AI Hyperautomation Security Automation 101

No Blind Spots: Hyperautomate Your Attack Surface Management

By Torq

June 10, 2025

11 Minute Read

Modern enterprises face an increasingly complex and dynamic digital environment, making effective attack surface management (ASM) more critical than ever. The sprawling nature of digital assets, rapid cloud adoption, and evolving threat landscape mean new vulnerabilities and exposures continually emerge. Manual processes and legacy tools can’t keep pace, leaving security teams struggling to track and address threats proactively.

Torq Hyperautomation™ transforms attack surface management by continuously detecting, contextualizing, and remediating threats, ensuring your organization remains ahead of adversaries.

What is Attack Surface Management (ASM)?

An attack surface refers to all the potential entry points (physical, digital, and human) an attacker can exploit to gain access to an organization’s system or data. The larger the attack surface, the higher the exposure to threats.

Attack Surface Management (ASM) is a proactive cybersecurity strategy designed to continuously discover, monitor, assess, and reduce potential exposure across an organization’s entire digital footprint. It focuses on identifying all entry points an attacker could exploit — known and unknown — and mitigating risks before they can be leveraged.

An effective ASM program includes:

Continuous discovery of exposed assets: ASM tools scan all environments for internet-facing and internal assets — cloud services, domains, APIs, SaaS platforms, shadow IT, and forgotten infrastructure — and make persistent discoveries to account for dynamic infrastructure changes, workloads, and rapid application development cycles.
Monitoring for vulnerabilities and misconfigurations: Vulnerability management is fundamental to attack surface management. Once assets are discovered, ASM monitors them for known vulnerabilities, insecure configurations, unpatched systems, open ports, and any anomalies that could be exploited. It acts as an early warning system that catches issues before attackers do.
Prioritization of risks: Not all exposures carry equal weight. ASM contextualizes alerts with business relevance, threat intelligence, and asset sensitivity to help security teams focus on what matters most. This triage process ensures critical issues are addressed quickly, while noise is minimized.
Streamlined response: Effective ASM initiates action. By integrating with ticketing systems, IAM tools, cloud consoles, and security automation platforms like Torq, ASM can automatically remediate issues or trigger workflows for immediate response, improving speed and efficiency.

Challenges of Traditional Attack Surface Management

Several challenges complicate traditional ASM approaches:

Shadow IT and SaaS sprawl: Rapid SaaS adoption and shadow IT create blind spots, leaving assets untracked and unmanaged.
Ephemeral cloud infrastructure: Cloud environments constantly evolve, creating fleeting assets that legacy ASM tools struggle to monitor effectively.
Legacy tools miss context: Traditional tools lack the context to prioritize threats effectively, causing delays and inefficiencies.
Alert overload stalls response: High volumes of security alerts overwhelm analysts, leading to alert fatigue and slower incident responses.

3 Keys to Effective ASM

Attack surfaces are dynamic, growing, and constantly shifting. Manual methods can’t keep up. That’s why modern ASM must be:

Automated: Detect and respond without relying on human intervention.
Continuous: Monitor in real time, not just during scheduled audits.
Integrated: Feed into your broader security operations stack for full context and control.

This is exactly where security Hyperautomation can help. Torq Hyperautomation transforms ASM from a slow, manual, and reactive task into a real-time, intelligent, and scalable security practice by automating every step, from asset discovery to remediation. With Torq, security teams gain continuous visibility, instant context, and automated action across the entire attack surface — external, internal, and everything in between.

How Automated Attack Surface Management Works

Traditional attack surface management tools often stop at discovery. Torq’s Hyperautomation platform goes several steps further, turning visibility into action and action into measurable impact. It’s not just about knowing your risks; it’s about resolving them automatically, intelligently, and at scale. Here’s how it works.

Asset Discovery

Torq continuously ingests data from across your infrastructure: cloud environments (AWS, Azure, GCP), SaaS platforms (Okta, GitHub), asset inventories, and external ASM tools like SentinelOne, Rapid7, or Qualys. Whether it’s a cloud workload, a shadow IT application, or an unmanaged endpoint, Torq ensures it’s identified and accounted for. The platform dynamically updates its asset map as your environment evolves, providing complete, real-time visibility across internal and external attack surfaces.

Exposure Monitoring

Once assets are discovered, Torq automatically monitors them for known vulnerabilities, insecure configurations, open ports, identity exposures, and other signs of risk. These checks run continuously — not periodically — ensuring that risks are detected as soon as they appear. Torq’s integration with leading vulnerability scanners, CSPM tools, and threat intelligence feeds enables rich, multidimensional analysis of exposures from both inside and outside the perimeter.

Contextual Alerting

Torq enhances every alert with contextual data that matters, like asset ownership, criticality, geographic location, user identity, and recent activity. This enrichment turns raw alerts into actionable intelligence. Instead of treating all alerts equally, Torq prioritizes them based on business risk, reducing alert fatigue and surfacing what truly needs attention. Analysts don’t just receive more information; they get the right information at the right time.

Automated Remediation

Once a threat is confirmed, Torq automatically executes response playbooks tailored to the incident type, asset profile, and organizational policy. These playbooks can:

Disable vulnerable cloud resources
Revoke compromised credentials
Trigger ticketing workflows in Jira or ServiceNow
Notify the responsible owners or escalate to human analysts
Re-run validation checks to confirm resolution

Every action is logged, auditable, and fully customizable, enabling high-assurance, closed-loop remediation with minimal manual intervention.

6 Benefits of Hyperautomated Attack Surface Management

Real-Time Visibility Across All Environments

Modern attack surfaces span hybrid clouds, SaaS tools, endpoints, and shadow infrastructure. Torq’s continuously scans your internal and external environment, providing a live, unified view of all known and unknown assets. This real-time visibility eliminates blind spots and ensures security teams can track changes the moment they occur, not days or weeks later. Enhanced visibility supports ongoing risk assessment efforts, allowing teams to prioritize vulnerabilities effectively.

Reduced Risk from Shadow IT and Misconfigurations

Unmanaged SaaS applications, orphaned cloud resources, and misconfigured systems are some of the riskiest parts of any attack surface. Torq’s ASM automations immediately flag these issues, correlate them with business context (e.g., owner, function, sensitivity), and kick off appropriate remediation workflows.

Fewer False Positives Thanks to Contextual Intelligence

False positives waste time, drain resources, and increase the likelihood of real threats slipping through. Torq solves this by enriching alerts with contextual data, such as asset criticality, historical behavior, identity attributes, and network topology. Analysts are presented with actionable intelligence instead of raw signals, reducing noise and sharpening focus on what matters most.

Dramatically Shorter Time to Detect and Respond

Automated ASM eliminates the latency of human-driven detection and triage. As soon as a vulnerability or suspicious exposure is detected, Torq initiates real-time enrichment and response. Whether isolating a misconfigured asset or revoking exposed credentials, remediation begins instantly, cutting Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR) by orders of magnitude.

Always-On Security Posture, Not Periodic Snapshots

Traditional ASM approaches rely on point-in-time scans that become outdated almost immediately. Torq replaces these snapshots with always-on automation, constantly monitoring your infrastructure, scanning for exposure, and triggering responses as needed. This 24/7 posture ensures your security surface evolves at the speed of your business.

Closed Loop from Detection to Resolution

Most ASM tools identify problems but leave resolution to manual processes. Torq completes the loop with intelligent, automated workflows that take action on validated exposures, revoking access, shutting down vulnerable services, notifying asset owners, and logging everything for audit and compliance. This full-cycle automation ensures exposures are resolved, verified, and documented.

Attack Surface Management Implementation: 4 Best Practices

1. Maintain continuous asset inventories: A complete, real-time view of your digital environment is foundational to effective ASM. Conduct continuous asset discovery and inventory updates to track new devices, applications, APIs, cloud resources, and shadow IT. This ensures your security team has an accurate understanding of all external-facing assets and can quickly spot unmanaged or vulnerable components before attackers do.

2. Integrate ASM with security stack: ASM should not operate in isolation. Connect it with your SIEM, vulnerability management, endpoint detection, and identity platforms to enable correlation and enriched context. This integration eliminates blind spots, improves visibility across environments, and empowers security teams to act on threats with unified intelligence.

3. Establish a strong vulnerability management process: Define formal, documented policies for identifying, prioritizing, and remediating vulnerabilities uncovered by ASM. Ensure roles, SLAs, and escalation paths are clearly defined. Integrate vulnerability data with your incident response workflows to speed up resolution and ensure no exposure goes unaddressed.

4. Automate notifications and remediation workflows: Reduce time-to-response and human error by implementing automated alerting and response playbooks. Use workflow automation to route findings to the right teams, trigger patching or access revocation, and track resolution status. Automation accelerates containment, improves coordination, and transforms ASM into a proactive defense layer.

How Torq Hyperautomation Powers End-to-End Attack Surface Management

Torq Hyperautomation integrates seamlessly into your security workflows:

Connects with external ASM tools (like Palo Alto, Crowdstrike, Microsoft) and internal asset inventories
Ingests and enriches alerts with detailed contextual data (identity, geography, asset ownership)l
Triggers automated playbooks for immediate remediation, revocation, alerting, or escalation
Reduces MTTR by integrating seamlessly with ticketing systems (Jira, ServiceNow), IAM solutions, and cloud providers
Continuously monitors post-remediation to confirm full resolution

Case Study: How Deepwatch Scaled Global Attack Surface Coverage with Torq Hyperautomation

For managed detection and response (MDR) providers like Deepwatch, delivering high-fidelity protection across a sprawling customer base means managing hundreds (if not thousands) of constantly shifting attack surfaces. But legacy SOAR platforms simply couldn’t scale with the speed, precision, or flexibility needed to keep up.

By adopting Torq Hyperautomation, Deepwatch transformed its security operations and delivered real-time visibility and response capabilities across global customer environments. The result: Over 90% automation of Tier 1 and Tier 2 alerts, faster onboarding for new clients, and dramatic reductions in both mean time to respond (MTTR) and operational overhead. “We’ve come from legacy SOAR to Hyperautomation, and what we’ve been able to build — the environment we now give to our analysts — I don’t think would have ever been achievable with legacy SOAR,” says Micah Donald, Sr. Director of Solutions Engineering, Deepwatch.

With Torq, Deepwatch automated the detection and remediation of exposed assets and vulnerabilities across internal and external attack surfaces without relying on slow manual scripting or disconnected tools. Torq’s low-code/no-code platform enabled Deepwatch analysts to build powerful workflows on the fly, integrate seamlessly with cloud infrastructure, and deliver precision response at scale.

From cloud complexity to shadow IT to ever-evolving customer demands, Deepwatch’s attack surface challenges mirror those of most enterprises today. Their success proves what’s possible when attack surface management is not just monitored but Hyperautomated.

“Torq helps customers get the biggest bang for their security buck, maximizing the value of their existing security investments.”.

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

Real Security Use Cases Powered by ASM Automation

Attack surface management isn’t a standalone task — it’s the foundation that powers broader security operations. With Torq Hyperautomation, ASM becomes the connective tissue for dozens of high-impact use cases across your SOC.

Identity and access management (IAM): Torq cross-references exposed assets with identity data from Okta, Azure AD, or HRIS systems. When orphaned accounts or overprivileged identities are discovered on exposed systems, Torq can automatically revoke access, enforce MFA, or trigger re-verification workflows without analyst intervention.

Cloud security posture management (CSPM): Combine CSPM tools like Wiz or Prisma Cloud with Torq’s Hyperautomation to turn misconfiguration alerts into real-time action. Whether it’s shutting down an open S3 bucket, quarantining an untagged instance, or enforcing encryption standards, Torq ensures posture risks are remediated, not just reported.

Threat intelligence operationalization: Torq integrates with threat intel platforms to correlate known IOCs (e.g., IPs, domains, malware hashes) with your asset inventory. If a match is found, Torq can isolate the asset, create a high-priority case, and initiate a full threat hunting workflow.

Email and endpoint security: Attack surface blind spots often include email systems and endpoints. Torq bridges the gap by integrating with email security tools (like Proofpoint and Microsoft Defender) and EDRs (like CrowdStrike and SentinelOne). ASM alerts tied to phishing or endpoint anomalies can trigger dynamic playbooks for containment, notification, and root cause analysis.

Compliance and audit automation: Torq’s action across your ASM program is fully logged and auditable. You can automatically generate compliance artifacts showing asset inventory, exposure history, response timelines, and post-remediation validation, streamlining audits for security frameworks like NIST, ISO, or SOC 2.

Hyperautomate Your Attack Surface Management with Torq

Your organization’s attack surface evolves continuously. ASM tools help you discover new vulnerabilities, but Torq empowers you to automatically respond and remediate, significantly shrinking your risk. With Torq, your ASM strategy is always-on, automated, and agile.

Don’t wait to react. Don’t accept blind spots.

