AI

Generative AI Cybersecurity: What It Is, What It Isn’t, and What Comes Next

By Torq
April 3, 2025
7 Minute Read
How can generative AI be used in cybersecurity?

Contents

Generative AI (GenAI) uses large language models (LLMs) to generate new content, synthesize data, and make context-aware decisions. In a cybersecurity organization, this means GenAI can help triage alerts, enrich threats, write playbooks, and assist analysts in real time.

But here’s the problem: Most SOCs are only scratching the surface of how generative AI can be used in cybersecurity. They’re using GenAI to summarize logs or generate scripts, which still requires human oversight and remains reactive. Did you know you could take your AI so much further? 

How Can Generative AI Be Used in Cybersecurity? 

GenAI is built on deep learning, a subset of machine learning, using large neural networks known as transformers. These transformers are trained on billions of data points and optimized to understand and mimic language, behavior, and structure.

Many GenAI systems are modeled after GPT (Generative Pretrained Transformer), which has learned how to respond to prompts in human-like ways by identifying patterns across massive data sets. 

Here are some ways Generative AI can be used in cybersecurity: 

  • Triage and enrichment: GenAI can automatically triage incoming alerts, enrich data from SIEM, EDR, and other sources, and generate clear, concise summaries. 
  • Threat detection: Trained on historical attack data and threat patterns, GenAI models can identify indicators of compromise (IOCs) and anticipate emerging tactics. 
  • Case documentation: Generative AI can produce case reports, threat timelines, and case summaries. These auto-generated insights reduce the need for manual documentation and simplify compliance reporting.
  • Threat hunting: Security analysts can use GenAI to query threat intelligence databases and data lakes using natural language prompts. This simplifies threat hunting workflows and empowers junior analysts to work at a higher level.
  • Workflow design: GenAI allows users to describe desired automations in natural language, which the system then converts into executable workflows. This eliminates the need for manual scripting and accelerates automation adoption across teams.

All of this helps analysts move faster — but it’s still reactive. It still requires humans in the loop. And it’s still just the beginning.

Challenges of Using Generative AI Alone

Without the right guardrails, GenAI in cybersecurity comes with serious risks:

  • Accuracy issues: GenAI can hallucinate. That means it can produce outputs that are confidently wrong. And in cybersecurity, that’s dangerous. An inaccurate summary of a threat, a misidentified IOC, or a fabricated correlation can derail an investigation, waste valuable analyst time, or worse, lead to improper remediation actions.
  • Data privacy: GenAI models are only as good as the data they’re trained on and how that data is handled. Feeding sensitive logs, incident data, or user information into GenAI without proper controls can lead to unintentional exposure of private data or regulatory violations. This is especially risky in regulated industries (finance, healthcare, etc.), where compliance failures come with heavy penalties.
  • Infrastructure overhead: Running LLMs requires serious computing, storage, and ongoing management. Even when using APIs from providers, the costs of integrating, fine-tuning, and securing the system can add up quickly. Without a well-architected platform, organizations often end up with fragile, expensive prototypes that don’t scale.
  • Threat actor access: You’re not the only one using GenAI. Threat actors are, too. From auto-generating phishing emails and malware variants to simulating voices or bypassing MFA with deepfakes, adversaries are industrializing their attacks with the same tools defenders are exploring.

This is why GenAI alone doesn’t cut it. It enhances the SOC — but it doesn’t free it. It still relies on humans to verify outputs, make decisions, and connect the dots. To truly transform security operations, you need more than content generation — you need contextual understanding, autonomous action, and real-time orchestration.

That’s why Torq goes beyond GenAI — combining it with agentic AI, Hyperautomation, and RAG-powered microagents to deliver a self-sustaining, intelligent SOC.

IDC: GenAI is Just the Beginning 

A recent IDC Spotlight Report reinforces what leading cybersecurity teams already suspect: Generative AI is only the beginning. The real transformation happens with agentic AI.

Although only 7% of organizations are using agentic AI today, 60% expect it to impact their SOC operations within the next 18 months significantly. The benefits are tangible: organizations embracing this shift are seeing a 50% reduction in mean time to detect (MTTD), automated response for 90% of alerts, and a 35% lower risk of major breaches.

Torq’s HyperSOC platform, powered by agentic microagents, delivers exactly the kind of automation and intelligence IDC highlights — and it’s already available today.

Torq’s Take: From Generative AI to Autonomous Cybersecurity

At Torq, generative AI in cybersecurity was just the beginning. We combine GenAI with agentic AI, Hyperautomation, and Retrieval-Augmented Generation (RAG) to create what no one else in the market has: a truly autonomous SOC.

Agentic AI: Thinks Like a Human Analyst

Agentic AI is the brain behind the operation. Torq’s multi-agent system, led by Socrates, understands context, makes decisions, and learns from experience. How? 

  • It uses semantic memory to understand relationships between threats, assets, and users.
  • It applies episodic memory to recall past incidents and resolutions.
  • It executes using procedural memory, adapting workflows in real-time based on its growing knowledge base.

Unlike GenAI, which waits for a prompt, agentic AI acts independently. It triages alerts, investigates root causes, and escalates only when necessary — moving SOCs from a human-in-the-loop to a human-on-the-loop approach. That means analysts step in only when they’re truly needed.

Hyperautomation: Machine-Speed Response Across Your Stack

Torq’s Hyperautomation engine seamlessly orchestrates your entire security ecosystem — across EDR, SIEM, IAM, email security, ticketing systems, cloud platforms, and beyond.

These AI-driven workflows:

  • Automatically isolate compromised endpoints
  • Revoke credentials and enforce MFA
  • Trigger alert suppressions and log escalations
  • Sync case updates across your tools of record

Hyperautomation connects all the dots — transforming detection into response with zero delay.

RAG-Enabled Microagents: Smarter Agents

Retrieval-augmented generation (RAG) enhances our specialized AI Agents with memory, precision, and real-time data access. Each microagent is trained on a specific domain, like investigation, remediation, or case management, and uses RAG to:

  • Pull in relevant threat intel, logs, and past incidents
  • Filter out noise and focus only on actionable data
  • Generate concise, accurate case summaries and recommendations

Think of them as subject matter experts inside your AI-powered SOC — each one armed with a knowledge base that updates every second. 

Defending Against GenAI Security Threats

Adversaries are using GenAI too — for phishing, deepfakes, malware variants, and more. That’s why Torq’s defense stack includes:

  • Behavioral detection: We spot the telltale signs of GenAI-generated attacks such as weird phrasing, impossible travel, or AI-crafted obfuscation. 
  • Automated response: The second a threat is flagged, Torq acts. Endpoints isolated. Credentials locked. Sessions terminated. Tickets opened. Teams alerted. No hesitation. 
  • Adaptive workflows: Attackers adapt. So do we… automatically. Torq’s workflows update themselves based on real-time threat intel, evolving tactics, and active defense insights. What was a one-off attack yesterday becomes a blocked pattern today.

Go Beyond GenAI Cybersecurity with Torq 

Generative AI in cybersecurity got us started — summarizing alerts, drafting playbooks, and answering questions. But Torq takes it further. 

With agentic AI, Torq’s platform went from suggestion to autonomous decision-making. With Hyperautomation, Torq executes those decisions instantly across your entire stack. And with RAG-enabled microagents, every move is precise, contextual, and based on real-time intelligence. 

