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

By Torq

July 3, 2025

9 Minute Read

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

Cloud-Native Security 101

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

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

What is Cloud-Native Security?

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

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

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

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

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

Manual Cloud Security is Broken: Key Challenges

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

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

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

5 Benefits of Cloud Security Automation

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

1. More Efficient Operations

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

2. Ensure Compliance

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

3. More Accuracy

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

4. More Consistency

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

5. Scalability

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

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

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

1. Identity and Access Management (IAM)

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

2. Automated Threat Hunting

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

3. Cloud Security Posture Management (CSPM)

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

4. Email Security

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

5. Self-Service Chatbots

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

6. Incident Response Automation

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

7. Application Security Automation

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

8. Phishing Detection and Response

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

9. Continuous Vulnerability Management

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

10. Threat Intelligence Enrichment

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

11. Suspicious User Behavior

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

12. Sensitive Data Access Controls

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

Hyperautomation: The Future of Cloud Security Automation

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

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

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

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

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

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

Cloud-Native Security Automation in Action: Torq + Wiz

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

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

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

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

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

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

Don’t Let Manual Security Hold You Back

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

Go all in with Torq Hyperautomation.

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

By Bob Boyle

June 24, 2025

6 Minute Read

Watch the on demand demo

How Wiz Defend Alerts Flow into Torq

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

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

How Wiz Finds and Detects Cloud Threats

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

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

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

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

Prioritized, Correlated, and Automated Cloud Threat Detection

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

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

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

What Gets Sent to Torq

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

How Socrates Automates and Orchestrates the Cloud Threat Response

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

Step 1: The Wiz Alert Becomes a Torq Case

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

Step 2: Socrates Begins Enrichment and Investigation

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

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

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

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

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

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

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

Step 4: Automatic Post-Incident Reporting

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

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

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

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

Why Torq is the Definitive Automation Tool for Your Wiz Environment

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

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

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

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

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

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

See Wiz Defend and Torq HyperSOC in action together.

The Top 3 Hyperautomation Use Cases for Torq POCs

By Torq

June 16, 2025

5 Minute Read

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

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

Hyperautomation: A SOC Must-Have

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

In the SOC, this means:

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

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

1. Endpoint Detection and Response

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

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

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

EDR Hyperautomation in Action: Torq and SentinelOne

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

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

2. Email Security

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

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

With Torq, you can:

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

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

Email Security Hyperautomation in Action: Torq and VirusTotal

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

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

3. Identity and Access Management (IAM)

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

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

Integrate Torq with your IAM, and you can:

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

IAM Hyperautomation in Action: Torq and Okta

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

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

Fast, Scalable Results… In Days

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

Our customers routinely:

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

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

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Squish the Phish: 6 Automated Phishing Response Strategies

By Torq

June 12, 2025

11 Minute Read

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

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

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

Manual Phishing Triage: A Losing Battle for SOC Teams

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

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

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

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

What is Automated Phishing Response?

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

6 Hyperautomated Phishing Response Strategies and Tactics

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

1. Perimeter Defense: Hardening the Email Gateway

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

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

Key tactics:

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

2. Identity and Access Control: Protecting Your People

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

Key tactic:

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

3. Endpoint Security: Containing the Impact

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

Key tactic:

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

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

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

Key tactics:

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

5. Data Protection & Incident Response: Minimizing the Damage

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

6. Continuous Improvement: Learning from Every Attack

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

Key tactic:

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

Example Automated Phishing Alert Analysis Workflow in Torq

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

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

Case Study: Lennar Cuts Phishing Resolution from Hours to Minutes

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

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

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

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Win the Phishing War with Automated Phishing Response

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

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

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

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

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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.

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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.

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The Multi-Agent System: A New Era for SecOps

By Torq

May 28, 2025

8 Minute Read

Three SOC Threats Solved in Minutes with Torq Hyperautomation

By Bob Boyle

May 22, 2025

5 Minute Read

The SOC Efficiency Challenge

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

Alert fatigue: Over half of security teams struggle with false positives and data overload.
Endless tickets: Legacy ticket systems and disjointed shift handoffs bog down response times.
Manual swivel-chairing: Analysts lose precious hours jumping between tools and logs.
Manual enrichment: Manually pulling threat intel and context is a major time-sink.

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.