Get the Manifesto

FAQs

How does Torq's Hyperautomation™ enhance attack surface management compared to traditional methods?

Torq Hyperautomation™ transforms attack surface management from a static, manual process into a dynamic, automated capability. Traditional ASM often involves periodic scans and manual triage, which leave gaps in visibility and delay remediation. Torq eliminates these blind spots by continuously orchestrating real-time asset discovery, risk prioritization, and automated response across your existing security stack.

This allows security teams to instantly detect new exposures and take immediate action without human intervention. By replacing fragmented processes with intelligent, automated workflows, Torq significantly reduces response time, operational overhead, and risk of oversight.

Can attack surface management help organizations with compliance requirements?

Yes — effective ASM is an enabler of compliance. Regulatory frameworks like HIPAA, PCI-DSS, and ISO 27001 require organizations to maintain visibility into their digital environments and actively manage vulnerabilities. Torq supports this by automatically inventorying assets, tracking configuration changes, and documenting remediation efforts.

Compliance reporting becomes faster and more accurate, with up-to-date telemetry across hybrid and multi-cloud environments. Torq also automates audit preparation through prebuilt workflows that map findings to compliance controls, helping security and GRC teams demonstrate ongoing adherence.

What industries benefit most from adopting advanced attack surface management strategies?

Industries with high-value data and strict regulatory requirements stand to gain the most from comprehensive ASM, including finance, healthcare, retail, manufacturing, and technology. These sectors often face sprawling digital footprints, complex supply chains, and increasing attack surface due to remote work and cloud adoption.

Torq tailors its Hyperautomation workflows to meet the unique operational and compliance demands of each industry, whether it’s protecting financial APIs, securing electronic health records (EHRs), or enforcing zero trust policies in distributed cloud environments.

How does Torq facilitate collaboration within security teams when managing the attack surface?

Torq breaks down silos between SecOps, IT, and cloud teams by providing a centralized automation platform that unifies threat detection, incident response, and asset visibility. Teams can collaborate on shared playbooks, receive alerts through integrated channels like Slack or ServiceNow, and maintain role-based access to workflows and data.

Torq’s automated workflows ensure consistent execution while allowing human oversight when needed, improving alignment and accelerating decision-making across teams. The result is faster response, reduced miscommunication, and a unified approach to attack surface defense.

SecOps Automation: How Lean Teams Can Achieve Enterprise-Level Security

By Torq

June 9, 2025

8 Minute Read

What Is SecOps Automation?

SecOps automation is the process using technology to streamline and automate the core workflows of security operations, including threat detection, triage, investigation, response, access control, and compliance reporting. It removes the manual work and alert fatigue that bog down security teams, enabling faster, more consistent, and more scalable operations.

While DevSecOps focuses on integrating security into the software development lifecycle, and ITOps automation targets infrastructure and IT service management, SecOps automation is laser-focused on protecting the business from threats.

Traditional SecOps Is Broken

Most security teams today are running on fumes. Threats are increasing, tools are multiplying, and analysts are stuck in an endless loop of triage and tuning as they face:

Too many alerts, not enough analysts: Security teams are drowning in noise. With limited headcount, it’s impossible to investigate everything, causing critical alerts to go unnoticed.
Poor tool integration: 51% of security leaders say their tools don’t integrate well, creating silos, manual handoffs, and slower response times.
Busywork over threat work: 46% of teams spend more time configuring and troubleshooting tools than mitigating threats. Another 59% say maintaining tools is the #1 inefficiency in their SOC.

It’s not sustainable — especially for lean teams.

Why Lean Teams Need SecOps Automation

Lean security teams are under pressure to deliver big results — without the benefit of big budgets, big headcount, or big enterprise infrastructure. They face the same volume of threats, alerts, and compliance requirements as a Fortune 500 but with a fraction of the resources.

SecOps automation bridges this resource gap. Deterministic automation workflows are ideal for the most common, repetitive, or predictable tasks, while non-deterministic workflows — augmented by agentic AI — enable understaffed SOC teams to handle more complex, multi-step security use cases more quickly and move towards an autonomous SOC.

SecOps automation significantly reduces manual overhead, accelerates threat response times, and empowers lean teams to run high-performance SOCs without the traditional overhead.

Five Ways Automated SecOps Helps Level the Playing Field

1. Phishing

Phishing is the most common form of cybercrime, with an estimated 3.4 billion spam emails sent daily. Each suspicious email requires triage, enrichment, investigation, and user outreach. Multiply that by dozens (or hundreds) of alerts a day, and you’re looking at full-blown burnout.

Automated SecOps turns phishing response into a self-contained workflow. From inbox monitoring and URL detonation to IOC lookups and automated takedowns, the entire lifecycle can be handled in minutes — not hours — without ever touching the analyst queue.

2. Threat Intelligence Enrichment

Threat intel is only useful if it’s fast, contextual, and operationalized — three things that don’t happen when analysts are manually switching between threat feeds and enrichment tools.

With SecOps automation, threat enrichment happens automatically. As alerts are ingested, automation pulls relevant context from multiple intel sources, correlates them with local data, and attaches insights to each case. That gives analysts a complete picture from the start.

3. Incident Response

Manual incident response is slow, error-prone, and hard to scale, especially with limited staff. Analysts have to piece together clues from multiple systems, coordinate handoffs, and manually document every action. For lean teams, it’s a recipe for delays and missed steps.

Automated incident response changes the game. As soon as an incident is detected, workflows kick off to contain the threat, collect forensics, notify stakeholders, and even auto-resolve based on pre-approved playbooks. With agentic AI in the loop, you can even triage, investigate, and remediate without any human intervention.

4. Vulnerability Management (VM)

Prioritizing which vulnerabilities matter is half the battle. But manually scanning assets, matching vulnerabilities to context, and assigning follow-up tasks can take days — assuming it gets done at all.

Automated SecOps streamlines the entire VM lifecycle. It ingests scanner output, correlates it with asset data, flags exploitable vulnerabilities, and initiates remediation workflows based on risk level — all without human touch. Analysts get real-time visibility into what’s fixed, what’s pending, and what’s critical.

5. Identity and Access Management (IAM)

Access creep and reused credentials are an open door for attackers — but they’re often overlooked because IAM tasks are tedious and time-consuming.

With automation, IAM becomes hands-free. Just-in-time access, automatic revocation, and periodic audits all run behind the scenes. You can even automate a response to suspicious activity, like impossible travel or privilege escalation, before an attacker has time to act.

SecOps Automation = Big Results for Lean Teams

Built for all skill levels: Low-code and no-code automation platforms have lowered the barrier to entry for security teams, making it easier for them to implement and manage security solutions. Analysts can build and deploy workflows without needing to write a single line of code, while more technical users can dig into scripting and APIs when needed. This flexibility empowers teams to move faster and focus on strategy instead of syntax.

Faster time to value with pre-built workflows: Many SecOps automation platforms offer prebuilt workflows for common use cases like phishing response and alert triage. These templates help teams launch fast, then iterate and customize for their environment.

Unified dashboards and reporting: Effective SecOps automation isn’t just about doing more — it’s about seeing more. Automation platforms often include built-in dashboards, visual workflow builders, and custom reporting tools that make it easier to track performance, prove value, and drive continuous improvement.

More use case coverage: Automation isn’t limited to incident response. Mature SecOps teams extend it to vulnerability management, insider threat detection, access controls, compliance audits, and even IT workflows like onboarding or offboarding. The more you automate, the more time your team has for strategic work.

Fully integrated AI access: It’s no secret that AI is the big hot ticket item in the cybersecurity industry. However, most organizations are diligently evaluating and carefully choosing when and where to deploy AI in their security stack — and rightfully so.

Whether you are slow-rolling AI access due to budget constraints or still building a business case to demonstrate the value of AI in the SOC to upper management, a SecOps automation platform provides a unique, centralized hub that fully integrates with every security solution, ensuring consistent and controlled AI access across your entire security environment.

Torq: The Leading Platform for SecOps Automation

Torq HyperSOC™ is the agentic AI-driven platform explicitly designed to empower lean security teams with extensive SecOps automation capabilities. Torq delivers:

Multi-Agent AI: Torq’s Socrates orchestrates automated workflows across specialized AI agents, seamlessly handling phishing triage, malware containment, IAM hygiene, and more.
Natural language workflows: No-code and low-code interfaces allow teams to launch and modify workflows simply by describing their intent, significantly accelerating adoption and effectiveness.
Rapid integration: Instant, seamless integrations across the entire security ecosystem eliminate silos, ensuring workflows operate fluidly across tools like AWS, Azure, Okta, SentinelOne, and many more.
Autonomous response: From detection to containment and remediation, Torq autonomously manages threats, dramatically reducing response times and enabling analysts to focus on high-impact tasks.

What SecOps Automation Looks Like

Torq customers consistently report transformative impacts from automating SecOps.

Check Point

Check Point’s SOC faced a crushing alert load and a 30–40% manpower gap, until Torq HyperSOC™ came into the picture. Within days, Torq deployed over two dozen AI-driven playbooks that automated repetitive tasks, reduced alert fatigue, and enabled autonomous remediation for low-level threats. Now, analysts are empowered to focus on what matters, with NLP-powered case insights helping them make faster, smarter decisions.

Global Retailer

This global fast-fashion giant replaced its legacy SOAR with Torq Hyperautomation™ to streamline security operations, cut alert fatigue, and simplify complex workflows across international teams. By automating end-user requests, case management, and just-in-time access, they reduced ticket resolution from days to minutes and saved a week of time per request.

Lennar

Lennar’s SOC team replaced XSOAR with Torq to eliminate manual phishing remediation that used to take hours and is now resolved in minutes. With no-code and AI-powered workflow building, analysts of all skill levels can build automations and refocus on proactive threat hunting. Torq’s flexibility and speed also helped streamline asset management, cutting hours of work down to just minutes.

Scale Your Security Without Scaling Your Team

Torq HyperSOC™ enables lean teams to protect their businesses at enterprise scale, with automated SecOps workflows that eliminate manual drudgery, reduce response times, and enable analysts to focus on strategic threat hunting and high-value tasks.

Want to scale your security operations with Torq? Get a demo. And check out our Field CISO’s guide with practical advice for a more efficient SOC.

Get the Guide

Hyperautomate the Vulnerability Management Lifecycle from Start to Finish

By Torq

June 6, 2025

11 Minute Read

Traditional vulnerability management is falling behind. Manual workflows stall progress. Legacy SOAR drags teams down. Siloed tools leave dangerous gaps. The result is delays, blind spots, and risk exposure that compound fast. Human error and inefficiency are baked into the process, costing teams more than time. It’s compromising compliance, degrading customer experience, and overwhelming analysts.

It doesn’t have to be this way.

This blog breaks the vulnerability management lifecycle into six steps, each primed for automation. We’ll show you how to modernize your workflows using Hyperautomation and agentic AI. This is how modern SOCs move faster, respond smarter, and stay in control.

What is the Vulnerability Management Lifecycle?

Vulnerability management is the continuous process of identifying, evaluating, prioritizing, remediating, and monitoring security weaknesses (vulnerabilities) across an organization’s systems, networks, and applications. Its goal is to reduce the attack surface by proactively addressing vulnerabilities before cybercriminals can exploit them.

The vulnerability management lifecycle is a continuous, systematic process for identifying, assessing, prioritizing, remediating, and monitoring security vulnerabilities within an organization’s IT infrastructure. It’s a crucial part of any cybersecurity strategy, aiming to manage risks and minimize the potential for cyberattacks proactively.

The vulnerability management lifecycle includes:

Discovery of all assets in the environment
Assessment of vulnerabilities using automated scanners and threat intelligence
Prioritization based on factors like severity (i.e., CVSS score), exploitability, and business impact
Remediation or mitigation through patching, configuration changes, or compensating controls
Validation and monitoring to confirm fixes and detect re-exposure or new risks
Reporting and improvement to refine processes and boost efficiency

Today’s dynamic cloud environments demand more than reactive security. As modern IT environments grow more complex and dynamic, traditional approaches that rely on manual processes and fragmented tools can’t keep up. The rapid change in cloud infrastructure and the constant emergence of new vulnerabilities make it nearly impossible for security teams to identify and act on every risk in time.

Automating the vulnerability management lifecycle — across asset discovery, scanning, prioritization, remediation, and validation — helps teams move from reactive to proactive. By integrating data from scanners, threat intelligence platforms, Configuration Management Databases (CMDBs), and ITSM (IT Service Management) systems, automated workflows can continuously identify critical issues, assign ownership, and trigger remediation actions.

Organizations can ensure consistent, efficient, and scalable risk mitigation with a well-defined and automated vulnerability management program. The result is faster response, reduced exposure, improved compliance, and a more resilient security posture.