That’s how you build a truly autonomous SOC.

Want to go beyond GenAI cybersecurity? Get the AI or Die Manifesto.

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Hyperautomation Insights

Unleash a Multi-SIEM Strategy with Hyperautomation

By Torq
April 3, 2025
5 Minute Read
SIEM integration in the modern SOC with Torq Hyperautomation

Contents

Industry analysts are calling it: Consolidation or collapse. 2024 saw Cisco’s $28B acquisition of Splunk, followed by Palo Alto Networks acquiring IBM’s QRadar SaaS assets, and LogRhythm and Exabeam’s merger to create an AI SIEM powerhouse.

We’ve seen this time and time again. Legacy security tools get acquired by larger tech companies as more efficient technologies come about. We saw it with antivirus, SOAR, and now SIEM. But here’s the twist: SIEM isn’t going away. Not even close.

Legacy SIEMs are deeply entrenched, housing massive volumes of regulated security logs and powering critical compliance workflows. The shift isn’t about replacing SIEMs — it’s about evolving how security teams use them.

What is a SIEM?

A SIEM (Security Information and Event Management) is a cybersecurity solution that collects, analyzes, and correlates security data from across an organization’s IT environment to detect threats, monitor activity, and support incident response and compliance. A SIEM can:

  • Ingest logs from sources like firewalls, endpoints, and applications
  • Correlate data to spot suspicious activity
  • Generate alerts for potential threats
  • Provide dashboards to help analysts investigate

What is SIEM Integration?

SIEM integration means connecting your SIEM to an orchestration and automation layer that amplifies its value without replacing it. Integrating an AI-driven Hyperautomation platform like Torq with your SIEM allows you to automate alerts, enforce policy-driven responses at machine speed, and orchestrate actions across your entire security stack.

The SIEM Struggle is Real

In The Evolution of the Modern Security Data Platform by Francis Odom and Josh Trup, legacy SIEM costs are largely indexed to data volume — meaning the more you ingest, the more you pay. This outdated pricing model is one of the biggest blockers to scaling detection across modern environments. 

SIEMs were also built for an on-prem world, not the cloud-native environments we operate in today. As more and more technologies shift to the cloud and SaaS sprawl grows, the volume of logs, events, and alerts increases exponentially.

Top SIEM challenges include: 

  • Excessive operational cost tied to ingestion and retention
  • Alert fatigue and time-consuming manual triage due to excessive noise
  • Tool sprawl and integration complexity
  • Difficulty scaling across hybrid and multi-cloud environments
  • Log retrieval penalties that make data migration expensive

Yet, despite these issues, most teams are not abandoning their SIEMs. Why? Because the cost and compliance risk of a rip-and-replace approach are even higher. This is where the multi-SIEM strategy emerges.

The Rise of the Multi-SIEM SOCs

Rather than choosing one SIEM to rule them all, forward-thinking SOC teams are embracing a multi-SIEM or hybrid SIEM architecture. Sometimes, this shift is born out of necessity, such as after mergers and acquisitions, where multiple SIEMs are bundled with the deal. At other times, it’s driven by a decline in trust in legacy SIEM innovation following industry shakeups and buyouts.

Legacy SIEMs charge by the byte, and with data volumes exploding, the cost to ingest, store, and retrieve logs has become unsustainable. Instead of a risky rip-and-replace, teams strategically minimize what they send to legacy platforms and route the rest elsewhere. 

To solve this, a wave of cloud-native, next-gen SIEM alternatives and data platforms has emerged: ETL orchestrators, cloud security data lakes, and multi-data SIEMs. These tools cleanse, normalize, and route logs more intelligently. Some even decouple analytics from storage to power faster, cheaper real-time detection across hybrid environments. 

Even for organizations that keep regulated data on-premises, new logs are increasingly routed to more flexible, lower-cost systems. It’s a smart move — but only if you have a way to connect and orchestrate it all.

Hyperautomation Makes SIEMs Better

Hyperautomation is the key to unlocking the full potential of a modern SIEM strategy. Torq Hyperautomation™ is the AI-driven orchestration layer that sits above your entire SIEM ecosystem. Whether you use one SIEM or several, Torq can connect the dots across tools, teams, and workflows to transform disparate data into actionable intelligence and automated responses.

Once integrated, Torq can:

  • Run parallel workflows across multiple SIEMs
  • Automate triage, investigation, and response across platforms
  • Reduce alert fatigue without disrupting existing operations
  • Build and deploy SIEM automations with drag-and-drop or natural language
  • Use Torq HyperSOC™ to auto-generate and resolve 95% of Tier-1 cases with agentic AI

Check Point SIEM and Torq Hyperautomation Integration Story

Check Point’s security team was in alert overload — not due to a lack of tooling, but because their SIEM was generating more noise than their lean SOC could handle. With a 30–40% manpower gap, traditional triage and manual response weren’t sustainable. 

Unlike legacy SOAR tools, Torq didn’t require Check Point to overhaul its SIEM or change how data was collected. Instead, Torq integrated directly into its existing SIEM infrastructure, ingesting and analyzing alerts. Within days, Check Point had deployed more than two dozen automated playbooks that operate natively across its security stack.

With Torq’s intelligent orchestration layer acting on SIEM-generated alerts — from triggering MFA to locking suspicious accounts — Check Point transformed a high-volume, high-fatigue environment into a streamlined, autonomous SOC. 

“With Torq HyperSOC, we can react automatically to problems before they become security incidents.”

Jonathan Fischbein, CISO, Check Point

Read Check Point’s full SOC transformation story here >

The Future: Autonomous SOCs Powered by AI + SIEM

The SIEM space is evolving fast. But legacy contracts, compliance requirements, and data gravity aren’t going away tomorrow. The future isn’t about replacing your SIEM. It’s about operationalizing it with AI.

With Torq, you can:

  • Connect any SIEM (or all of them)
  • Orchestrate security automation across platforms
  • Transform log overload into real-time response
  • Move toward an autonomous SOC without sacrificing control

Want to learn more about adopting AI in the SOC? Get the AI or Die manifesto to learn how to think strategically about AI in SecOps — from data privacy to AI hallucinations.

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Insights Integrations

Operationalize Data Security Automation with Cyera and Torq

By Torq
April 1, 2025
4 Minute Read
Together, Cyera and Torq deliver unparalleled data security automation in the SOC. Learn how Torq operationalizes Cyera’s data security intelligence to enforce policies and remediate data risks at machine speed.

Contents

Data is the critical foundation for all organizations, powering innovation, decisions, and growth. It’s also the fastest-growing attack surface, with sensitive information scattered across clouds, on-premise servers, and SaaS platforms. 

Cyera, the leader in modern data security, provides rich visibility into sensitive data down to its DNA level, providing vital context, identifying data risks and vulnerabilities, and delivering SOC teams a clear map of their data attack surface.

Once data insights are uncovered, SOC teams must take swift and consistent action. Torq’s platform operationalizes Cyera’s data security intelligence, organizing remediation and policy enforcement with machine-speed efficiency. Together, Cyera and Torq enable SOCs to protect sensitive data and intellectual property quickly, precisely, and accurately.