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

When a Ruby-powered reverse shell (courtesy of njRAT) targeted an EC2 Linux instance, Socrates got to work. As Torq HyperSOC’s Omniagent, Socrates detected anomalous process behaviors and network connections, flagging the reverse shell command within seconds.

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.

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, allowing analysts to move swiftly to higher-priority tasks.

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. Socrates streamlined this process by automatically linking and tagging threats with relevant MITRE ATT&CK tactics, techniques, and procedures (TTPs).

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 not just the primary tactic but also 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.

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

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.

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.

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: This workflow took under three minutes, reducing MTTR and giving analysts hours back by eliminating manual checks and unnecessary escalations.

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.

You Wanna See Some Real Speed?

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 doesn’t just move faster; they move smarter.

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.

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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.

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The Future of Retail Cybersecurity: SOC Automation

By Bob Boyle

May 12, 2025

6 Minute Read

Retail companies are high-value targets for cybercriminals. With sprawling infrastructures, complex supply chains, and large amounts of customer data, retailers are a goldmine for bad actors. In 2024, the retail sector accounted for 24% of all cyberattacks — more than any other industry. The average cost of a data breach in retail rose to $3.28 million.

Meanwhile, security teams in the retail sector face increasing pressure to maintain uptime, protect consumer data, and streamline operations across global environments. This is where security Hyperautomation comes in.

Below, we explore key retail cybersecurity use cases for security Hyperautomation and spotlight how a fashion retail giant used Torq to cut ticket response times and scale SOC operations across global markets.

Why Retail Cybersecurity Teams Need SOC Automation

Retail has become one of the most targeted industries, accounting for one in four cyberattacks. Phishing, ransomware, and credential theft are the leading threats driven by attackers looking to exploit high volumes of customer data and payment information.

The rise of e-commerce (84% of consumers now shop online) and global retail operations has dramatically expanded the attack surface. Add distributed teams and ever-tightening compliance demands — and it’s no wonder retail cybersecurity processes are struggling to keep up.

Top retail SOC challenges include:

High alert volumes with limited analyst headcount
Manual ticket handling and case management
Access and identity control challenges
Customer service expectations and compliance demands

SOC automation is the engine behind this transformation, powered by Torq Hyperautomation™. By leveraging specialized AI Agents, Torq Hyperautomation helps retailers meet these security challenges: eliminating repetitive work, accelerating incident response, and gaining visibility across global environments — all without needing to rip and replace their security stack.

Top Retail Cybersecurity Challenges Solved by Hyperautomation

Below are the top use cases being Hyperautomated by Torq’s retail cybersecurity customer base, along with real-world examples of the workflows they have built.

1. Security Case Management

Automate the ingestion and processing of security incidents from Wiz. For “open” incidents, facilitate the creation and management of security cases with enriched data and actionable insights.

Workflow Steps:

Filter Wiz event data to select incidents with status ‘OPEN’ and severity ‘MEDIUM’, ‘HIGH’, or ‘CRITICAL’.
Transform data using Data Agent (AI-generated data transformation) operator to prepare it for case creation.
Create a new case with detailed incident information and links.
Add a quick action button to the case for advancing investigation phases based on the assigned runbook.
Extract indicators of compromise (IOCs) from incident alerts.
Populate observables within the security case with the newly extracted IOCs.
Update case severity based on incident severity and;
1. IF case severity changes to ‘CRITICAL’ or ‘HIGH’, change the case state to ‘TRIAGE’ and assign the case to the appropriate Tier-2 analyst.
2. IF case severity changes to ‘MEDIUM’ or ‘LOW’, change the case state to ‘TRIAGE’ and assign the case to Socrates, Torq’s AI SOC Analyst, for remediation.

2. Threat Intelligence Analysis

Automate the process of retrieving, analyzing, and managing threat intelligence data from CrowdStrike alerts, integrating AI Task Agent operator analysis, and updating case observables.

Workflow Steps:

List Crowdstrike case events and filter them based on [custom] criteria.
Create a session with CrowdStrike, retrieve alert details, and add to case.
Filter and process command line data using the AI Task Agent for analysis.
Extract and filter IOCs from alert details.
Compare new IOCs with existing case observables and identify unique ones.
Trigger a secondary nested workflow to check observables with threat intelligence (Workflow: Parallel execution — VirusTotal, Recorded Future, AlienVault).
Revoke the CrowdStrike session token and exit.

