step guides that make sense to analysts but can be confusing for AI. 

When left to interpret these text-based instructions independently, AI might:

• Misinterpret steps
• Make unexpected decisions
• Produce unintended results

AI can become unpredictable without a structured plan and human alignment, risking accuracy and eroding your team’s trust in automation. A collaborative planning phase to ensure AI guardrails is crucial as it provides SOC analysts visibility into how the AI “interprets” the runbook and plans to automate it. This transparency allows analysts to refine the AI’s approach, ensuring the plan aligns with real-world needs before execution begins.

Collaborative Planning: Aligning AI and Analysts

To understand the value of Torq’s approach to runbook automation, let’s consider a common SOC runbook for investigating phishing reports. Such runbooks guide analysts through tasks like checking attachments, analyzing email headers, and escalating incidents when certain conditions are met.

Automating these tasks with AI is more complex than simply running through the steps. Many runbooks are written for human understanding and involve actions that may be ambiguous or beyond direct AI capabilities. Torq’s plan-and-execute approach addresses this challenge by separating the process into distinct planning and execution phases, giving analysts more control and visibility over the AI’s actions.

1. Planning Phase

In this phase, the AI:

1. Reads through the runbook
2. Converts instructions into a structured, transparent plan
3. Break down each instruction into clear, atomic steps
4. Identifies steps it can automate and those requiring human intervention
5. Highlights gaps where it lacks necessary tools or access

This transparency allows SOC analysts to modify the plan, choosing where the AI should pause for guidance or where additional human-defined workflows are needed. In scenarios where full automation isn’t feasible, such as in highly secure or restricted environments, this collaborative planning ensures that the AI aligns closely with human intent and avoids unnecessary errors.

2. Execution Phase

Once the analyst reviews and approves the plan, execution follows this carefully vetted blueprint. 

This approach:

• Strips ambiguity and indeterminism from the execution
• Provides transparency and reliability
• Fosters trust in the automation process

Analysts can be confident that AI will follow the exact plan, making the automation more efficient and dependable without sacrificing control or accuracy.

To reinforce the concept further, let’s consider how Socrates, our AI SOC analyst, would function without the ability to add tags while focusing on his communication skills and resistance to AI hallucination.

Socrates, even without the capability to add tags, would still demonstrate its effectiveness in several ways:

Clear communication of limitations: When faced with a task it cannot perform, such as adding a tag, Socrates would explicitly state its limitations. For example, it might say, “I’m unable to add the tag ‘Malicious IOC’ as I don’t have that capability. This step requires human intervention.”

Requesting user input: Socrates pauses the process and asks for user input when the necessary tools or permissions are lacking. This demonstrates its ability to recognize boundaries and seek assistance when needed.

Proceeding with available tools: For steps where Socrates has the required capabilities, it would continue to execute them efficiently. These actions would be marked as completed or “green” in the process.

Detailed explanations: Throughout its analysis and decision-making process, Socrates provides clear, thorough explanations of his reasoning, helping analysts understand its thought process even when it couldn’t perform specific actions.

Suggesting alternatives: When unable to perform a specific action, Socrates might suggest alternative approaches or provide information that could help the human analyst complete the task manually.

Focusing on these aspects can highlight Socrates’ ability to communicate effectively, recognize its own limitations, and resist AI hallucination by not claiming capabilities it doesn’t have. This approach emphasizes AI’s role as a collaborative tool that enhances human decision-making in the SOC rather than attempting to replace human judgment entirely. See what this looks like below:

Strengthening Security Through Transparent AI Collaboration

Trust and transparency are fundamental to building an effective security strategy in today’s rapidly evolving threat landscape. Torq’s AI capabilities prioritize collaboration and clarity, transforming how SOC teams handle automation. By structuring automation as a two-phase process — planning and execution — Torq ensures that AI usage is efficient, bounded by AI guardrails, and aligned with human oversight and intent.

This collaborative approach allows human SOC analysts to:

• Maintain control over automated processes
• Reduce uncertainty in AI actions
• Trust in the predictability and reliability of AI-driven tasks

Fostering a security environment where AI and human expertise work together can strengthen organizations’ SOC capabilities and enhance overall security posture. See Torq’s AI in action — schedule a demo.

Learn more about building trust in AI and how structured, evidence-backed summaries generated by AI enable seamless SOC shift transfers.

GigaOm recognizes Torq as the only Hyperautomation vendor capable of delivering true autonomy to the SOC without vendor lock-in.

For years, security teams have grappled with relentless alert fatigue and burnout, exacerbated by disjointed security tools like SIEMs and SOARs. Legacy security vendors have tried to address this by cramming disconnected solutions into “all-encompassing” SecOps platforms, and many have now falsely tacked on “autonomous SOC” and “Hyperautomation” claims to their products. 