Solving Data Security’s Greatest Challenges 

Today’s landscape has opened a paradox. Organizations rely on data for business to thrive, yet the more data is generated, the harder it is to secure. Sensitive information is being spread everywhere, stored in cloud buckets, shared across SaaS apps, and accessed by a growing number of users and systems. SOC teams are tasked with protecting this sprawling landscape, but the sheer volume of alerts and manual processes makes it nearly impossible to keep up.

Cyera cuts through this noise, giving teams a clear view of what sensitive data exists, where the data lives, who (or what) has access to it, and the risks the data faces. Cyera’s approach is rooted in clarity — mapping the attack surface and delivering insights needed to protect critical assets.

This is where Torq comes in. By integrating with Cyera, Torq automates the actions required to secure data, eliminating inefficiencies and enabling SOC teams to instantly respond to data risks.

Data Security Automation at Work

When Cyera identifies a risk, such as an exposed cloud storage bucket or an anomalous data transfer, Torq acts immediately to execute tailored workflows, automating everything from remediation to stakeholder notifications. Here’s how Cyera and Torq work together: 

Comprehensive Data Discovery: Cyera scans your environment to identify sensitive data, classify it, and assess its risk profile.

Real-Time Insights: When Cyera detects an anomaly or identifies a risk, it triggers an event and passes the data insights along to Torq

Automated Orchestration: Torq picks up the baton, automatically launching workflows tailored to the specific alert, whether that’s notifying the right stakeholders, enforcing security controls, or triggering remediation actions.

Continuous Improvement: Cyera and Torq enable SOC teams to refine processes iteratively, reducing noise and improving response efficiency over time.

For example:

  • Cyera flags a misconfigured cloud storage bucket as containing sensitive PII. Torq automatically executes a remediation workflow, closing the bucket’s exposure and notifying relevant teams.
  • Cyera identifies an anomalous data transfer from a high-risk location. Torq not only alerts analysts but also enriches the alert with context and executes automated containment actions.

Cyera and Torq: Better Together

What makes Cyera and Torq a revolutionary pair is the shared commitment to scalability, speed, and precision. Cyera’s intelligence provides a clear path forward, while Torq delivers the power to act quickly and precisely.

Everyone in cyber knows speed is no longer an option. Manual processes simply can’t keep pace with the breakneck pace of today’s security landscape. Torq and Cyera together turn hours of work into seconds, automating everything from alert triage to remediation. Cyera provides 95% precision classification, while data security automation workflows from Torq ensure every response is consistent, reliable, and error-free, even under the pressure of an escalating incident.

As your organization grows, so do your risks. Cyera and Torq scale effortlessly, adapting to evolving needs and protecting data across clouds, Saas platforms, and beyond.

Elevate Your SOC

The integration of Cyera and Torq sets the new standard for what SOC teams can achieve with data security automation. By combining Cyera’s data-first approach with Torq’s automation expertise, organizations gain the tools to move faster, act smarter, and confidently secure data. 

Request a demo today to see how Cyera and Torq can transform your SOC.

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Hyperautomation

What is Security Automation? A Comprehensive Guide for Modern SOCs

By Torq
March 28, 2025
11 Minute Read
What is security automation?

Contents

Security teams are drowning — managing 10,000+ daily alerts, stretched thin by an ongoing cybersecurity talent shortage, and struggling to keep up with evolving threats. The solution? Security automation, particularly AI-driven security Hyperautomation.

What is Security Automation?

Security automation leverages automated workflows to handle critical cybersecurity tasks at machine speed— eliminating time-consuming manual processes like threat detection, analysis, and response. By automating these repetitive tasks, organizations can increase efficiency and accuracy and ensure a consistent security posture against threats.

The gold standard of security automation is AI-driven Hyperautomation, enabling security teams to move beyond simple automation and build an autonomous SOC for even greater efficiency and security gains.

Cybersecurity is essential to every organization — but without automation, it’s slow, resource-intensive, and prone to human error. Manual workflows bog down security teams, stretching time and resources thin while leaving gaps in threat detection, assessment, and remediation. Automating security not only accelerates response times but also ensures accuracy, eliminating costly mistakes and inefficiencies.

Cybersecurity automation uses technology to identify, understand, and respond to threats within your organization’s environments and to execute repetitive and time-consuming tasks. In other words, when you automate security, much of the grunt work can be handled by software, with limited, if any, manual intervention. This is especially useful when dealing with a high volume of alerts, allowing the software to filter out the low-priority and false positives threats and prioritize the critical ones, escalating to human analysts only when necessary. 

Security automation has become table stakes for SOC teams in today’s connected digital world.

How Security Automation Works

Security automation functions by integrating data from numerous security tools, applying artificial intelligence (AI) for threat detection, and enabling autonomous decision-making for immediate response. 

Hyperautomation combines GenAI, agentic AI, and extensive integration capabilities to enable seamless, real-time threat management across all environments, significantly enhancing detection and response capabilities.

Why is Security Automation Necessary? 

Large organizations, from Fortune 500 companies to global multinationals, face existential security challenges that demand security automation solutions, including:

  • Expanding attack surface: Security teams face alerts on alerts on alerts, from phishing and endpoint vulnerabilities to insider threats and fraud. Without automation to filter, prioritize, and respond to these threats at machine speed, teams simply can’t keep up.
  • Global cybersecurity talent shortage: According to ISC2, the estimated cybersecurity workforce gap is 4.76 million. SOC teams are stretched thin, and this problem is only getting worse. As tech stacks expand across multi-cloud environments, security teams’ capability to manage them is maxed out. Cloud security automation isn’t replacing analysts — it’s making their jobs possible.
  • Siloed security architecture: SecOps teams manage 70+ security tools across environments. Without integrations to combine these workflows, security teams face misaligned processes, inefficient work, and manual effort that slow down response times.

“60% of line of business users agree an inability to connect systems, apps and data hinders automation.” – ZDNET

Benefits of Automating Security

Enhanced efficiency: Cybersecurity automation eliminates repetitive tasks like data analysis and incident investigation. By streamlining workflows, security teams can dramatically reduce time-consuming processes, improve mean-time-to-respond (MTTR), and alleviate operational fatigue — boosting productivity, agility, and overall security resilience.

More accurate response: Manual processes run the risk of human error. Security automation minimizes this risk by implementing consistent detection and quicker responses. It also shortens the time-to-action for remediation, preventing further risks to the business.

Reduced analyst burnout: By automating time-consuming manual processes, security automation lightens workloads and prevents the constant alert fatigue that drains security teams. Automation frees up time for analysts to develop their expertise instead of getting bogged down in repetitive, busy work.

Scalable deployment: Automation in security centralizes tooling, enriches security cases with contextual intelligence, and provides real-time updates across platforms for seamless teamwork.

Reduced costs: Automation can help optimize resources and operational expenses by eliminating manual tasks, streamlining workflows, reducing the need for specialized staff, and improving resource allocation. It can also help avoid data loss, reputational damage, and other financial losses from security incidents.

Stronger compliance: Leveraging security automation tools to manage reporting and compliance activities decreases regulatory risk.

Faster MTTD/MTTR: Reduces alert fatigue by quickly identifying and remediating threats.

Autonomous Case Management: AI-driven automation manages incidents from detection through resolution, eliminating manual bottlenecks.

Full-lifecycle Response: Comprehensive automation enables end-to-end threat handling.