The 6 Steps of Vulnerability Management Lifecycle You Can Automate Today

Step 1: Asset Discovery and Vulnerability Assessment

Before vulnerabilities can be managed, organizations must first identify every asset in their environment. This step begins with building a complete, real-time inventory of IT assets — including endpoints, servers, cloud workloads, SaaS apps, IoT devices, and shadow IT — across on-premises, cloud, and hybrid environments. Critical vulnerabilities often go undetected without accurate asset discovery, leaving organizations exposed.

Once discovered, assets should be classified based on business importance, data sensitivity, and exposure level. Security frameworks like the CIS Controls or ISO standards can help guide this classification process to ensure consistent, policy-driven prioritization.

Vulnerability assessment follows closely behind discovery. Organizations conduct scheduled or continuous scans using tools like Qualys, Tenable, or Rapid7 to identify known vulnerabilities. Automated scans are augmented by penetration tests and configuration audits, which simulate real-world attack scenarios and uncover deeper misconfigurations that scanners might miss. These assessments provide the foundation for informed, risk-based decision-making in later stages.

Key metrics for this step include asset discovery completeness, vulnerability coverage rate, and time to discovery. Organizations that automate asset discovery and vulnerability scanning reduce blind spots, accelerate detection, and set the stage for a proactive vulnerability management lifecycle.

How Torq Can Automate This: Torq integrates with your asset inventory, CMDB, cloud providers, and endpoint detection tools to ingest asset data continuously. No-code workflows automatically reconcile discovered assets across hybrid environments, keeping your inventory current without spreadsheets or manual audits. Clients can also use Torq to trigger validation workflows when new, unmanaged assets appear, alerting security teams to take immediate action.

Step 2: Vulnerability Scanning and Detection

With assets identified and inventoried, the next step is systematic vulnerability scanning. Continuous scanning ensures that new vulnerabilities are identified immediately, not just during scheduled review windows. Modern scanners integrated with SIEMs, EDRs, and threat intelligence platforms can detect vulnerabilities and push findings into workflows.

Equally important is the normalization and automation of scan data. Without these key systems, teams often struggle to analyze findings from multiple tools or formats. Automated ingestion pipelines ensure scan results are normalized, deduplicated, and enriched with contextual metadata so teams can prioritize issues efficiently. This minimizes human error and eliminates manual data wrangling, allowing analysts to focus on threat mitigation rather than spreadsheet management.

How Torq Can Automate This: Torq connects directly to vulnerability scanners like Tenable, Qualys, and Rapid7 to ingest real-time scan results. It normalizes disparate data formats and enriches them with contextual metadata, like asset criticality, owner, and business function, then automatically routes findings into triage workflows. Torq eliminates bottlenecks by auto-tagging vulnerabilities based on severity, source, and exploitability, and escalating only the ones that matter.

Step 3: Risk-Based Vulnerability Prioritization

Not all vulnerabilities pose the same threat, and relying solely on Common Vulnerability Scoring System (CVSS) scores often wastes time and leads to missed priorities.

Effective vulnerability prioritization combines multiple factors: severity ratings, real-time threat intelligence, asset value, exploitability, and the potential business impact if compromised. A vulnerability on a public-facing application used by customers carries far more weight than one on an internal test server, even if their CVSS scores are identical.

This stage involves applying structure and strategy to vulnerability triage. It requires input from multiple systems and stakeholders and the ability to evaluate each vulnerability in context, not just in isolation.

How Torq Can Automate This: Torq automates prioritization by combining CVSS scores, threat intelligence, asset importance, and business impact. Risk-scoring models are baked into workflows that assign ownership based on asset tags or business unit and notify the right team instantly. AI Agents dynamically adapt prioritization workflows to changing threat intel, for example, reprioritizing based on active exploitation reports from MISP or Recorded Future.

Step 4: Remediation and Patch Deployment

Once vulnerabilities are prioritized, the next step is action — and this is where many organizations get bogged down. Patch management and remediation can be time-consuming, error-prone, and resource-intensive, especially when handled manually.

Coordinating patch deployment, configuration changes, and policy enforcement is complex. Different systems, ticketing queues, and ownership models often introduce delays that extend mean time to remediate (MTTR). Critical asset patching may sometimes be skipped entirely due to a lack of visibility or process bottlenecks.

The key to making remediation effective is ensuring it’s consistent, policy-driven, and well-integrated with existing IT and security infrastructure. Automated workflows streamline this process.

How Torq Can Automate This: Torq triggers auto-remediation actions the moment a vulnerability crosses a risk threshold. Whether that’s opening a ServiceNow ticket, deploying a patch through CrowdStrike, or updating firewall rules — Torq coordinates every step across ITSM, EDR, and config management systems. Torq lets you define remediation SLAs by risk level, then automatically tracks and escalates any patching delays.

Step 5: Validation and Continuous Monitoring

Even after a patch is deployed or a mitigation is applied, teams must validate that the vulnerability is truly resolved and that the fix hasn’t introduced new risks. Organizations can be left with a false sense of security without a clear validation process.

This step is also where continuous monitoring comes into play. Threats evolve, and systems change, meaning previously resolved vulnerabilities can resurface or emerge in the same risk areas. Keeping tabs on those changes in real time is essential to maintaining a strong security posture.

Beyond operational assurance, validation and monitoring also feed key performance indicators (KPIs). Metrics like mean time to validate, remediation success rate, and recurring vulnerabilities offer insight into program effectiveness and guide continuous improvement.

How Torq Can Automate This: Torq ensures that every remediation action is followed by automatic verification. It coordinates post-patch scans, checks system health, and updates real-time vulnerability status. If a scan fails or a system shows signs of re-exposure, Torq reopens the case and notifies the right teams.

Torq’s workflows also power continuous monitoring across your environment, triggering alerts and actions the moment new vulnerabilities are detected. All validation results are logged with full audit trails, giving teams a clear, compliant record of what was fixed, when, and how.

Step 6: Reporting and Improvement

The final — and often most overlooked — step in the vulnerability management lifecycle is reporting and continuous improvement. This stage turns tactical remediation work into strategic insight, enabling security teams to track performance, share results with stakeholders, and refine processes over time.

Effective reporting starts with capturing and consolidating key metrics from across the lifecycle. These include mean time to detect (MTTD), mean time to remediate (MTTR), validation success rate, outstanding vulnerabilities by risk level, and SLA adherence. Automation can generate these reports in real time, pulling directly from ITSM, scanning tools, and case management systems, eliminating manual data gathering and improving accuracy.

But reporting isn’t just about compliance dashboards or CISO updates. It’s also about communicating clearly across teams. Security analysts need detailed, technical data to investigate root causes. IT and DevOps teams need actionable task lists and timelines. Executives need business-aligned summaries showing risk reduction, operational efficiency, and ROI. Torq’s AI case summaries and customizable reports ensure the right insights reach the right people.

Beyond communication, this stage powers process improvement. Every vulnerability managed, every patch deployed, and every false positive investigated is an opportunity to learn. Were there delays in detection? Was ownership misrouted? Did remediation workflows succeed automatically, or require manual overrides?

Automation platforms like Torq can highlight bottlenecks, track repetitive tasks, and suggest optimizations for future cycles, helping teams evolve with the threat landscape.

How Torq Can Automate This: Torq aggregates lifecycle metrics — MTTR, patching trends, asset coverage, false positives, and more — into real-time dashboards. It automates reporting to different stakeholders (security, IT, execs) and uses historical data to optimize future workflows. With Torq’s intelligent case summaries and agentic AI analysis, your team gets metrics, insights, and improvement recommendations after every cycle.

Visualizing the Automated Vulnerability Management Workflow

Each stage features integration points with standard security tools, all unified through no-code automation and adaptive AI workflows, ensuring seamless transitions between each lifecycle step.

How Torq’s No-Code, Agentic AI Transforms VM

Legacy SOAR platforms often promise automation — but deliver rigid, playbook-style workflows that break the moment something unexpected happens. They’re difficult to update, heavily reliant on code, and require constant upkeep to remain useful in fast-changing threat environments. Vulnerability management, in particular, suffers from this inflexibility. New CVEs emerge daily, patch windows shift, and business priorities evolve. Static systems simply can’t keep up.

Torq is built for the opposite. Its modern no-code platform empowers security teams to create and customize complex vulnerability management workflows — without writing a single line of code. Whether integrating with vulnerability scanners like Tenable or Qualys, orchestrating patch actions through CrowdStrike or SCCM, or syncing data across Jira, ServiceNow, and CMDBs — Torq makes it fast, repeatable, and reliable.

Where Torq truly sets itself apart is with agentic AI — purpose-built intelligence that doesn’t just execute tasks, but reasons through them. Torq’s agentic AI dynamically adjusts prioritization models based on live threat intelligence, changes workflows on the fly based on remediation delays or escalation policies, and even recommends new automation paths based on past actions and results.

This creates an entirely different experience:

No-code flexibility means teams can launch or modify vulnerability workflows in minutes, not days or weeks.
Dynamic response allows the system to reprioritize or reassign vulnerabilities as business needs or threat conditions shift.
Human-level reasoning lets agentic AI anticipate gaps or delays, take corrective action, and escalate intelligently, all without manual input.

By combining intuitive workflow creation with adaptive intelligence, Torq transforms the vulnerability management lifecycle from a slow, manual process into a fast, autonomous system. Teams can focus on strategy and oversight while Torq handles the orchestration, remediation, and validation at machine speed — all with full visibility and control. It’s not just automation — it’s Hyperautomation, designed for the pace and complexity of modern cybersecurity.

Reclaim Time. Reduce Risk. Automate Everything.

With Torq Hyperautomation™, every stage of the vulnerability management lifecycle becomes faster, more accurate, and radically more effective. Teams reclaim time, reduce risk, and stay focused on what matters: preventing the next security incident.

Ready to make the shift? Read the SOC Efficiency Guide to see how leading security teams accelerate response, eliminate alert fatigue, and scale operations with Torq.

Get My Copy

Cybersecurity Frameworks Explained: Avoid Critical Risks in Your Strategic Enterprise

By Torq

June 4, 2025

9 Minute Read

Cybersecurity frameworks provide organizations with clear, actionable pathways to safeguard assets, ensure regulatory compliance, maintain robust security controls, and align security initiatives effectively. But while frameworks like NIST, ISO, and CIS provide a vital blueprint for security, implementing them is anything but straightforward. Manual processes, siloed tools, and resource constraints slow implementation and dilute impact.

Torq Hyperautomation™ eliminates the operational friction of security framework adoption. It connects your tools, automates repetitive control validation, and ensures your security program stays aligned, agile, and audit-ready.

Whether you’re building toward SOC 2, aligning to NIST CSF, or managing global compliance at scale, Torq transforms frameworks from static documents into living, responsive systems that secure your entire network.

Why Cybersecurity Frameworks Matter

A security framework is a structured set of guidelines, best practices, and standards designed to help organizations manage and reduce cybersecurity risk. It provides a repeatable methodology for identifying, protecting, detecting, responding to, and recovering from cyber threats, while ensuring alignment with regulatory, legal, and industry-specific compliance requirements.

A security framework outlines:

Security controls: Technical, administrative, and physical safeguards to protect systems and data
Risk management processes: How to assess and prioritize threats and vulnerabilities
Governance structures: Roles, responsibilities, and oversight mechanisms
Continuous improvement: Ongoing assessment, monitoring, and adaptation to evolving threats

Benefits of adopting a cybersecurity framework include:

Improved risk management: Frameworks provide comprehensive and established methods for identifying, assessing, and mitigating cybersecurity threats and vulnerabilities.
Enhanced compliance: Frameworks such as GDPR, HIPAA, and PCI DSS outline explicit guidelines for managing sensitive data, ensuring enterprises meet regulatory obligations and avoid costly penalties.
Streamlined security processes: Implementing standardized cybersecurity frameworks reduces complexity and enables more efficient security operations.