3. Automated Alert Enrichment

Aggregate endpoint information from SentinelOne, Axonius, and Azure AD to enrich security data and support threat intelligence efforts.

Workflow Steps:

Execute parallel processes to gather endpoint details from multiple sources.
Retrieve agent details from SentinelOne using an API call with specified parameters.
Extract key information from SentinelOne data using a JSON query.
Fetch device details from Axonius with a POST request and process the response to extract relevant attributes.
Generate an access token for Microsoft 365 and retrieve device information from Azure AD based on display name.
Compile the gathered data from SentinelOne, Axonius, and Azure AD using AI Task Agent to create a formatted summary of results.

4. Identity Access Request Management

Automate the process of requesting, approving, and granting temporary admin rights to Mac users across different store locations, ensuring compliance and proper authorization.

Workflow Steps:

Search for a Slack user’s email address based on the provided username.
If the email is found, prompt the user to provide a reason for requesting temporary admin rights on their Mac.
Depending on the user’s response, either proceed to find computers and store locations associated with the user’s email, or end the request.
If approved computers are found at the current location, ask the user to select which Mac they need admin rights on.
Request IT approval for granting admin rights.
If approved, temporarily grant admin rights on the selected Mac and notify the user.
After 15 minutes, revoke the admin rights and notify the user of the expiration.
If not approved, notify the user about the denial.

5. Daily Health Check

Automate the monitoring and management of security cases and detections, integrating with CrowdStrike and Microsoft Teams for comprehensive incident handling and communication.

Workflow Steps:

Query Crowdstrike events for specific states and severities, starting a custom SLA timer for each based on severity.
Retrieve the current date from each event; check if it is Monday, Wednesday, or Friday to proceed with further actions.
Search for unassigned detections and incidents older than specified hours/days.
Filter and process detection and incident data, collecting details for each unassigned detection and incident.
Summarize findings and send to Microsoft Teams.

Case Study: Fast Fashion Retailer Enhances SOC Efficiency with Hyperautomation

One of the world’s largest fast-fashion retailers was struggling under the weight of manual processes, siloed tools, and a legacy SOAR platform. With thousands of alerts coming in every day, their team was spending most of their time chasing false positives and combing through disjointed systems, leaving little time for meaningful response and strategy.

The retailer turned to Torq Hyperautomation to modernize their cybersecurity processes. With Torq’s intuitive workflow builder, analysts at all skill levels could build automations in minutes. Torq’s case management system and integrations with the team’s existing security solutions streamlined alert enrichment, triage, and response. They were also able to automate their just-in-time access across OS systems, cloud, and hybrid environments, ensuring a streamlined process for administrative workflows.

The retailer now solves end-user tickets in minutes and automates admin access across globally distributed teams. Read the full case study for more.

Get the Case Study

Contents

Cloud-Native Security 101

What is Cloud-Native Security?

Manual Cloud Security is Broken: Key Challenges

5 Benefits of Cloud Security Automation

1. More Efficient Operations

2. Ensure Compliance

3. More Accuracy

4. More Consistency

5. Scalability

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

1. Identity and Access Management (IAM)

2. Automated Threat Hunting

3. Cloud Security Posture Management (CSPM)

4. Email Security

5. Self-Service Chatbots

6. Incident Response Automation

7. Application Security Automation

8. Phishing Detection and Response

9. Continuous Vulnerability Management

10. Threat Intelligence Enrichment

11. Suspicious User Behavior

12. Sensitive Data Access Controls

Hyperautomation: The Future of Cloud Security Automation

Cloud-Native Security Automation in Action: Torq + Wiz

Don’t Let Manual Security Hold You Back

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

The Top 3 Hyperautomation Use Cases for Torq POCs

Squish the Phish: 6 Automated Phishing Response Strategies

Contents

How Wiz Defend Alerts Flow into Torq

How Wiz Finds and Detects Cloud Threats

Prioritized, Correlated, and Automated Cloud Threat Detection

What Gets Sent to Torq

How Socrates Automates and Orchestrates the Cloud Threat Response

Step 1: The Wiz Alert Becomes a Torq Case

Step 2: Socrates Begins Enrichment and Investigation

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

Step 4: Automatic Post-Incident Reporting

Why Torq is the Definitive Automation Tool for Your Wiz Environment

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

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