Cybersecurity Automation Types and Tools

Several tool types enhance security automation:

  • Hyperautomation: Combines advanced AI, machine learning, and integration capabilities, enabling autonomous decision-making and remediation, thus significantly outperforming traditional tools.
  • XDR (Extended Detection and Response): Provides integrated visibility and automated responses across endpoints, network, and cloud environments.
  • SOAR (Security Orchestration, Automation, and Response): Coordinates security tools, automating predefined responses (though now largely replaced by Hyperautomation).
  • AI Ops (Artificial Intelligence Operations): Uses AI to analyze vast datasets, detect anomalies, and automate responses proactively.

Best Practices for Security Automation

Maximizing security automation ROI requires:

  • Integration: Ensure seamless integration with existing tools
  • Customization: Tailor automation workflows to organizational needs
  • Regular Updates: Continuously update and refine automated systems
  • User Training: Equip analysts to leverage automated systems fully

Challenges and Limitations of Security Automation

Common challenges around security automation include:

  • Integration complexity: Difficulty linking legacy tools and data silos.
  • False positives: High false-positive rates from insufficient intelligence and correlation.
  • Operational complexity: Challenges in maintaining complex automation rules.

Torq solves these challenges with agentic AI, providing seamless integration, adaptive workflows, and accurate threat response.

Security Automation vs. Security Orchestration and SOAR

It’s easy to assume security automation and orchestration are synonymous, but there are many important differences between the two.

Security orchestration was intended to create a more streamlined workflow when connecting multiple tools and processes for security teams to act with greater efficiency and confidence. We all know this didn’t happen (See: SOAR is Dead Manifesto). 

SOAR platforms are slow, rigid, and don’t actually speed up processes for SOC teams. With limited integrations, outdated technology, and running on a single server, legacy SOAR hinders security teams’ ability to detect and respond to threats across environments. SOARs were a foundational tool for many SOC teams but are rapidly being replaced by security automation.

Cybersecurity automation brings together different teams, processes, and technologies to drive more efficient and scalable operations across a much broader scope. It does this through no-code, low-code, and even AI-generated workflow building, meaning that these tools can be used by just about anyone, not just security engineers, to define risks, enforce security rules, and remediate threats.

SOAR was built to automate security workflows, but it’s slow, complex, and requires extensive coding. Security Hyperautomation is the next evolution, eliminating inefficiencies with AI and no-code automation. Here’s how they compare.

Security Hyperautomation vs. SOAR

Security HyperautomationSOAR
Architecture✔ Cloud-native architecture, elastic scalingX Monolithic architecture, limited scaling
Integrations✔ Limitless, extensible, continuous API updatesX Limited, inflexible, requires custom dev
Efficiency✔ Helps manage risks at scale without adding headcount or requiring specialized resourcesX Requires extensive resources and constant maintenance
Accessibility✔ Allows all stakeholders to define and enforce security requirements X Requires cybersecurity expertise to configure and operate
Automated Response✔ No-code automation frameworks can automate threat response based on rulesX Focuses more on orchestrating responses by security professionals than remediating 
AI Capabilities✔ Built-in AI agents for autonomous remediation, workflow building, data transformation, and moreX Limited or non-existent
Analyst Productivity✔ High, 10x+ operational boostX Low, prone to burnout
Overall Effectiveness✔ Future-proof solution, providing comprehensive security coverage and automationX Limited flexibility, struggles to meet modern SecOps demands

Ready to pull the plug on your SOAR? Get the migration guide >

How to Pick the Right Security Automation Tool

Choosing the right security automation solution isn’t just about checking a box — it’s about finding a platform that seamlessly integrates with your existing security stack, scales with your needs, and actually delivers on the promise of efficiency and protection. Here’s what to consider:

1. Integration and Compatibility

An enterprise security automation platform is only as good as its ability to integrate with your existing tools. Look for a solution that offers out-of-the-box integrations with all of your key security and IT infrastructure, as well as the flexibility to build custom integrations without requiring extensive coding. The best platforms eliminate manual bottlenecks by enabling security teams to connect their entire stack effortlessly — without waiting on vendor updates or custom development work.

2. True No-Code vs. Customization Capabilities

Some solutions claim to be “no-code” but still require extensive scripting to handle real-world security scenarios. Choose a platform that provides both no-code simplicity and AI-generated workflow building. You shouldn’t have to choose between ease of use and flexibility. A well-designed security automation tool allows security professionals of all skill levels to build workflows while still enabling advanced users to fine-tune automations for complex use cases.

3. AI-Driven Decision Making

Cybersecurity automation has evolved beyond simple if-this-then-that workflows. Modern solutions, like agentic AI-powered automation, don’t just execute pre-defined rules — they can analyze threats in real time, correlate signals across multiple tools, and autonomously remediate low-risk incidents. When evaluating platforms, look for AI-driven insights and contextual automation that help security teams make smarter, faster decisions.

4. Speed and Scalability

At this stage, you should evaluate potential security automation solutions with a Proof of Concept (POC), focusing on ROI and time-to-value. Choose the use cases that are mission-critical to your organization to assess how quickly and easily they can be operational. Additionally, ensure the platform can scale with your needs — handling increasing volumes of security events without performance degradation or the need for constant tuning.

5. Vendor Vision

Security threats evolve daily, and your security automation solution should grow with them. Choose a vendor with a clear vision for innovation — one that’s actively incorporating AI, Hyperautomation, and advanced case management capabilities. The best platforms don’t just keep up with security trends — they redefine them.

Common Security Automation Use Cases and Examples

  • Identity and access management (IAM): Automates access control, reducing manual errors.
  • Threat hunting: Continuously detects and responds to threats proactively.
  • Cloud security posture management (CSPM): Ensures compliance across cloud environments.
  • Email security: Automates detection and remediation of phishing and malware.
  • Incident response: Accelerates and automates alert triage and threat containment.
  • Vulnerability management: Automates scanning, prioritization, and remediation.

Major Regional Bank Accelerates Phishing and Ransomware with Security Automation

A leading regional financial services organization turned to Torq for security automation to eliminate slow, inconsistent security responses and automate critical processes across its SOC. Facing a growing volume of phishing, ransomware, and fraud threats — along with a shortage of security analysts — the bank needed a solution that could streamline alert triage, investigation, and remediation in real time. 

Bypassing legacy SOAR solutions, this top 30 bank found the Torq Hyperautomation platform to be the best fit. By deploying Torq’s low-code/no-code security automation, the bank built and launched 100+ workflows in just three months, reducing mean time to investigate (MTTI) from hours to minutes. Torq’s limitless API integrations easily integrated with the bank’s existing security stack, allowing for a unified, automated approach to phishing and ransomware mitigation. 

Read their story >

The Future of Security Automation: Torq Hyperautomation and the Autonomous SOC

Security automation is an important step in modernizing cybersecurity, eliminating manual processes, and accelerating threat response. But the story doesn’t end there. 

The evolution of security automation and AI for security operations.
Explore the evolution of security automation and AI for security operations >

Security Hyperautomation enables SecOps to operate on a new scale thanks to AI-driven decision-making, adaptive workflows, and full-stack interoperability. This shift is powering a natural evolution toward the autonomous SOC, where AI doesn’t just automate security processes but also intelligently manages and optimizes them in real time.