12 Common Types of Security Frameworks in 2025

Understanding the various security frameworks available is crucial for selecting the right approach tailored to your organization’s needs. Here are some of the most widely adopted cybersecurity frameworks:

SOC 2 (System and Organization Controls 2): A framework developed by the AICPA to evaluate service providers’ ability to manage customer data securely. It is based on five trust service criteria: security, availability, processing integrity, confidentiality, and privacy. SOC 2 is crucial for SaaS and cloud service providers handling sensitive customer data. It signals to clients and auditors that your organization meets strict standards for data handling and privacy.
GDPR (General Data Protection Regulation): A European Union regulation that sets strict requirements for data privacy and protection for any organization handling EU citizen data. GDPR impacts organizations worldwide due to its extraterritorial scope and severe penalties for noncompliance.
PCI DSS (Payment Card Industry Data Security Standard): A global standard for securing credit card transactions and sensitive payment data. It is mandatory for any organization that stores, processes, or transmits cardholder data.
HIPAA (Health Insurance Portability and Accountability Act): A U.S. regulation that establishes national standards to protect sensitive patient health information. It applies to healthcare providers, insurers, and business associates managing protected health information (PHI).
CIS Controls: A prioritized set of 18 best practices developed by the Center for Internet Security (CIS), designed to protect against the most common and dangerous cyber threats.
ISO 27001: An international standard for establishing, implementing, maintaining, and continually improving an Information Security Management System (ISMS). It’s one of the most comprehensive and certifiable frameworks available.
NIST SP 800-53: A catalog of security and privacy controls developed by the National Institute of Standards and Technology (NIST) for federal agencies and their contractors. It’s highly detailed and adaptable for enterprises seeking rigorous security control baselines.
NIST SP 800-171: Aimed at non-federal organizations, this framework outlines security requirements for protecting Controlled Unclassified Information (CUI). Often used by defense contractors and other government-adjacent enterprises.
NIST Cybersecurity Framework (NIST CSF): A voluntary framework designed to help organizations of all sizes manage and reduce cybersecurity risks. It consists of five core functions: Identify, Protect, Detect, Respond, and Recover.
NIST SP 1800 Series: A collection of practical, example-driven publications offering step-by-step guidance for implementing cybersecurity technologies, tailored for specific sectors and challenges.
COBIT: A framework by ISACA for governance and management of enterprise IT, aligning security with strategic business goals.
DORA (Digital Operational Resilience Act): A regulation introduced by the EU to ensure the financial sector’s operational resilience. DORA requires banks, insurers, investment firms, and other financial entities to manage and withstand risks.

How to Choose a Security Framework

Selecting an appropriate security framework requires careful consideration of several critical factors.

Understand your business context and requirements: Assess your industry, business size, regulatory landscape, and specific cybersecurity challenges.
Evaluate framework compatibility: Consider how easily the framework integrates with your existing technologies and security controls.
Prioritize scalability and adaptability: Ensure the chosen framework can grow with your organization and adapt to evolving threats.
Seek broad organizational support: Engage stakeholders across your organization, including IT, compliance, and executive teams, to ensure alignment and buy-in.
Leverage Hyperautomation for execution: Look for opportunities to operationalize framework controls using automation platforms like Torq. Automating control validation, policy enforcement, and evidence collection accelerates adoption and reduces long-term operational burden.

How to Navigate Security Framework Challenges with Torq

Implementing security frameworks can pose significant challenges for many organizations. Between legacy infrastructure, fragmented tooling, evolving threats, and limited resources, many organizations struggle to move from documentation to real-world execution. Torq Hyperautomation™ helps security teams overcome the most common framework adoption barriers by eliminating manual overhead and automating critical workflows. Here are some common challenges and how Torq helps solve them.

Integration with Existing Systems

Challenge: Legacy systems and fragmented security stacks can hinder effective integration of cybersecurity frameworks.

Torq Solution: Torq’s Hyperautomation Platform acts as the connection across your environment, integrating seamlessly with SIEMs, EDRs, ticketing systems, IAM tools, and cloud platforms. Whether you’re automating control testing, enforcing configuration standards, or orchestrating incident response, Torq streamlines the end-to-end flow of data and decisions. Drag-and-drop and AI-generated workflows and low-code/no-code interfaces empower teams to operationalize frameworks without developer bottlenecks.

Budget Constraints

Challenge: Many organizations have limited resources, which complicates the implementation of comprehensive security frameworks.

Torq Solution: Torq automates the grunt work of security operations. From mapping controls to running automated assessments, Torq eliminates repetitive tasks and minimizes the need for dedicated coding resources. Torq helps organizations achieve full framework alignment within days or weeks by reducing engineering dependencies and accelerating time-to-value. The result is lower operational costs and higher team productivity.

Evolving Threat Landscape

Challenge: Cyber threats continually evolve, requiring dynamic responses from security frameworks.

Torq Solution: Torq continuously adapts to changing threat conditions using telemetry, AI-driven enrichment, and dynamic workflows. When anomalies are detected, it can automatically trigger responses aligned to your framework requirements, whether that means escalating high-risk activity, revoking access, or triggering predefined mitigation playbooks.

Ensuring Compliance and Audits

Challenge: Maintaining ongoing compliance and being audit-ready at all times is challenging, particularly for global enterprises.

Torq Solution: Torq automates evidence collection, control validation, and documentation, ensuring compliance workflows are baked into daily operations. It creates a centralized audit trail of all actions taken, complete with timestamps, enriched context, and mapped framework references. Whether preparing for an internal review or a third-party audit, Torq gives your team a single source of truth that’s always up to date and defensible.

Why Torq?

Torq Hyperautomation is built to operationalize security frameworks at scale. It delivers:

Unified orchestration across tools, teams, and cloud-native environments
Contextual automation that adapts to evolving threats and compliance needs
Framework-aligned workflows that are repeatable, measurable, and audit-ready
Enterprise-grade security with RBAC, logging, version control, and policy enforcement

Whether you’re building toward SOC 2, aligning to ISO 27001, or navigating NIST 800-171 requirements, Torq makes it faster, easier, and more cost-effective to meet your goals.

Operationalizing Security Frameworks with Hyperautomation

For many organizations, cybersecurity frameworks exist primarily as static documents, useful for audits, but disconnected from daily security operations. The result is an execution gap: security teams know what they should be doing but lack the tools to enforce those controls in real time. This is where most frameworks fall short.

With Torq Hyperautomation™, security frameworks are no longer theoretical. Every control, requirement, and guideline can be translated into automated workflows that enforce compliance continuously across your environment.

Torq brings security frameworks to life:

Control mapping: Connect framework controls to specific, repeatable workflows. Based on your framework’s requirements, automate user access reviews, policy enforcement, or data loss prevention.
Continuous monitoring: Instead of relying on periodic assessments, Torq continuously validates whether controls are being followed, flagging drift immediately and triggering corrective action before gaps become risks.
Automatic documentation and evidence collection: Every action is logged, timestamped, and mapped back to the corresponding framework control. That means when audit time comes, all the evidence is already there.
Case management: Framework-driven alerts or incidents (e.g., a failed backup, an unauthorized access attempt) are automatically routed into case management workflows. Analysts can investigate, respond, and document resolutions, ensuring nothing falls through the cracks.

Make Cybersecurity Frameworks Work for You

Security frameworks are essential to building a resilient, compliant, and threat-ready enterprise, but only when they’re effectively operationalized. Too often, organizations get stuck in manual processes, fragmented tools, and misaligned controls, turning frameworks into paperwork rather than real protection.

By combining powerful Hyperautomation with deep integration across your security stack, Torq brings cybersecurity frameworks to life. It ensures your organization isn’t just aligned to standards like NIST, ISO 27001, or SOC 2 but actively enforcing them in real time.

From automating evidence collection and incident response to dynamically adapting to new threats, Torq empowers your security teams to move faster, reduce costs, and improve outcomes, without compromising control or compliance.

Stop managing frameworks. Start operationalizing them.

Get the Manifesto

The AI SOC Analyst That Offloads 90%+ of Tier-1 Cases — Meet Socrates

By Bob Boyle

June 2, 2025

10 Minute Read

Security Operations Centers (SOCs) continue to struggle in 2025. The perfect storm of growing alert volume, consistent talent shortage, and the well-documented limitations of legacy SOAR solutions have brought many SOC teams to a breaking point. At the same time, bad actors continue to innovate, and cybercriminals have become more sophisticated in their tactics and techniques, including using AI to launch attacks at scale.

Fortunately, AI in the SOC has begun to revolutionize the security operations field, specifically in the area of Tier-1 security analysis. According to Gartner, “By 2026, AI will increase SOC efficiency by 40% compared with 2024 efficiency, beginning a shift in SOC expertise toward AI development, maintenance and protection.”

Why the SOC Needs an AI Analyst

As alert complexity rises, so does burnout and alert fatigue. SOC analysts today spend too much time sifting through noise and manually triaging alerts, rather than taking action to proactively secure the environment. According to the 2024 SANS Detection and Response Survey, more than half of security teams say false positives are a huge problem, and 62.5% are overwhelmed by sheer data volume.

A major reason for this frustration is that security teams are fighting with their own tools. In a recent State of Security 2025 report, Cisco’s Splunk surveyed over 2,000 security professionals in their community to find:

59% spend too much time and/or effort maintaining tools and associated workflows
51% admit their tools do not integrate well with one another
47% face alerting issues
32% of teams do not have the requisite skills to be efficient in the SOC

Tier-1 alert triage is overwhelming. Analysts face tens of thousands of Tier-1 alerts per day, and on average, security analysts are only getting to half of the alerts they’re supposed to review. Combined with these SOC inefficiencies, the volume becomes too high for human-only triage. As a result, detection and response times suffer. Gartner says, “AI agents are emerging as a critical solution to enhance efficiency, reduce burnout, and enable teams to focus on strategic initiatives.”

Enter Torq Socrates — the agentic AI SOC Analyst designed to dramatically offload Tier-1 workloads and lead organizations toward an autonomous SOC.

What is an AI SOC Analyst?

An AI SOC Analyst serves as an extension of SOC teams, automating incident response by interpreting natural language instructions in security runbooks to execute tasks such as alert triage, containment, and remediation actions. While an AI SOC Analyst autonomously handles over 90% of Tier-1 tasks, human analysts remain in control of critical decisions and can interface with the AI SOC Analyst using natural language for additional enrichment, investigation, and recommended next steps.

Learn unconventional criteria for evaluating AI SOC analysts >

What Is Torq Socrates?

Socrates is Torq’s agentic AI SOC Analyst — a self-deterministic, autonomous AI Agent that plans, reasons, and acts the way a human SOC analyst would. Unlike SOAR solutions or common Generative AI chatbots, Socrates does not require human instruction or guidance. Socrates understands the SOC objectives and executes complex actions with minimal oversight.

Legacy SOAR and generic workflow automation solutions offer AI chatbots that run on static, rule-based playbooks — controlled by human input. And, while GenAI augments case triage by generating context to help reduce detection and response times, it is still largely reactive and reliant on human analysts to instruct, guide, and manually trigger remediation actions. Agentic AI, on the other hand, represents the next leap towards a more autonomous SOC.

According to IDC’s latest report, agentic AI has enormous potential in cybersecurity as it can process and solve problems the way a human being would. Socrates isn’t reactive — it’s adaptive. To continuously improve and evolve with new threats, Socrates uses:

Semantic memory to understand prompts and take explicit action
Episodic memory to learn from past incidents to develop new strategies
Procedural memory to make decisions on which tools to use and which data to gather

The Anatomy of Socrates: Torq’s OmniAgent

Socrates is more than just a single AI Agent. Socrates sits at the helm of Torq’s Multi-Agent System (MAS), acting as an OmniAgent in charge of coordinating multiple specialized AI Agents. Each of these agents is trained to perform a specific task, and is capable of using sophisticated iterative planning and reasoning to solve complex, multi-step problems autonomously. Torq’s AI Agents include:

Runbook Agent: Autonomously plans and adapts incident response runbooks with a deep knowledge and understanding of the environment.
Investigation Agent: Performs deep-dive investigations in seconds, uncovering hidden patterns across disparate data sources and tools to pinpoint root causes and assess threat impact.
Remediation Agent: Executes remediation actions, closing the loop with verifiable outcomes, either by autonomously following the associated runbook or through human-in-the-loop response.
Case Management Agent: Gathers real-time and historical data, organizes case timelines, highlights key indicators, and reprioritizes incidents based on evolving information.

This agentic AI architecture is supported by first in class Retrieval-Augemented Generation (RAG) and Model-Context Protocol (MCP) technology that helps the Torq MAS dynamically accelerate SecOps outcomes by improving detection and triage accuracy, while reducing MTTD and MTTR.

How an AI SOC Analyst Performs Tier-1 Tasks

So, how does Socrates leverage Torq’s MAS to perform Tier-1 security tasks? Let’s look at this Command and Control attack detected by Crowdstrike and see how tasks previously handled by human analysts are now handled with unprecedented efficiency by Torq’s AI SOC Analyst, Socrates.

*Watch Socrates, Torq’s AI SOC Analyst, following the guidelines in a SOC runbook to triage a case automatically.*

1. Automatic Runbook Analysis

When a security event arises, an analyst traditionally consults a “runbook” – a guide specifying the response to that specific type of event. Today, these “runbooks” exist in all modern SOCs and are prepared by senior architects to benefit Tier-1 and Tier-2 analysts.

Torq Socrates looks at outcomes of historical cases and associates the appropriate runbook based on the observables of the new case. Socrates automatically analyzes runbooks written in natural language, typically containing step-by-step procedures for handling various security incidents. By analyzing the semantic meaning of the natural language instructions, the AI SOC Analyst derives action flow from the recommended response strategies for different security events.

*The associated case remediation runbook is written in natural language that Socrates analyzes, “understands,” and can follow.*

2. Deep Research Incident Investigations

The many security tools available in the arsenal of Tier-1 SOC analysts can return a large amount of detailed information. The analyst’s goal is to synthesize this information into a decision about which next steps to take, according to the runbook’s guidance.