Security teams can’t afford to invest in another expensive, hard-to-maintain platform that doesn’t deliver on its promise of autonomy and automation — so where should they turn?

GigaOm’s newly-released Autonomous SOC Radar Report confirms: Torq Hyperautomation is the clear frontrunner in realizing the autonomous SOC vision and delivering the autonomy SOC teams have long been promised.

What is an Autonomous Security Operations Center (SOC)?

While legacy vendors now claim to offer SOC autonomy, true autonomy isn’t achieved by locking users into rigid, all-in-one platforms. These legacy solutions contributed to the very burnout problem that led to a talent shortage of 4 million security professionals. Their proposed solution? Dump more cash into the same outdated platforms.

A genuinely autonomous SOC leverages advanced automation and AI to handle manual and routine security tasks, accelerating response times, enhancing threat management, and ultimately safeguarding the well-being of SOC analysts. The most efficient path to this goal involves breaking down silos between security tools, enabling seamless communication and streamlined security operations across a modern, best-of-breed tech stack.

Simply put, it isn’t possible to achieve an autonomous SOC without automation. Torq is the only vendor solely dedicated to empowering security teams to automate more, faster.

“Torq is the only vendor positioned in the Innovation/Feature Play quadrant, as it is the only non-SIEM solution featured in the report, which also explains its differentiated position.“

– Andrew Green, Research Analyst for Networking & Security, GigaOm

Torq is the Only Hyperautomation Vendor Listed in GigaOm’s Autonomous SOC Report

Hyperautomation is the next evolution in scalable autonomous security operations. By definition, Hyperautomation requires enterprise-grade scalability, availability, and connectivity — essentially solving the challenges caused by these large legacy vendors. While the idea of the autonomous SOC is centered around the ability to automate everything, similarly, Hyperautomation is built on a foundational ability to integrate with anything. 

Torq’s recognition as the only Hyperautomation vendor in GigaOm’s Autonomous SOC Radar report underscores that unique position in the security operations landscape. 

Frameworks coming into law, such as DORA in the EU and CCSPA in Canada, spotlight the need for vendor diversity to reduce single points of failure and enable redundancy. Torq is the only autonomous SOC vendor enabling organizations to seamlessly integrate best-of-breed solutions — free from vendor lock-in.

Torq combines this vendor-agnostic approach with advanced technologies like purpose-built AI and Hyperautomation, engineered to create intelligent end-to-end solutions for security processes.

And GigaOm isn’t alone in recognizing Torq as the leader of autonomous SOC — industry analysts across the board are taking note.

“Torq is the first solution we’ve seen that effectively enables SOC professionals to mitigate issues including alert fatigue, false positives, staff burnout, and attrition. We’re impressed by how its AI augmentation capabilities empower these staff members to be much more proactive about fortifying the security perimeter.”

– Chris Kissel, Vice President, Security & Trust Products, IDC Research

By choosing Torq, organizations are embracing the future of security operations, as recognized by industry experts — with an approach that’s creating a more agile, effective, and strategic security operation.

Leveraging AI to Drive SOC Autonomy 

Torq integrates purpose-built AI capabilities such as generative AI and large language models (LLMs) to evolve SOC operations fundamentally and deliver on the promise of an autonomous SOC. This enables security teams to focus their efforts on proactive security measures, resulting in greater efficiency and accuracy in decision-making processes.

“80% of our security alerts are assisted and accelerated by Torq workflows. To analyze, enrich, and also autonomously respond to alerts is a paradigm shift that brings unprecedented efficiencies.″

– Joshua Blackwater, Deputy CISO, SentinelOne

Socrates, Torq’s AI SOC Analyst, exemplifies this by automating 90% of Tier-1 tasks through AI-powered triage and investigation. Socrates accelerates analyst response times by summarizing case data and providing immediate insights. It also automates 95% of security cases from investigation to response, intelligently assigning critical cases to human analysts when necessary. This augmentation empowers analysts at all levels to achieve machine-speed response times while supporting ongoing learning and skills development. 

The Sole Winner: Torq’s Unique Position

GigaOm’s report highlights the critical importance of AI-powered autonomous SOCs. As the sole Hyperautomation solution free from platform constraints, Torq provides the agility and innovation necessary for modernizing security operations in an increasingly demanding environment. 

For organizations seeking to enhance their SOC capabilities without sacrificing flexibility or risking vendor lock-in, Torq offers the only comprehensive solution designed to meet these challenges head-on. Schedule a demo to see it in action.