Unlike traditional security automation, which focuses on predefined rule-based responses, Torq Hyperautomation dynamically connects disparate tools, enriches alerts with real-time intelligence, and autonomously executes remediation — all without manual intervention. It integrates AI and large language models (LLMs) to instantly correlate signals across multiple sources, filter false positives, and prioritize critical threats.

Where security automation removes friction, Hyperautomation eliminates inefficiencies entirely — allowing organizations to move from reactive to proactive, self-sustaining security operations. Agentic AI-powered automation can investigate, escalate, and remediate threats autonomously, closing security gaps faster than ever. AI-powered Hyperautomation doesn’t just improve security workflows — it redefines how modern SOC teams operate.

Get Started with Torq Hyperautomation

Choosing the right vendor is crucial — Torq offers unmatched AI capabilities, rapid time-to-value, seamless integration, and true no-code flexibility. See how Torq transforms your SOC into an autonomous security powerhouse.

Want to see how AI-powered security Hyperautomation can transform your SOC?

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AI Hyperautomation Integrations

How to Turn a SOAR Migration into SOC Transformation

By Torq
March 24, 2025
5 Minute Read

Contents

SOAR is dead-dead (too inflexible, too complex, and too limited on integrations) — but it’s not quite buried in some SOCs where it’s only hanging on because migrating can feel daunting when mission-critical workflows are tied to the system.

AI-driven Hyperautomation from Torq is the SOAR killer. Our team has helped major enterprises from every industry make the switch, quickly and easily, to achieve true SOC transformation.

We chatted with Mark Carosella, Sr. Sales Engineer at Torq, to hear firsthand what surprises new Torq customers the most when they pull the plug on their SOAR and learn what it is about Torq that makes migrating from legacy SOAR not just fast, but also transformative.

1. Don’t Just Switch Platforms — Optimize

One of the first — and most striking — realizations for companies logging into the Torq platform for the first time is just how easy it is to build SOC workflow automations. For those who previously used code-heavy automation tools and had to manage thousands of lines of Python, Torq’s intuitive, drag-and-drop workflow designer and AI workflow builder is game-changing — enabling security teams to build and deploy Hyperautomated workflows faster than ever before. Users can also test each step of their workflow in real-time, gaining instant feedback and making adjustments on the fly.

With Torq, even customizing integrations with APIs or configuring various data sources becomes accessible to those without advanced dev skills, by using AI agents with expert coding logic and syntax for script writing, CLI, and data manipulation. 

When migrating existing workflows to Torq, the ease of use and robust scalability of the platform provides the opportunity to do things that simply weren’t possible with legacy SOAR. To escape tech debt and inefficient and outdated processes, Torq encourages new customers to think beyond a “lift and shift” mentality so they can optimize SOC processes, rather than replicating them exactly as they were. The result is a true SOC transformation, not just a platform change.

The Torq team has seen it all and has a vast store of expertise and experience to recommend best practices for optimizing security processes. Torq Hyperautomation makes it much simpler to combine traditional workbooks into seamless workflows that take advantage of the platform’s strengths, such as AI-driven remediation and dynamic case management. 

Most Torq customers are able to consolidate security processes during the migration —  achieving the same outcomes with significantly fewer and much more efficient automations.

2. Reclaim Control Over Your Security Stack

During Torq Proof of Concepts (POCs), new users consistently highlight the same recurring challenges with their legacy SOAR platforms: limited integrations and difficulty connecting to essential data within existing tech stacks. This often forced their teams to resort to extensive, time-consuming Python coding, a painful and difficult-to-scale process. 

In contrast, Torq enables rapid, limitless integrations. Companies can connect their entire security stack in record time by using AI to generate integrations in seconds, or they can maintain granular control with draggable, low-code or full-code capabilities. Even if your third-party API or data format changes (a recipe for disaster in legacy SOAR platforms), real-time API monitoring ensures none of your integrations are at risk of breaking, so your stack always stays connected for uninterrupted automation. 

In one example Mark shared, a customer needing specific SIEM technology functions — which were previously inaccessible through their SOAR platform —  achieved their goal in minutes by simply copying an API command into Torq’s intuitive workflow builder canvas, eliminating the need to wait months for a team to develop custom code to create the connection.

3. Accelerate Adoption and Time-to-Value 

“Whenever we talk to customers or to the folks that are POCing Torq and getting into the platform for the first time, there’s one word that comes up in every single engagement: intuitive.”

– Mark Carosella, Sales Engineering Manager, Torq 

Building security automation workflows in Torq’s drag-and-drop and AI-assisted interface is highly intuitive, which means teams quickly grasp the fundamentals to get up and running during onboarding. Mark shared that within a day or two, new users are often independently building custom automation workflows. This can feel like a major “aha” moment for users who came in with the perception of automation as a complex, code-heavy experience in legacy SOAR platforms. 

One Torq user shared, “My favorite thing about Torq is that concepts go from my head to a working reality in just a few hours, instead of a few weeks, largely in part to the no-code functionality.”

This ease of use empowers any user, regardless of their coding skills, to rapidly implement workflows and adapt their security operations, accelerating time to value.

Transform Your SOC: Get the SOAR Migration Guide

If you’re ready to finally pull the plug on your SOAR, get the Kill Your SOAR Migration Guide to plan ahead. It covers the big picture of what you need to know going into a migration, plus a migration success story from a leading security company, advice from a SOC manager who made the switch, and the top 3 POC use cases. 

With Torq, your migration isn’t just about switching platforms — it’s an opportunity to transform your security operations.

Get the Guide
Ready for SOC transformation? Get the Kill Your SOAR migration guide.
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Insights Research

SANS Survey: 5 Security Challenges Keeping SOCs in the Dark

By Torq
March 20, 2025
6 Minute Read
SANS Detection and Response Survey shows that SecOps teams are facing existential security challenges.

Contents

The 2024 SANS Detection and Response Survey sheds new light on some all-too-familiar security challenges: security operations teams are overwhelmed with alerts, struggling to respond fast enough, and tracking the wrong KPIs. Sure, automation adoption is increasing (64% of organizations now leverage it in some capacity), but most SecOps teams are still operating in slow, reactive, and heavily manual environments.

Five Security Challenges Faced by SecOps Teams

1. Security teams are stuck in semi-automation mode.

Most security operations teams think they have automated response mechanisms, but they’re really just babysitting inefficient, semi-automated workflows. The SANS Survey data shows that while 64% of teams have automated response mechanisms in place, less than a quarter have fully automated their processes. That means the vast majority still rely on analysts to manually intervene and execute responses.

2. Slow response times are leaving organizations exposed.

Speed matters. Attackers are betting you’ll take a while to respond to threats. SANS found that a whopping 32.8% of teams take hours to respond to threats, and 41.4% say they respond within minutes. In today’s reality, even minutes can be too slow. Recent data shows that lateral movement breakout times dropped from 62 minutes to 48 minutes, with the fastest recorded breakout happening in just 51 seconds. If a response takes more than a minute, the damage may already be done. 

3. Alert fatigue and data overwhelm are killing security team productivity.

It’s loud in the SOC. More than half of security teams say false positives are a huge problem, and 62.5% are overwhelmed by sheer data volume. Every second spent triaging junk alerts is a second not spent investigating real threats — meaning SOCs are burning through their most precious and expensive resource: human focus. Analysts’ expertise is critical for threat investigation and response, yet most of their time is wasted manually sorting through thousands of low-value alerts that should’ve been filtered out in the first place. This wastes time, burns out analysts, and, worst of all, lets real threats slip through. 