Just as human analysts rely on insights from the runbook, Socrates can assist in automating investigation or even incident response tasks. This includes executing tasks such as alert triage, data enrichment, containment, and remediation actions, which speeds up response times and reduces the manual effort required from human analysts.

An agentic AI SOC Analyst like Socrates excels at processing both structured and unstructured security tool data. This enables it to analyze complex information and create dynamic decision trees based on runbook analysis. These decision trees adapt to the specific context of each incident, allowing for more efficient and accurate incident handling. For example, Socrates can determine: Is the file malicious? Is the user a very important person (VIP)? Is the activity frequent or infrequent during a specific time period indicating anomalous behavior?

*Socrates utilizing Crowdstrike, VirusTotal, and a deep understanding of the organization’s environment to query observables and distill the relevant information.*

3. Knowledge of Security Frameworks for Context

More experienced alert triage specialists bring their own contextual knowledge and understanding of networking, endpoint architecture, and attack techniques into the mix.

AI Agents are trained on an immense body of natural language documents containing information about the above and more. This allows the semantic analysis of an AI Agent to match the observed outcome of a security tool and the technique described in a documented framework, such as the MITRE ATT&CK framework.

Using the above technique, Torq’s agentic AI SOC Analyst, Socrates, leverages the information available in numerous documents describing attack frameworks, such as the MITRE ATT&CK framework, and maps its tactics and techniques to the outcomes observed in the analyzed security event.

Intelligent modeling with Torq’s AI SOC Analyst Socrates enables it to mimic a human-like thinking process, correlating information efficiently and mapping the appropriate outcomes to common frameworks like the MITRE ATT&CK framework, NIST, and more.

4. Leveraging Hyperautomation to Perform Designated Remediation Actions

The next step for a human analyst is to carry out the remediation actions outlined in the runbooks, choosing the proper tool and executing the instructions.

Based on the content of the runbook, the AI SOC Analyst utilizes its semantic analysis capabilities to suggest and trigger suitable Hyperautomated workflows and security tools from the list of ones explicitly made available within the Torq platform. These workflows align with the specific steps outlined in the document conveyed in natural language.

*Torq Socrates performing the initial actions within the runbook.*

5. Intelligent Case Management and Documentation

An important pillar of any operational practice is the meticulous documentation of all actions taken, decisions, and achieved outcomes.

AI Agents have proven to be efficient at summarizing large amounts of natural language text. Torq Socrates leverages this capability to summarize the “conclusions” and desired next steps, and document them in the “case timeline”. Socrates then reaches back into its toolbox and ability to take action autonomously, marking the case as “closed” and moving the case forward without any human intervention.

*Torq Socrates summarizing the findings and actions taken of the security event and automatically adding them to Torq’s built-in ticket management system timeline.*

How Security Teams Use Socrates Today

Gartner forecasts that by 2028, multi-agent AI in threat detection and incident response will rise from 5% to 70%. For Torq customers leveraging Socrates, this is already their reality.

“I believe the successful use of Torq Agentic AI in SOC operations shows up in practical outcomes. With Torq Agentic AI, the answer is yes to questions such as: Are analysts happier? Are they sticking around? Do they have time to focus on more interesting and complex investigations? Are MTTM and MTTR lower? Torq Agentic AI extends and enhances our team so it can make better decisions more quickly — resulting in stronger security all around.”
Mick Leach, Field CISO, Abnormal Security

Socrates isn’t just another tool — it’s another teammate. And it’s changing the way security gets done. With Socrates, security decisions are made with context, fully automated incident response becomes the default, and agentic AI becomes the connective tissue across previously siloed security solutions that enable SOC teams to move from human-in-the-loop to human-on-the-loop.

According to IDC, Torq HyperSOC, powered by Socrates, helps:

Eliminate over 95% of Tier-1 analyst workload
Reduce time-to-remediation by 90%
Increase case handling capacity 3-5x with zero added headcount

Torq Socrates is designed to handle Tier-1 triage actions by mapping the tasks and activities of human Tier-1 analysts to use cases leveraging agentic AI. With Torq Socrates as their AI SOC Analyst, human security analysts remain in charge of processes and outcomes while introducing dramatic new efficiencies and incident response accuracy, alleviating security analysts’ most critical challenges.

Want to meet Socrates? Request a demo. And get the AI or Die Manifesto to learn strategic considerations and CISO advice for deploying AI in your SOC.

Get the Manifesto

Cybersecurity Best Practices Every Organization Should Follow

By Torq

May 30, 2025

8 Minute Read

What are Best Practices in Cybersecurity?

Cybersecurity best practices are proactive measures, policies, and technologies designed to minimize your organization’s cyber risk. Adhering to these practices helps businesses stay secure by preventing breaches, ensuring compliance, protecting sensitive data, preventing data breaches, and maintaining business continuity.

Many cybersecurity frameworks emphasize the “5 C’s of cybersecurity”:

Change: Regularly updating security measures.
Compliance: Adhering to industry standards and regulations.
Cost: Balancing security spending and effectiveness.
Continuity: Ensuring ongoing business operations after incidents.
Coverage: Comprehensive protection across all digital assets.

To improve cybersecurity, companies must combine extensive policies, employee education, strong access controls, and real-time threat response, ideally powered by scalable Hyperautomation platforms.

10 Essential Cybersecurity Best Practices (and How Torq Hyperautomates Them)

Cyber threats move fast, and your defenses need to move faster. These ten best practices are non-negotiable for modern SOC teams. But implementing them manually? That’s where most organizations fall behind.

Torq Hyperautomation™ eliminates the friction by turning best practices into fully automated, always-on workflows. Whether enforcing access controls, responding to phishing attempts, or monitoring endpoints, Torq ensures each control is executed precisely and at scale.

Here’s what to put in place now — and how Torq helps you do it effortlessly.

1. Use Strong, Unique Passwords and a Password Manager

Passwords are often the first — and weakest — line of defense against cyber intrusions. Weak or reused passwords significantly increase the risk of account compromise, especially in credential stuffing and brute-force cyber attacks. Organizations should enforce strong password policies that mandate the use of long, complex, and unique passwords for every account.

To ease the burden on employees, deploy enterprise-grade password managers that generate, store, and autofill passwords securely. These tools reduce password fatigue and help prevent risky practices like writing down credentials or reusing them across platforms. Periodic password audits can also be automated with Torq, which can trigger alerts when passwords aren’t updated or don’t meet compliance standards.

2. Enable Multi-Factor Authentication (MFA) Everywhere

MFA is one of the simplest and most effective ways to prevent unauthorized access. It ensures that even if credentials are compromised, hackers can’t easily access sensitive systems without a second form of verification, such as biometrics, hardware tokens, or authenticator apps.

Torq enhances MFA implementation with Role-Based Access Control (RBAC) automation workflows. Security teams can use Torq to enforce MFA across platforms, audit authentication events, and automatically revoke access for users who haven’t completed MFA setup, minimizing friction and oversight.

3. Keep All Software and OS Up to Date

Outdated systems often harbor unpatched vulnerabilities that threat actors exploit. From zero-day vulnerabilities in operating systems to neglected third-party apps, every unpatched asset is a liability.

Implement an automated patch management strategy. With Torq, security teams can set up workflows that monitor software versions across endpoints, flag outdated components, and trigger notifications or remediation actions when updates are overdue. Coupling this with scheduled audits ensures continuous hygiene and reduces attack surfaces.

4. Install Antivirus and Anti-Malware on Every Device

Endpoint protection remains critical in defending against a broad range of cyber threats including ransomware, malware, and trojans. Organizations should deploy endpoint detection and response (EDR) solutions that use real-time behavioral analysis, not just signature-based detection.

To ensure these tools stay effective, Torq can integrate with antivirus platforms to monitor endpoint health, validate update statuses, and automate quarantine or isolation actions in response to detected threats, speeding up remediation and reducing exposure windows.

5. Secure Networks with Firewalls and VPNs

Firewalls and VPNs help shield organizational networks from unauthorized access and malicious traffic. Firewalls block suspicious inbound/outbound traffic, while VPNs provide encrypted tunnels for secure remote access, especially critical in hybrid work environments.

Torq can enhance these protections by automating firewall rule updates, triggering alerts when unexpected changes occur, and monitoring VPN usage for anomalous patterns such as logins from unusual geolocations or times. This automation ensures your network security posture stays strong without requiring constant manual oversight.

6. Regularly Back Up Data to the Cloud and Offline

Cyberattacks like ransomware and accidental deletions can lead to devastating data loss. Regular backups are your safety net. Organizations should adopt a 3-2-1 backup strategy: three copies of data, two on different media, and one offsite.

Torq helps ensure backup best practices are followed by automating backup verification, alerting if a backup fails, and orchestrating regular backup operations. Teams can also use Torq to conduct post-backup security posture checks to ensure backups aren’t infected or misconfigured, ensuring they’re both usable and secure.

The human element remains the weakest link in cybersecurity. Regular security awareness training, including simulated phishing campaigns, is essential to prepare employees for common social engineering tactics.

Torq supports these efforts with automated phishing response workflows. When phishing attacks are reported or detected, Socrates, our AI SOC Analyst, rapidly investigates, auto-remediates the message, and updates the reporting employee, reducing response time and enabling analysts to focus on complex threats. Combined with training, this creates a layered defense against email-based attacks.

8. Use Encryption for Sensitive Data at Rest and in Transit

Encryption ensures that even if data is intercepted or accessed without authorization, it remains unreadable. All sensitive data — customer records, financial information, proprietary code — should be encrypted both at rest (on storage systems) and in transit (during transmission over networks).

Organizations should enforce the use of industry-standard protocols such as AES-256 and TLS 1.3, and regularly audit encryption configurations. Torq can automate policy enforcement and integrate with encryption management systems to verify encryption coverage and trigger alerts for unprotected data assets.

9. Limit User Access with RBAC and Least Privilege

The principle of least privilege (PoLP) limits access rights for users to the bare minimum necessary. Overprivileged accounts are a goldmine for cybercriminals and a major source of internal risk.

Torq’s RBAC capabilities automate access provisioning, ensure only necessary permissions are granted, and continuously audit user roles. If access privileges drift over time due to role changes or misconfigurations, Torq can automatically flag or correct them, helping prevent lateral movement in case of compromise.

10. Monitor for Suspicious Behavior and Automate Alerts

Traditional alerting often leads to analyst burnout due to high volumes of low-fidelity alerts. Modern threats demand intelligent monitoring that can identify anomalies and respond in real time.

Torq’s multi-agent system continuously monitors systems for signs of compromise and suspicious behavior. When an anomaly is detected, it automatically triages the event, enriches it with context, and initiates workflows to investigate or contain the threat, without requiring human intervention. This reduces MTTD and MTTR, keeping your defenses agile and proactive.

Common Cyber Threats Every Organization Faces

To understand why these security best practices matter, consider some of today’s most pressing cyber threats:

Ransomware: Ransomware attacks encrypt critical data, demanding payment for restoration. Organizations must maintain backups, enforce patch management, and automate threat detection to prevent such attacks.
Phishing: Attackers trick employees into revealing credentials or downloading malware. Continuous security awareness training and automated phishing remediation significantly reduce phishing-related breaches.
Insider Threats: Whether intentional or accidental, insider threats pose significant risk. Implement strong RBAC policies and continuous user activity monitoring to quickly detect suspicious behavior.
DDoS (Distributed Denial of Service): Attackers overwhelm your network or services with traffic, disrupting operations. Deploy firewall protections, traffic monitoring, and automated mitigation responses to maintain availability.

Hyperautomate Your Cybersecurity Best Practices with Torq Hyperautomation

Even the most extensive cybersecurity best practices can fall short without consistency, speed, and scalability. That’s where Torq Hyperautomation steps in.

Torq automates every layer of your security operations — from detection to remediation — without writing a single line of code. Whether you’re enforcing MFA, orchestrating real-time phishing response, or managing RBAC policies across hybrid environments, Torq executes it all with precision and speed.

Torq’s Hyperautomation platform empowers organizations to convert cybersecurity best practices into always-on, fully orchestrated workflows. Our agentic AI capabilities, including our multi-agent system led by Socrates, detect, triage, and respond to alerts instantly, without flooding your team with noise.

This means your security analysts spend less time on repetitive triage and more time focused on high-impact, strategic initiatives. And with a vast library of integrations and workflow templates, you can implement sophisticated security controls faster than ever.

Build a Stronger, Smarter Security Posture

Cybersecurity threats are growing rapidly, but so are the solutions to fight them. Adopting these cybersecurity best practices will strengthen your organization’s defenses against modern threats. However, manually managing every aspect of security is unsustainable.

Torq Hyperautomation gives your organization an edge by transforming security best practices into streamlined, automated operations. From employee training and endpoint protection to real-time threat response and compliance reporting, Torq ensures that your security posture isn’t just strong; it’s intelligent, adaptable, and future-ready.