4. Security teams are still tracking the wrong KPIs.

The most surprising part of the survey responses is that more than 50% of security teams aren’t even tracking KPIs like Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR). ​​Instead, they’re tracking vanity metrics like the number of incidents detected  —  or, worse, they don’t have enough data to measure their own efficiency. Without the right data, SOC teams cannot optimize performance or reduce response times.

5. SOAR is holding teams back.

SOAR was supposed to be the answer to security automation… right? The majority of respondents use SOAR for threat response, but half still rely on manually running commands to respond to threats. This proves what we at Torq already know: SOAR hasn’t lived up to its promise. SOAR platforms were supposed to automate security workflows, but most teams still struggle with slow response times, rigid playbooks, and high maintenance overhead.

The Fix: An Autonomous SOC Powered by AI-Driven Hyperautomation

The answer to these existential security challenges isn’t manually tuning SOAR, tweaking detection rules hoping something works, or hiring more analysts (Be real: Where are you even finding them? The SANS Survey found the majority of security teams struggle with lack of skilled personnel). The real fix is an autonomous SOC powered by AI-driven Hyperautomation: a SOC that invests in AI and automation to eliminate inefficiencies, take action at machine speed, and, ultimately, shorten response times.

Comparison table showing how an autonomous SOC fixes 5 key security challenges.

1. Go autonomous. 

Ditch the scripts, stop the manual tuning, and let AI take over. An autonomous SOC removes the need for engineers to build, maintain, and tweak workflows with extensive coding. Instead, teams can simply describe a workflow, use case, or outcome using natural language to guide agentic AI as it implements workflows to secure the organization faster than ever before. An autonomous SOC can handle 95% of Tier-1 cases — allowing security teams to focus on critical, high-impact threats, rather than babysitting outdated playbooks or struggling with the limitations of rigid SOAR architectures.

“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  

2. Slash response time.

With SOC automation, alerts don’t sit in a queue waiting for an analyst to take action. AI-driven Hyperautomation instantly takes action to investigate alerts, enrich cases, and contain threats  — isolating infected endpoints, disabling compromised accounts, and blocking malicious infrastructure before damage is done. Unlike SOAR’s static playbooks, an autonomous SOC leverages AI to tirelessly and intelligently analyze and remediate massive volumes of security incidents, shrinking response times from hours to seconds.

3. Eliminate alert fatigue.

AI Agents don’t just process alerts — they triage and prioritize them. AI-powered SOCs use sophisticated planning and contextual reasoning to filter out low-fidelity alerts, suppress false positives, and escalate only the alerts that matter. Analysts no longer have to sift through thousands of useless alerts  —  AI handles the noise so teams can focus on critical security risks.

4. Track the right KPIs.

An autonomous SOC should be able to measure security response and provide visibility into operations. Instead of requiring analysts to manually track and compile data, AI can capture and log detection times, response actions, and remediation speeds automatically. SOC leaders finally get a clear picture of what’s working, where bottlenecks exist, and what to optimize.

5. SOAR is dead. Ditch it.

SOAR is simply too slow, rigid, and high-maintenance to keep up with modern SOC demands. An autonomous SOC doesn’t rely on pre-scripted playbooks — it builds, executes, and adapts automation dynamically, all in natural language. With AI-driven Hyperautomation, security teams move faster than attackers, not the other way around. See the difference.

It’s time to move past the limitations of SOAR and slow, reactive security operations. Take your SOC autonomous — learn how easy it is to switch to AI-driven Hyperautomation from Torq.

Get the SOAR Migration Guide
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Insights

How to Automate Application Security Operations: 4 Ways

By Torq
March 19, 2025
5 Minute Read
Automate application security operations.

Contents

Maintaining an online business presence nowadays means that malicious actors are going to target and likely exploit any application vulnerabilities they can find sooner or later. According to the 2021 Mid Year Data Breach Report, although the number of breaches has declined by 24%, the staggering number of records that were exposed (18.8 billion) means that there is still room for improvement.

How can you protect your business from the constant threat of exposure and security breaches? One crucial step is to establish solid foundational layers of security controls that check and validate every part of the SDLC. By using automation when performing those checks, you can detect and prevent common security risks and exposures before they end up in production.

Keep reading for a comprehensive overview of application security automation, along with four ways to automate security ops to protect the core of your business from data breaches.

What Is Application Security?

The term application security (AppSec) refers to the series of processes and tools related to security controls that development teams use during SDLC. Creating secure software is hard, mainly because there are myriad risks involved. Attackers prefer to target web applications instead of infrastructure components because these applications offer a convenient way to access databases or other internal systems. Defenders need to plug up every conceivable hole, while attackers only have to find one vulnerable spot. This often results in an uneven playing field.

To counter that pervasive threat, development teams must adopt effective methodologies and best practices for developing secure software. One way to do this is to utilize tools to analyze the code both statically and dynamically to pick up any known insecure idioms. For example, a tool might flag code that is implementing unsafe casting, secrets that have been committed to VCS, or a failure to close streams after they have been used. Developers can manually review these issues and fix them before they get deployed to production.

Another strategy is to scan application dependencies. For example, when developing a financial app, developers might use an open source library that offers a convenient currency model. But how would they know that this library was safe? Dependency scanners monitor those dependencies and check to see if they are out of date or suffer from open CVEs. That way, they will know as soon as possible if anything changes.

Writing secure software starts with integrating proper application security controls and automating the process. We will explain that part next. 

Why You Should Automate Application Security: Main Benefits

As we mentioned earlier, there are several tools and processes that development teams employ to flag risks in their software repositories. Automating this task helps you make the most of this process. That’s because you can achieve better coverage when looking for threats and find them sooner when you eliminate the manual parts of the process.

In addition, you will be better equipped to respond to security incidents. Your AppSec teams will have all the context they need to address any issues. Finally, you can achieve better compliance and auditing scores, since this eliminates the risks involved in working manually, such as skipped events and slower response rates. 

Next, we’ll explain four important ways to automate application security operations.

Four Ways to Automate Application Security Ops

1. Trigger Automated Security Flows as Part of Your CI/CD Pipeline

The best place to start with automation is to implement shift-left security within the CI/CD pipelines. When we say CI/CD pipelines, we mean the various steps that are taken when pushing code in a remote environment. These steps include admission to VCS and triggering the CI pipeline, static code analyzers, security alerts, bots, and notification systems as well as external security integrations. Incorporating these steps will give you the best chance of protecting your application from exploits.

2. Validate/Enforce Requirements and Perform Periodic Checks When You Create Repositories, Components, and Cloud Environments 

When developers create new repositories or provision new clusters that operate company accounts, there should be a preliminary check to apply basic security templates and policies. This will prevent gaps or missed security controls from the moment you create those resources until you actually use them. You want to create default standards for all components that prevent them from existing in a sub-standard security state. 

3. Orchestrate Follow-Ups for Application Security Findings, Assign and Escalate Issues, and Validate Fixes 

Once the system pinpoints security issues in your resources, you should use a separate mechanism to capture those events and store them in a threat intelligence platform. As we explained in this article on the basics of threat intelligence, you can pull and combine those indicators, run customized workflows, and deliver the information you collected to the system of your choice.