Ready to strengthen your cybersecurity posture with Torq?

Get a Demo

The Multi-Agent System: A New Era for SecOps

By Torq

May 28, 2025

8 Minute Read

3 Ways Torq HyperSOC Reduces MTTR with AI and Automation

By Bob Boyle

May 22, 2025

10 Minute Read

The SOC Efficiency Challenge

Reducing MTTR is a top priority for SOCs, yet many struggle to make meaningful progress. The root of the problem lies in legacy SOC environments’ outdated, manual, and disconnected nature.

If you’ve spent time in a SOC, these pain points are familiar:

Manual investigations slow everything down: Over half of security teams struggle with false positives and data overload. Analysts spend valuable time pivoting between tools, manually gathering context from logs, threat intel feeds, and asset databases. This “swivel-chair” approach introduces friction at every stage of the investigation.
Siloed tools don’t talk to each other: Most SOCs operate across dozens of disconnected platforms — EDR, SIEM, IAM, CMDB, ticketing, and more — without unified visibility or shared context. This makes correlating events and making informed decisions harder and slower.
High alert volume leads to fatigue: Teams receive thousands of alerts daily, many of which are false positives. Sifting through the noise to find true threats overwhelms even the most seasoned analysts, increasing the time it takes to detect and resolve incidents.
Disjointed shift handoffs cause delays: Without standardized processes or automated case management, investigations are often paused or reset between analyst shifts. Critical details get lost, increasing downtime and dragging out resolution timelines.
Inconsistent processes and tribal knowledge: The lack of documented workflows and reliance on individual expertise mean response varies from one analyst to the next. This inconsistency increases mean time to detect (MTTD), mean time to investigate (MTTI), and ultimately mean time to resolve (MTTR).
Delayed escalation and decision-making: Analysts often wait for senior approval before containing threats, primarily when procedures aren’t codified. This slows the response and allows attackers to move laterally or escalate privileges.

These pain points slow your team’s reaction times and increase risk. But these barriers disappear when Hyperautomation, AI, and smart case management are unified.

Why Reducing MTTR Is the Key to SOC Efficiency

What is MTTR in Cybersecurity?

MTTR (Mean Time to Resolution) measures the average time it takes to detect, investigate, contain, and fully resolve a security incident — from when it’s identified to when it’s no longer a threat. It’s one of the most critical KPIs for security operations because it directly reflects how quickly a SOC can respond to threats and minimize damage.

Related metrics include:

MTTD (Mean Time to Detect): How long it takes to identify that an incident has occurred.
MTTI (Mean Time to Investigate): The time required to assess and understand the scope and severity of an incident.
MTTR (Mean Time to Resolution): The full incident lifecycle — detection through response and resolution.
MTTx: A flexible term for any “mean time to X” metric, such as mean time to contain, recover, or respond.

High MTTR leads to longer dwell times, greater risk exposure, and higher operational costs. Reducing MTTR means:

Stopping attackers before lateral movement or data exfiltration
Limiting downtime and business disruption
Giving analysts time back to focus on proactive defense

Reducing MTTR is a direct path to stronger security, happier analysts, and a more efficient SOC.

How AI, Hyperautomation, and Case Management Can Reduce MTTR

Torq HyperSOC is an autonomous, cloud-native security operations platform designed to reduce MTTR by eliminating manual bottlenecks across the incident lifecycle. Built on the Torq Hyperautomation platform, HyperSOC combines:

Agentic AI (Socrates) to autonomously triage, investigate, and resolve threats
No-code/low-code orchestration for rapid integration with existing tools across SIEM, EDR, IAM, and SaaS environments
Natural language processing (NLP)-powered automation for dynamic workflows, smart case management, and intuitive analyst interaction

How Automation Speeds Detection, Investigation, and Response

Every minute matters in security. HyperSOC uses automation to minimize time spent on repetitive and manual tasks, which directly reduces MTTR.

Automated threat detection eliminates wait time for analyst triage.

Instant data correlation reduces downtime spent stitching logs, alerts, and asset context.

Hands-free auto-remediation triggers the correct response playbooks based on the threat type.Audit-ready documentation is generated in real time, ensuring compliance and traceability.

Use Case #1: Neutralize a Reverse Shell Command & Control (C2) Attack

This example shows how Torq HyperSOC reduced MTTR from hours to under two minutes by automating detection, investigation, and containment, without human intervention.

Threat detection and autonomous response: When a Ruby-powered reverse shell (courtesy of njRAT) targeted an EC2 Linux instance, Socrates got to work. As Torq’s AI SOC Analyst, Socrates detected anomalous process behaviors and network connections, flagging the reverse shell command within seconds.

Real-time enrichment: Without waiting for analyst input, Socrates quarantined the EC2 host. The platform harvested file hashes, process trees, and destination IPs, then enriched them via threat intel feeds and internal CMDB lookups.

AI-generated reporting: Through a deep understanding of the environment and analysis of the remediation runbook associated with the detected use case, Socrates autonomously killed the malicious process in its tracks before the bad actor was able to spread laterally, exfiltrate sensitive data, or cause any further damage. In under two minutes, the HyperSOC dashboard included an AI-generated incident report with prioritized next steps and detailed documentation of every AI-driven action taken.

Result: The threat was detected and neutralized without manual intervention, reducing MTTR and allowing analysts to move on to higher-priority tasks.

The threat was detected and neutralized without manual intervention, allowing analysts to move swiftly to higher-priority tasks. — Torq HyperSOC™ detected and neutralized a Ruby-based njRAT attack on an EC2 Linux instance in under two minutes.

Use Case #2: Reduce MTTR with Automated MITRE ATT&CK Tagging

Manually identifying and tagging MITRE ATT&CK tactics, techniques, and procedures is time-consuming.

Automatic TTP mapping: Socrates can streamline this process by automatically linking and tagging threats with relevant MITRE ATT&CK tactics, techniques, and procedures (TTPs).

Runbook recommendations: The AI Agent parses case data, file hashes, process names, network connections, and behavior patterns, and distills them into discrete observables. Socrates cross-references each observable against the latest MITRE ATT&CK framework — pinpointing the primary tactic and related sub-techniques and procedures. For each matched TTP, Socrates auto-tags the case, links to relevant playbooks, and correlates with past incidents that used the same methods.

Automated scoring: Finally, the AI generates a concise report section that shows:

Tactic: TA0011 – Command and Control
Technique: T1219 – Remote Access Software
Procedure: njRAT reverse shell delivered via Ruby script on EC2 instance.
Confidence: 92%
Potential Impact: Successful execution of these TTPs can lead to unauthorized access and control of critical systems, leading to data breaches or disruptions.
Next Steps: Trigger the containment playbook, notify the Tier-2 SOC analyst team, and run a full asset sweep.

Result: Analysts no longer spend time manually tagging or correlating cases, which helps reduce MTTR and increase consistency across investigations.

Analysts no longer spend time manually tagging or correlating cases, which helps reduce MTTR and increase consistency across investigations. — Socrates auto-tagged MITRE ATT&CK TTPs for a reverse shell incident, cutting MTTR and surfacing next steps in seconds.

Use Case #3: Investigate and Close an Impossible Travel Alert in Minutes

Use Case #3: Investigate and Close an Impossible Travel Alert in Minutes

This case shows how Socrates cut MTTR from 20+ minutes to under three, replacing a manual investigation across multiple tools with a fully automated workflow.

Cross-platform checks: Okta flagged suspicious logins from Austria, Singapore, and Brazil for a single user within a 30-minute window, an impossible travel scenario indicating potential compromise.

Anomaly resolution: Socrates autonomously checked the user’s leave status in Workday and calendar systems. Next, Socrates messaged the employee on Slack, capturing their response directly into the case notes. Simultaneously, it enriched each login IP against external threat intelligence feeds, scoring them for risk and historical malicious activity.

Automated case closure: Socrates then compared the session details against the user’s normal behavior baseline to spot anomalies. Finally, because the user had confirmed the unusual travel and all IP reputations returned legitimate, Socrates marked the alert as a benign true positive, documented the reasoning, and closed the case.

Result: MTTR was reduced to three minutes, false positives were resolved autonomously, and analysts stayed focused on real threats.

This workflow took under three minutes, reducing MTTR and giving analysts hours back by eliminating manual checks and unnecessary escalations. — Socrates investigated suspicious Okta logins, cross-checked HR systems, messaged the user, and closed the alert autonomously.

What These Results Mean for Your SOC

The use cases above aren’t isolated wins — they represent a repeatable, scalable model for transforming your security operations. When you reduce MTTR through AI, Hyperautomation, and intelligent case management, your SOC becomes faster, more resilient, and dramatically more cost-effective.

Proving the ROI of MTTR Reduction

Reducing mean time to resolution doesn’t just make your SOC more efficient — it delivers measurable business value:

Faster resolution = less dwell time and downtime: The longer a threat lingers, the more damage it can do. By shortening the incident lifecycle, your team minimizes business disruption, data loss, and risk exposure.
Fewer escalations = less analyst fatigue: Automating repetitive tasks and low-risk decisions reduces the volume of escalations sent to senior analysts. That frees them up to focus on high-value investigations — and helps reduce burnout.
Higher accuracy = better threat outcomes: With real-time enrichment, contextual tagging, and autonomous decision-making, your SOC can respond more precisely, even under pressure. This leads to faster containment, fewer false positives, and stronger compliance reporting.

Operational resilience = higher ROI: SOCs that reduce MTTR gain more value from their existing tools and staff. You’re not just solving problems faster — you’re using fewer resources.

How to Start Automating Your SOC the Right Way

To reduce MTTR, you don’t need to rip and replace your entire tech stack. The best approach is incremental and targeted, focusing first on areas with high volume, low complexity, and high analyst fatigue.

Start by automating:

High-volume alert triage: Automatically enrich, correlate, and suppress low-risk alerts based on historical context and threat intelligence.
Repetitive enrichment tasks: Automated gathering of user context, asset data, geolocation, IP reputation, and vulnerability information can be done in seconds, not hours.
Access investigations and policy violations: Build workflows that verify unusual access events across IAM, HR, calendar, and communication platforms, then take action based on policy.

These aren’t theoretical benefits; they’re proof points from the frontlines of modern AI-powered SOCs. When the powers of Hyperautomation, AI, and intelligent case management are combined in Torq HyperSOC, your team moves smarter and faster.

Instead of being bogged down, analysts are empowered to lead, strategize, and scale across complex environments. That’s how you reduce risk, retain talent, and prove real value.

Want to see HyperSOC in action? Book a demo now — and don’t miss our Field CISO’s guide full of practical advice for building a more efficient SOC.

Get the Guide

The Best Threat Intelligence Tools & How to Automate Alert Enrichment with Torq

By Torq

May 21, 2025

11 Minute Read

What Are Threat Intelligence Tools?

Threat Intelligence (TI) tools are software and services that collect, enrich, analyze, and distribute information about cyber threats so security teams can detect, prioritize, and respond faster.

What Threat Intelligence Tools Do

Collect data: Ingests signals from OSINT, dark web sources, malware sandboxes, DNS/WHOIS, product telemetry, ISACs, and commercial vendor feeds to build a comprehensive threat picture.

Normalize and enrich: Standardizes formats, deduplicates indicators, and adds context — actor, campaign, TTPs, confidence, and sightings — so data is usable and trustworthy.

Correlate and score: Links indicators to behaviors using frameworks like MITRE ATT&CK and assign risk and confidence to drive prioritization.

Distribute intel: Pushes curated intelligence to SIEM, EDR, or SOAR via APIs and STIX/TAXII, often triggering automated playbooks.

Search and investigate: Lets analysts pivot across IPs, domains, and hashes, build campaign timelines, and track adversary infrastructure.

Report and measure: Provides dashboards, alerts, and takedown and mitigation guidance while tracking coverage and efficacy.

Threat Intelligence Tooling Categories

Feeds (Raw indicators): Continuous streams of IPs, domains, hashes, phishing kits, and C2 infrastructure.
Threat Intelligence Platforms (TIPs): Central hubs that aggregate sources, dedupe and score indicators, enable sharing, and orchestrate automation.
Vertical/Community intel: ISAC/ISAO groups that facilitate trusted, sector-specific sharing of timely threats and mitigations.
Managed TI services: Provider-run offerings where human analysts deliver curated, finished intelligence and advisory support.

4 Types of Threat Intelligence

Strategic (Board/CISO): High-level trends, risks, and business impact to inform investment and policy.
Operational (SOC/IR): Campaign-level insights — adversaries, infrastructure, and TTPs — translated into detections and response actions.
Tactical (Detections): Short-lived IOCs with confidence and expiry to feed blocklists and detection rules.
Technical (Artifacts): Low-level signatures and artifacts — YARA/Sigma rules, decoders, and malware I/O — used to research and codify detections.