4. Automate Updates to Infrastructure-as-Code and Configuration Settings

Finally, consider your usage of Infrastructure-as-Code (IaC) and your configuration settings. These internal tools are part of the developer tooling, and they are also susceptible to exploitation. You will have to enforce the same kind of rules and policies when using those programs. It’s even better if you have an automated tool that monitors and updates only the development tools in your infrastructure. This way, you will not risk exposure or a major upgrade process if some of them become outdated or are found to contain a known vulnerability.

Next Steps: Automating Application Security Ops with Torq

The best way to automate application security ops is to create a strong foundation of tools, processes, and techniques. Attackers are constantly trying to exploit vulnerable applications. However, automating application security ops doesn’t have to be complicated. In fact, security and DevOps teams should be able to use a low-code platform to achieve those targets.

Torq offers a complete no-code platform for automating application security ops using threat intelligence, threat hunting, security bots, and workflow modules. You can request a demo here.

 

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AI Hyperautomation

What is Hyperautomation?

By Torq
March 18, 2025
5 Minute Read
Diagram explaining what is Hyperautomation in cybersecurity

Contents

Hyperautomation is an efficiency-driven, strategic process that integrates across business technology stacks to rapidly automate and orchestrate as many business and IT operations as possible. It uses advanced technologies such as AI and low-code/no-code platforms for greater speed and ease of use.

Hyperautomation Definition

So, what is Hyperautomation? It’s a strategic business approach that unifies multiple automation technologies to streamline and speed up complex processes end to end. While traditional automation focuses on repetitive, rules-based tasks, Hyperautomation layers in intelligence, adaptability, and orchestration for machine-speed efficiency — transforming how teams work across IT, business, and cybersecurity.

Learn more about security Hyperautomation > 

Automation vs. Hyperautomation

At a glance, automation and Hyperautomation sound similar, but they solve very different problems in cybersecurity. Traditional automation handles simple, repetitive tasks. Hyperautomation spans systems, layers in AI-driven decision-making, and coordinates human-machine collaboration at scale. It’s about full lifecycle automation — detection, triage, enrichment, response, and resolution — across multiple domains.

In cybersecurity, this means moving beyond automating password resets or phishing reports. Hyperautomation empowers your security operations center (SOC) to autonomously detect threats, prioritize alerts, trigger tailored responses, and continuously optimize based on results.

How Hyperautomation Tools Work

Hyperautomation isn’t one tool — it’s a coordinated ecosystem. It connects multiple Hyperautomation technologies into a single framework, typically combining:

  • GenAI and agentic AI for decision-making and contextual awareness
  • Low-code/no-code platforms for fast workflow building without extensive coding
  • Business process management for orchestrating complex workflows
  • Integration platforms for connecting apps, tools, and systems
  • Analytics and reporting tools for measuring performance and optimizing automations over time

Hyperautomation can adapt — systems can dynamically adjust workflows, update rules based on new data, and seamlessly coordinate human and machine collaboration.

The Hyperautomation Advantage

Hyperautomation technology transforms SecOps by delivering faster, smarter, and more scalable operations. Here’s a quick look at the biggest Hyperautomation benefits:

  • Ease of use: With drag-and-drop interfaces and no coding required, anyone on the security team can create powerful automations in minutes. Complex threat responses become easy to build, deploy, and scale across teams without relying on the complexity of legacy SOAR solutions or waiting for custom coding.
  • Lower costs: Dedicated expert support with no surprise consulting fees.
  • Secure on-prem connectivity: Zero-trust agents connect hybrid environments securely.
  • Flexible, full-stack automation: Integrate and automate anything across cloud, infrastructure, and on-prem systems.

From Automation to Hyperautomation 

Security automation started with promise — but hit its limits fast. Legacy SOAR tools were designed to orchestrate basic security actions but broke down under the weight of modern security demands. Static playbooks, brittle integrations, and clunky interfaces turned what was supposed to be “automation” into yet another bottleneck.

Security teams needed a new way forward as threats grew faster, more dynamic, and more complex. Unlike SOAR, Hyperautomation doesn’t just automate a few steps; it transforms the entire SOC workflow. 

It connects tools across your technology stack, enables context-aware decisions, and executes actions quickly. And because it’s built with low-code/no-code at its core, it empowers any analyst, not just engineers, to build, test, and deploy workflows in minutes.

Where SOAR failed to scale, Hyperautomation moves 10x faster with infinite extensibility, seamless integrations, and built-in case management to reduce noise and prioritize what matters. It enables SOCs to go from “human-in-the-loop” to “human-on-the-loop,” directing strategy while AI and automation handle the grind.

When paired with agentic AI, Hyperautomation becomes the foundation of the autonomous SOC, which is a SOC where alerts are triaged, threats are hunted, incidents are remediated, and analysts stay focused on the big picture.

Hyperautomation Use Cases in Cybersecurity

Hyperautomation doesn’t just make your SOC more efficient — it can transform how your team works. Here are some ways where Hyperautomation delivers major impact for cybersecurity teams.

1. Incident Response
Hyperautomation enables end-to-end incident response without human bottlenecks. From initial detection and triage to investigation, enrichment, and remediation, intelligent SOC automation accelerates every phase of the process — reducing mean time to respond (MTTR) from hours to minutes.

2. Phishing
Phishing is a top entry point for attackers. Hyperautomation instantly identifies suspicious messages, quarantines affected inboxes, revokes compromised credentials, and notifies users — all without requiring analyst intervention.

3. Just-in-Time (JIT) Access Provisioning
Managing administrative privileges across a hybrid infrastructure can be a nightmare. Hyperautomation grants and revokes access dynamically based on workflows and business rules, reducing privilege creep and improving security posture.

4. Threat Hunting
With Hyperautomation, SOCs can continuously search for threats using AI agents across SIEMs, EDRs, and identity platforms. It’s proactive defense — and it’s fast.

5. Identity and Access Management (IAM)
From self-service access validation to automatic account cleanup, Hyperautomation brings control and consistency to identity workflows, ensuring alignment without added complexity.

Hyperautomation with Torq

Torq Hyperautomation™ combines agentic AI, low-code/no-code workflow building, and multi-system security orchestration into one unified experience. Whether you’re deploying across cloud, on-prem, or hybrid environments, Torq makes it easy to automate your entire SOC — without needing a single line of code.

Key benefits of Hyperautomating your security operations with Torq include:

  • AI-native: Orchestrate AI agents that triage, investigate, and remediate alerts.
  • Low-code simplicity: Use drag-and-drop or natural language prompts to build advanced workflows in minutes.
  • Massive integration library: Connect with any tool in your security stack and beyond.
  • Built-in case management: Prioritize and enrich alerts automatically, route decisions to the right people, and track everything.

As threats grow faster, more complex, and more automated, your response strategy has to evolve just as quickly. Whether you’re replacing legacy SOAR, reducing alert fatigue, or scaling your SOC, Torq’s Hyperautomation platform gives you the speed, intelligence, and flexibility to stay ahead.

Feeling the pressure to get more done faster across your security operations? 

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Hyperautomation Use Cases

Combating Ransomware, Phishing, and Zelle Fraud at Financial and Bank SOCs

By Bob Boyle
March 12, 2025
7 Minute Read
Learn how financial services and bank SOCs are using security Hyperautomation to replace spreadsheets, defend against phishing, and combat Zelle fraud.