While threat intelligence is vital for shifting from reactive to proactive security, most tools stop short of execution. They provide intel but don’t automate triage or incident response, leaving a critical gap in the security kill chain.

Why Threat Intelligence Alone Isn’t Enough

“Threat intelligence — while abundant — is frequently underutilized due to inconsistent application and a lack of objective analysis, keeping teams stuck in reactive mode.”

– SANS 2025 SOC Survey

High-quality threat intelligence is essential for modern security operations, but even the best intel feeds can only take you so far. Many SOC teams still struggle to operationalize that intelligence effectively, facing challenges such as:

Siloed data sources: Threat intel often lives in separate tools and feeds, requiring analysts to manually pivot between consoles to correlate indicators with events in their environment. This not only slows investigations but also risks missing connections entirely.
Alert fatigue from unverified IOCs: Raw intelligence feeds can produce an overwhelming volume of indicators of compromise (IOCs). Without automated context and verification, analysts are forced to triage a flood of alerts, many of which turn out to be irrelevant or false positives.
Slow MTTR due to manual processes: Even when malicious activity is identified, enrichment, prioritization, and incident response often rely on a series of manual steps. This delays containment, gives adversaries more time to act, and increases the likelihood of impact.

The missing link is security Hyperautomation: The ability to take incoming threat intelligence and enrich it in real time, validate it against your environment, prioritize based on risk, and execute the right response automatically.

With Hyperautomation in place, security teams can:

Instantly correlate threat intel with live telemetry from SIEM, EDR, IAM, and cloud security tools.
Automatically filter out low-confidence or irrelevant IOCs before they reach analysts.
Trigger pre-approved auto-remediation workflows such as blocking a domain, isolating an endpoint, or disabling a compromised account in seconds.

Threat intelligence is powerful, but it becomes truly operational when paired with automation. That’s how teams turn static data into actionable, measurable defense at machine speed.

The Power of Automated Alert Enrichment

Threat intelligence enrichment is the critical bridge between raw threat data and meaningful, actionable threat intelligence. It transforms a bare IOC or alert into a fully contextualized security event, giving analysts the information they need to make faster, more confident decisions.

Without enrichment, a malicious IP alert is just a red flag without a story. You know something might be wrong, but you don’t know:

Who controls the IP
When it was first reported as malicious
Whether it has been active in other attacks
If it’s currently interacting with your environment

With threat enrichment, those questions are answered instantly. You can see ownership, reputation scores, historical abuse records, and whether the threat currently targets your assets. This drastically reduces false positives, helps prioritize real threats, and accelerates triage, especially in high-volume SOC environments.

Real-Time Enrichment with Torq

Torq automates this process end-to-end, ingesting IOCs from virtually any source:

Open-source feeds like AbuseIPDB or AlienVault OTX
Commercial CTI platforms such as Recorded Future or CrowdStrike Falcon Intelligence
Internal telemetry from SIEM, EDR, IAM, and CSPM systems

Once ingested, Torq automatically enriches each IOC or alert with:

Threat intelligence lookups for risk scoring and category classification
WHOIS data to identify domain or IP ownership
GeoIP mapping for geographic attribution
Historical incident correlation to see if this IOC has appeared in past investigations

All of this happens without writing a single line of code, using Torq’s no-code/low-code visual builder.

Connecting Enrichment to Automated Response

Enrichment is all about enabling faster, more precise action. With Torq, once an alert is enriched, it can immediately trigger targeted, pre-approved response runbooks, such as:

Block malicious IPs or domains at the firewall or secure web gateway
Disable compromised accounts in IAM systems like Okta or Azure AD
Quarantine infected endpoints via EDR tools like CrowdStrike or SentinelOne
Notify analysts in Slack or Microsoft Teams with full, structured context for review

Because enrichment and incident response are linked in the same Hyperautomation workflow, there’s no waiting for an analyst to manually look up data before taking action — vulnerabilities are validated, prioritized, and remediated in near real time.

Real-World Use Cases: How Torq Elevates Your Threat Intelligence Stack

IOC-Triggered Triage

Scenario: A new malicious IP is published by Abuse.ch’s SSL Blacklist feed.

How Torq Handles It:

The IOC enters Torq through a scheduled or webhook-based integration with Abuse.ch.
Torq automatically enriches it with:
- Recorded Future for risk scoring and threat actor attribution.
- VirusTotal for file and domain associations.
- WHOIS and GeoIP for ownership and location details.
The enriched IOC is compared against SIEM and EDR telemetry to see if it’s active in your environment.
Based on the risk score and internal matches, Torq either:
- Auto-blocks the IP in your firewall and secure web gateway.
- Escalates the IOC to a case in Torq for analyst review.

Result: Threats are validated and acted on within seconds, without manual lookups or context switching.

Autonomous Response to High-Risk Alerts

Scenario: Correlated threat intel and internal detections reveal an active phishing campaign targeting corporate users.

How Torq Handles It:

The IOC feed from a commercial CTI provider flags multiple domains tied to a phishing kit.
Torq cross-references internal email gateway logs to confirm delivery attempts to specific users.
Upon confirmation, Torq executes automated actions:
- Revokes credentials in Okta or Azure AD for targeted accounts.
- Sends a Slack or Teams alert to affected users with security guidance.
- Updates the SIEM with an incident record for correlation and compliance.

Result: Compromised accounts are secured, and users are alerted before threat actors can exploit access.

Threat Intel + Phishing Detection

Scenario: A user reports a suspicious email via the company’s phishing reporting button.

How Torq Handles It:

The reported email is sent to Torq via Microsoft 365 Security or Proofpoint TAP integration.
Torq extracts sender domains, IPs, and embedded URLs.
Those indicators are checked against:
- External threat intel feeds like AlienVault OTX and Abuse.ch.
- Internal blocklists and historical case data in Torq.
If confirmed malicious, Torq:
- Quarantines the email for all recipients at the email gateway.
- Blocks the domain in the web proxy.
- Notifies the reporting user with a “verified malicious” confirmation.

Result: A single user report becomes a fully automated, organization-wide protection action.

Scalable Enrichment Without Developer Overhead

Scenario: The SOC wants to enrich all IOC feeds with cross-platform intelligence but lacks developer bandwidth.

How Torq Handles It:

An analyst drags and drops connectors for Recorded Future, VirusTotal, AbuseIPDB, and MISP into the workflow canvas.
Using Torq’s no-code visual editor, the analyst chains enrichment steps, scoring logic, and conditional response rules.
New threat intel feeds can be added in minutes, and workflows update automatically without engineering intervention.

Result: The SOC scales enrichment capabilities rapidly, integrating multiple TI sources and incident response actions without waiting on dev cycles.

Threat Intelligence Is Only as Good as the Action It Enables

Threat intelligence is the spark that ignites detection, but it’s the action you take with that intelligence that determines whether it prevents an attack or becomes just another line in a report. Without automation, even the most curated and timely feeds leave SOC teams drowning in manual triage, correlation, and remediation steps.

The challenge is operationalizing threat intelligence at machine speed, ingesting, validating, enriching, and acting on it in seconds, not hours. That requires an automation platform that connects intelligence sources directly to your detection, investigation, and response layers.

What to Look for in an Automated Threat Intelligence Stack

To fully realize the value of your threat intel, your automation stack should deliver:

Interoperability: Native integrations with SIEM, SOAR, EDR, firewall, email security, and CTI feeds so threat data flows seamlessly across tools.
Real-time enrichment: The ability to instantly enhance IOCs with reputation scores, geo-location, WHOIS data, historical activity, and related incidents, and feed that context back into detection and response systems.
Scalability: Capacity to process thousands (or millions) of IOCs per day without slowing down, whether from burst attack campaigns or ongoing intelligence streams.
No-code flexibility: The option for analysts to adapt, expand, or fine-tune workflows without relying on developer resources, so you can pivot quickly to new threats.

Why Torq Is Built for Modern Threat Detection

Torq’s Hyperautomation Platform turns raw threat intel into orchestrated action across your SOC. It’s designed to:

Automate at scale with autonomous runbooks that can process and act on high IOC volumes without analyst intervention.
Integrate instantly using agentless, native connectors to 1,000+ tools — from threat intel platforms like Recorded Future, VirusTotal, and MISP to your SIEM, EDR, and firewall stack.
Enable SOC agility through a visual no-code/low-code editor and AI workflow building, so analysts can build or modify enrichment and incident response workflows in minutes.
Drive immediate outcomes — blocking malicious IPs, quarantining emails, disabling compromised accounts, or alerting security analysts— all triggered by enriched intel in real time.

With Torq, threat intelligence isn’t just data; it’s a live signal that moves seamlessly from detection to decision to remediation, without manual processing delays.

Categories of Threat Intelligence Tools Cybersecurity Teams Rely On

Category	Workflow Stage	Purpose	Where Torq Fits	Example Tools
Threat Data Aggregators & Feeds	Collect → Normalize	Centralize raw intel from OSINT, dark web, vendor feeds	Ingests IOCs, auto-dedupes, normalizes to STIX/TAXII, applies TTL, routes to SIEM/EDR with guardrails	AlienVault OTX, Abuse.ch, Recorded Future
Threat Analysis & Correlation	Enrich → Analyze → Hunt	Link IOCs to malware families, campaigns, actors	Automates enrichment and correlation, captures analyst pivots as runbooks, pushes TTPs back to detection	ThreatConnect, Anomali, VirusTotal
Alert Prioritization & Risk Scoring	Triage → Prioritize	Rank alerts by risk and asset criticality	Auto-escalates high-risk alerts, auto-suppresses noise, learns from analyst feedback	Splunk ES, Cisco SecureX, Exabeam
Threat Intelligence Sharing & Collaboration	Share → Collaborate → Govern	Distribute intel across teams & communities	Auto-ingests shared intel, validates, enriches, deploys, feeds outcomes back to community	MISP, OpenCTI, ISAC Portals

Operationalize Threat Intelligence Tools with Torq

Great threat intelligence tools surface what’s out there; Torq turns that signal into outcomes. By ingesting feeds and TIPs, normalizing to common schemas, enriching with WHOIS/GeoIP/reputation, and correlating against your SIEM/EDR/IAM telemetry, Torq’s no-code Hyperautomation moves from detect to resolve in seconds — automatically.

Pre-approved playbooks block domains and IPs, isolate endpoints, revoke access, and notify stakeholders in chat, all with full audit trails and role-based control. The result: lower MTTR, less downtime, fewer manual escalations, a stronger security posture, and a calmer on-call.

If you’re investing in threat intelligence tools but still triaging by hand, you’re leaving value on the table. Pair your intel with automation that’s interoperable, explainable, and scalable so every high-confidence indicator translates into immediate, governed action.

Ready to turn intel into impact? See how Torq can help make your SOC more efficient.

Get the Guide

FAQs

What are examples of threat intelligence?

Examples of threat intelligence include malicious IP addresses, suspicious domain names, file hashes associated with malware, phishing email indicators, and known threat actor infrastructure. More advanced threat intelligence also includes TTPs (tactics, techniques, and procedures) tied to specific threat actors.

What are the four types of threat intelligence?

Strategic: High-level trends and risks for executive decision-making.
Tactical: Information on adversary TTPs for defensive planning.
Operational: Intel on active campaigns and imminent threats.
Technical: Raw indicators like IOCs for detection and blocking.

What are six major sources of cyber threat intelligence?

Open-source threat feeds (e.g., AlienVault OTX, Abuse.ch)
Commercial CTI platforms (e.g., Recorded Future, Mandiant Advantage)
Security product telemetry (SIEM, EDR, XDR)
Dark web monitoring
Industry sharing groups (ISACs/ISAOs)
Government or law enforcement alerts (e.g., CISA, FBI)

What are the best free cyber threat intelligence feeds?

Popular free feeds include AlienVault OTX, Abuse.ch, MalwareBazaar, URLhaus, and various ISAC community feeds. While valuable, they should be supplemented with commercial feeds and automated enrichment for best results.

What does threat intel do?

Threat intelligence helps security teams understand, anticipate, and respond to cyber threats by providing context, patterns, and IOCs that inform detection and incident response workflows.

What are feeds in cybersecurity?

A threat feed is a continuously updated stream of IOCs and threat data that can be ingested into cybersecurity tools like SIEMs and SOAR platforms to enhance detection.

What are examples of threat feeds?

Examples of threat feeds include IP blocklists, malicious domain lists, malware hash databases, and phishing URL repositories.

What is threat feed vs threat intelligence?

Threat feed: A raw data stream containing IOCs.

Threat intelligence: Enriched, analyzed, and contextualized data derived from one or more feeds, ready to be used in decision-making and automated workflows.

CISOs’ Unconventional Criteria for Evaluating AI SOC Analysts

By Noam Cohen

May 19, 2025

10 Minute Read

Noam Cohen is a serial entrepreneur building seriously cool data and AI companies since 2018. Noam’s insights are informed by a unique combination of data, product, and AI expertise — with a background that includes winning the Israel Defense Prize for his work in leveraging data to predict terror attacks. As the Head of Artificial Intelligence at Torq, Noam is helping build truly next-gen AI capabilities into Torq’s autonomous SOC platform.

Still obsessing over compliance certifications and data volumes when choosing your AI SOC analyst? You might as well be that guy at the dealership kicking tires and demanding V8 specs while ignoring the self-driving capabilities.

Today’s CISO battlefield isn’t won with yesterday’s metrics. While AI security vendors sell you on training corpus size and customization options, you should be demanding zero-day detection without signatures and unified threat visibility.

Let’s be brutally honest: the blistering pace of AI innovation means your current AI SOC evaluation checklist is obsolete. GenAI marked an inflection point; now, agentic AI is completely disrupting SecOps. This means the real competitive edge lies in capabilities your procurement team isn’t even asking about.

So, what should CISOs look for in an AI SOC analyst? Below, we break down 8 key capabilities that you might not have considered but are crucial to ensure AI trust and effectiveness in your SOC.

What to Look for in an AI SOC Analyst Evaluation

1. AI That Simplifies and Communicates Context

Look for: Next-gen AI for the SOC that shows sophistication beyond query-response models, demonstrating a nuanced understanding and delightful communication of organizational context, ongoing security incidents, and specific scenarios.

Rather than summarizing in a generic “TL;DR” format, the AI should communicate about logs, case artifacts, and indicators of compromise (IOCs) through a cybersecurity-oriented UI that highlights key information for the specific security context.

Ask:

Can the AI maintain contextual continuity across analyst shifts and SOC handoffs?
How does the chat UI maintain context for the user when referencing information-heavy items like logs and cases?
Does the AI have different user views for summarizing actions, IOCs, and alerts?
Where can I embed our knowledge and policies to guide the AI’s interactions?

General example:

AI SOC Evaluation example: Example: simplified context communication — General example showing how a smart reference summarization popup from Arc (The Browser Company) helps users quickly understand selected text or an entire webpage without leaving their current browser.

2. AI for the Entire Team

Look for: Practical AI capabilities mapped explicitly to real-world SOC workflows and use cases.

The AI SOC analyst should do the actual, gritty tasks your SOC team performs daily — from initial triage to investigating alerts, hunting for threats, and remediating problems. This isn’t about general intelligence; it’s about directly supporting actual analyst workflows from end to end. If you use a multi-agent system (MAS), the AI SOC analyst should act as an OmniAgent to coordinate and collaborate with multiple specialized AI agents to accomplish these complex security goals.

Ask:

What analyst-level jobs does the AI accelerate (e.g. query writing, unstructured enrichment, and response recommendations)?
How does the AI SOC agent accelerate threat hunting and detection engineering through intelligent hypothesis generation?
Is the system capable of auto-healing errors in security workflows the way a good security engineer can?

General example:

Example of AI for cross-functional teams — *General example showing how Gemini’s Gem store features different chatbots for Marketing, Sales, and Developers.*

3. AI That Explains What It’s Doing

Look for: AI that grounds its findings and recommendations in clear, structured explanations showing its sources.

CISOs increasingly prioritize “explainability” in AI decisions as a pragmatic imperative for achieving cognitive alignment between the AI SOC analyst and the human security team. To foster trust, adoption, and effective action, your security team must have a line of sight into the AI’s reasoning, not just its conclusions.

Ask:

Does the AI SOC analyst clearly explain why particular security events are flagged or escalated?
How easily can human analysts validate or challenge the AI’s recommendations? For instance, can they request source links, exact quotes, or highlighting?
Do we have visibility into the AI agent’s self-critique step?
What validation guardrails does the AI implement?

General examples:

Example of AI that explains what it's doing — *General examples showing how two AI models show the data it relies on. Perplexity shows a snippet of the source while NotebookLM highlights the exact sentence it used from the source.*

4. AI That’s Easy to Interact With — Without Training

Look for: A SOC-specific user interface that is genuinely intuitive, innovative, and frictionless and that directly enhances analyst productivity, retention, and job satisfaction.

Even the most powerful AI can be hampered by a clunky or difficult interface, undermining your team’s effectiveness and morale and discouraging AI adoption. A truly innovative interface should feel natural to use and streamline workflows, not add complexity or friction to processes. An intuitive design enables analysts of any level to quickly access insights and take action without specialized skills or knowledge.

Ask:

How much do our human analysts need to be familiar with AI hacks and general prompt engineering, such as knowing when to use deep search options, ask for a specific data format, or open a new conversation thread?
Does the AI SOC analyst support conversational SIEM queries and natural-language threat exploration?
How does the AI communicate its planning and thinking process?
In autopiloting, can I interrupt the investigation before the AI is done?

General example:

AI SOC Evaluation: example of AI that is intuitive to use — *General example showing how Perplexity creates a simpler user experience by auto-choosing the model according to its research, rather than making the user choose a model by task/prompt.*

5. AI That Helps You Get Ahead

Look for: An AI SOC analyst that doesn’t only react to known threats but proactively guides SOC teams towards improving security posture and operational effectiveness.

Think of your top analysts — the ones who are always one step ahead, anticipating your team’s needs and suggesting improvements without being asked. Agentic AI that performs at this advanced level can act as a virtual extension of your team, identifying weaknesses and suggesting optimizations to elevate your security operations.

Ask:

Can the AI SOC analyst proactively detect and suggest SOC operational improvements, such as recommending repetitive manual processes that are ripe for automation?
Can it automatically correlate cases with incident history and recommend improvements?
Has your AI ever caught a missing step in its instructions and fixed it (or asked about it) before executing?
Can the AI automatically tag and store important information from your interactions that can help in future cases?
Will the AI suggest changes to the detection rules, workflows, or playbooks? How often does your AI flag inefficiencies in workflows?

General example:

Example of AI that proactively recommends optimizations — General example of ChatGPT maintaining context after you’ve told it that you are an AI product manager in San Francisco. When asking it to brainstorm messaging for a social post celebrating an achievement, ChatGPT already knows where to start.

6. AI That Understands What You Really Want (and Can Figure Out How to Do It)

Look for: Deterministic, agentic AI that understands how to break a user intent into multiple tasks, which may require different execution plans.

Good AI gets a task and starts working. Great AI first looks for communication gaps, understands the goal, and asks for more instructions when needed. Ideally, the user shouldn’t have to think like the AI to ensure the AI grasps their intent — the AI should understand how the user thinks and ask clarifying questions when needed.

A structured execution scheme reduces ambiguity and improves the accuracy of the AI’s planning and orchestration, eliminating the likelihood of the AI agent skipping steps, going out of order, selecting incorrect tools, or misinterpreting instructions.

Ask:

When I give the AI a vague or complex instruction, does it ask clarifying questions — or just charge ahead?
How does it use screens, user information, and past sessions to better understand the user’s specific intent?
Can your AI break down a high-level goal (‘Investigate this alert’) into a sequence of logically ordered tasks — and tell you why?
Can your AI explain its execution plan in plain language before it starts and adjust if you push back?

General example:

AI SOC Evaluation: Example of AI that asks clarification questions — *General example showing how ChatGPT asks clarification questions before building a report in Deep Research.*

7. An AI Assistant That You Don’t Need to Babysit

Look for: Agentic AI capable of autonomously chaining together multiple actions without constant human prompts.

Your human analysts don’t want to click through 10 steps every time they need the AI to take action. While human oversight of critical decisions is important, to efficiently investigate an alert end-to-end and even initiate containment, an AI SOC analyst must be capable of independently stringing together a sequence of relevant subtasks — like log collection, enrichment, reverse engineering, and containment suggestions — in pursuit of a high-level goal.

Ask:

Can the AI SOC analyst complete a multi-step investigation with one high-level instruction?
Can the AI write and execute deterministic workflows when needed?
Does it pause and check with human analysts before executing sensitive tasks (e.g., blocking users or IPs)?
When given a high-level goal or non-playbook scenario, does the AI independently decide which steps to take and in what order?
How does the AI identify when not to act — and escalate to a human when it hits a confidence or authority threshold?

General example:

AI SOC Evaluation: Example of AI that defines when it needs to loop humans in — *General example of how Intercom’s Fin interface defines the moments where a human needs to be looped into the convo.*

8. AI That Gets More Helpful Through Human Feedback

Look for: An AI SOC analyst that continuously learns and improves by observing and incorporating feedback from human analyst behavior.

The best AI SOC analysts learn from human analyst behavior to become more effective and accurate over time. Think of it as shaping the ideal analyst that shadows your team, watches how they triage alerts, write queries, and handle false positives — and gets smarter with every interaction.

Human analysts should be able to fine-tune and correct AI as threats evolve rather than treating it as a black box. In practice, features like thumbs-up/down ratings, interactive retraining, or the ability to override AI decisions make the human–AI loop tighter and more effective.

Ask:

How does the AI SOC analyst adapt based on human analysts’ corrections or preferences over time?
Can I adjust the AI’s prioritization or response style via feedback?
How can the user flag a successful conversation with the AI to make future sessions easier and more effective?
Can you review and audit what the AI has learned from your team?

General example:

AI SOC Evaluation: Example of AI that continuously improves — *General example showing how Cursor’s Coding Rules feature helps developers continuously improve and adapt their preferences using natural language.*

Next-Gen AI for the SOC is Here — Are You Ready?

Don’t be the security leader who marvels at a shiny paint job while ignoring the revolutionary engine. When evaluating AI SOC analysts, focus on explainable intelligence, seamless integration into your team’s workflow, and deterministic AI that can independently plan and orchestrate all of the actions required to complete a high-level goal from end to end.

Finding an AI SOC analyst that truly understands context, empowers your analysts, and acts with proactive autonomy will ensure you’re not just keeping up with the latest tech but investing in a force multiplier for your security team.

Get the AI or Die Manifesto to learn strategic considerations, get insights from a CISO, and learn red flags and more questions to ask for an AI SOC evaluation.

Get the Manifesto

Contents

What is Attack Surface Management (ASM)?

Challenges of Traditional Attack Surface Management

3 Keys to Effective ASM

How Automated Attack Surface Management Works

Asset Discovery

Exposure Monitoring

Contextual Alerting

Automated Remediation

6 Benefits of Hyperautomated Attack Surface Management

Real-Time Visibility Across All Environments

Reduced Risk from Shadow IT and Misconfigurations

Fewer False Positives Thanks to Contextual Intelligence

Dramatically Shorter Time to Detect and Respond

Always-On Security Posture, Not Periodic Snapshots

Closed Loop from Detection to Resolution

Attack Surface Management Implementation: 4 Best Practices

How Torq Hyperautomation Powers End-to-End Attack Surface Management

Case Study: How Deepwatch Scaled Global Attack Surface Coverage with Torq Hyperautomation

Real Security Use Cases Powered by ASM Automation

Hyperautomate Your Attack Surface Management with Torq

FAQs

Related Articles

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

Automating MITRE ATT&CK Analysis with Torq Socrates

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

Contents

What Is SecOps Automation?

Traditional SecOps Is Broken

Why Lean Teams Need SecOps Automation

Five Ways Automated SecOps Helps Level the Playing Field

1. Phishing

2. Threat Intelligence Enrichment

3. Incident Response

4. Vulnerability Management (VM)

5. Identity and Access Management (IAM)

SecOps Automation = Big Results for Lean Teams

Torq: The Leading Platform for SecOps Automation

What SecOps Automation Looks Like

Check Point

Global Retailer

Lennar

Scale Your Security Without Scaling Your Team

Related Articles

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

Automating MITRE ATT&CK Analysis with Torq Socrates

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

Contents

What is the Vulnerability Management Lifecycle?

The 6 Steps of Vulnerability Management Lifecycle You Can Automate Today

Step 1: Asset Discovery and Vulnerability Assessment

Step 2: Vulnerability Scanning and Detection

Step 3: Risk-Based Vulnerability Prioritization

Step 4: Remediation and Patch Deployment

Step 5: Validation and Continuous Monitoring

Step 6: Reporting and Improvement

Visualizing the Automated Vulnerability Management Workflow

How Torq’s No-Code, Agentic AI Transforms VM

Reclaim Time. Reduce Risk. Automate Everything.

Related Articles

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

Automating MITRE ATT&CK Analysis with Torq Socrates

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

Contents

Why Cybersecurity Frameworks Matter

12 Common Types of Security Frameworks in 2025

How to Choose a Security Framework

How to Navigate Security Framework Challenges with Torq

Integration with Existing Systems

Budget Constraints

Evolving Threat Landscape

Ensuring Compliance and Audits

Why Torq?

Operationalizing Security Frameworks with Hyperautomation

Make Cybersecurity Frameworks Work for You

Related Articles

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

Automating MITRE ATT&CK Analysis with Torq Socrates

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

Contents