Contents

Banking and financial services companies sit on a goldmine of sensitive customer data, making them a prime target for phishing and ransomware attackers hoping to strike a payout. 

Even with defenses like MFA and security training, human error continues to be a critical point of failure for financial institutions — a 2024 report found that 3 out of every 1000 individuals working in banking click on a phishing link each month. This stark reality of risk highlights the industry’s urgent need for more proactive, automated security processes.

Below, we break down the top financial and bank SOC use cases for security Hyperautomation and cover how a major regional bank successfully reinstated Zelle services by automating account lockdowns for fraud alerts.

The Automation Imperative in Finance and Bank Security Operations

Two of the most common — and critical — security operations priorities for CISOs we’ve talked to at banks and financial services companies are to:

  • Mitigate risk by quickly responding to, containing, and remediating attacks.
  • Maintain materiality by focusing on the most important security issues that could cause the biggest problems and by being able to accurately assess when a cybersecurity incident requires SEC reporting.

Achieving these requires reducing Mean Time to Respond (MTTR), ensuring swift and effective remediation, and gaining visibility across all identities and security assets. However, manual processes, a jungle of spreadsheets, and siloed data compound operational challenges at financial and banking organizations. 

To modernize their financial and bank SOCs, forward-thinking CISOs are embracing Hyperautomation as a way to unify their security stack and automate incident response. Integrating solutions like ServiceNow or Snowflake with Torq’s AI-driven Hyperautomation platform can provide a single source of truth and streamline security operations for a stronger security posture and greater visibility across the SOC. 

Top 5 Bank SOC Challenges Solved by Hyperautomation

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

1. Phishing Alert Analysis

Automate the extraction and aggregation of URLs, file hashes, and message headers from Outlook messages and attachments, providing a comprehensive data set for further security analysis. 

Workflow Steps:

  1. Receive potential phishing alert from Microsoft 365.
  2. Execute parallel tasks to extract URLs from the email body, retrieve message headers, and process attachments (if present).
  3. For the email body, extract all unique URLs and collect them.
  4. Retrieve message headers using Microsoft Graph API and store them.
  5. If the email has attachments, list them and filter out non-file attachments.
  6. For each file attachment, retrieve detailed information and extract URLs from the content if available.
  7. Collect and combine URLs from various sources (e.g. body and attachments). Set default values if no URLs are found.
  8. Link message headers from the email and attachments, setting default values if none are found.
  9. Generate a structured output containing URLs, file hashes, and message headers.
  10. Nested Workflow: Case Management

2. Ransomware Case Creation and Categorization

Automate the ingestion and processing of CrowdStrike threat data by creating a comprehensive case in Torq. Once the case is created, notify the security team via email while categorizing the threat and adding relevant observables for further analysis. 

Workflow Steps:

  1. Extract specific fields from the incoming CrowdStrike event data into a sparse JSON object.
  2. Flatten the JSON object for easier processing and format it for a markdown table.
  3. Convert the event’s creation date to a specified format.
  4. Create a markdown table from the formatted data.
  5. Use a switch-case structure to categorize the threat as malware or ransomware, setting a variable accordingly.
  6. Create a case in Torq using the extracted and formatted data, including custom fields and tags.
  7. Add observables to the case, such as file hashes, with specified reputation scores.
  8. Query historical cases and link any closed cases with matching observables. 
  9. Generate an access token for Microsoft 365 and send an email notification about the new case to the specified recipient list.

3. Automated Threat Analysis and Enrichment 

Automate the process of extracting and analyzing threat intelligence data based on specific commands submitted by the security team — e.g. “Check IP”, “Check Hash”, or “Check Host”. Facilitate communications through Microsoft Teams to trigger the workflow and receive the enriched threat analysis. 

Workflow Steps:

  1. Evaluate incoming event text to determine the command type (!checkip, !checkhash, !checkhost).
    • For !checkip: Extract IP address using regex and retrieve information for each IP from AbuseIPDC
    • For !checkhash: Extract patterns using regex, retrieve analysis reports from AnyRun and get threats from SentinelOne
    • For !checkhost: Extract patterns using regex and initiate a scan on SentinelOne agents, wait for a specified duration, then retrieve threats from SentinelOne.
  2. Reply with the information gathered to the thread in the originating Microsoft Teams channel. 

4. Case Management

Automate the process of checking for existing cases and creating new cases if necessary, ensuring efficient case management and reducing duplicate cases. This workflow is a valuable and repeatable tool for any case management program. Consider using a “nested workflow” attached to other Hyperautomated use cases (for example, see Phishing Alert Analysis above).

Workflow Steps:

  1. Query existing cases to check if a case already exists with the specified name, event data, or observable submitted.
  2. If a case exists, attach the new observable to the case and exit the workflow with the existing case ID.
  3. If no case exists, create a new case with the provided details such as title, SLA, severity, and state.
  4. After attempting to create a case, check the creation status.
  5. If the case creation is successful, exit with the new case ID.

5. Fraud Detection

Automate the process of locking or unlocking a user account based on suspected fraud event data. Update your CRM with relevant fraud activity and notify the appropriate stakeholders with contextual information about the actions taken.

Workflow Steps:

  1. Set workflow parameters to include user ID and notification email addresses.
  2. Check if required fields are present in the event data.
  3. Verify the user’s status via an API call and determine if the user should be locked or unlocked.
    1. If lock: Execute an API call to lock the user and set a variable indicating the action taken.
    2. If unlock: Execute an API call to unlock the user and set a variable indicating the action taken.
  4. If the lock/unlock action is successful, query Salesforce to retrieve the user’s account information.
  5. Add a “fraud task” to the user’s account in Salesforce and notify the specified email addresses of the action taken.
  6. If adding the activity to Salesforce fails, send a failure notification to the specified email addresses.

Case Study: Automating Zelle Fraud Detection and Lockdown from End to End

A major regional U.S. bank with billions in assets faced an urgent, compliance-driven requirement to automate their detection and response to fraud alerts in Zelle, a customer-facing payment service that had been suspended by the SEC due to a surge in fraudulent activity.  

With Torq’s Hyperautomation platform, the bank’s SOC quickly automated the end-to-end process of locking down accounts triggered by fraud alerts, enabling them to reinstate Zelle services. Torq also automates CRM updates, giving customer service immediate context when talking to customers about account lockdowns.

And that’s not all they achieved with Torq — read the case study for the full story of how they published over 100 workflows in just 3 months and reduced their Mean Time to Investigate (MTTI) from hours to minutes.

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AI Hyperautomation

AI SOAR Alternative: Why SOAR is Dead and What’s Next

By Torq
March 6, 2025
6 Minute Read
Torq is the leading AI SOAR alternative for SOC automation.

Contents

Security Orchestration, Automation, and Response (SOAR) was once hailed as the answer to a more efficient and automated Security Operations Center (SOC). The idea was compelling: automate repetitive tasks, reduce manual workloads, and speed up response times. 

But fast-forward to today, and despite generations of SOAR evolution, SOCs are still battling familiar challenges. Here’s why SOAR is dead — and why AI SOAR alternatives like Hyperautomation have replaced it.

What is SOAR? 

SOAR first emerged in the mid-2010s, promising to automate SOC tasks and improve operational efficiency. It aimed to accelerate incident response, reduce manual workloads, and unify siloed tools. 

While SOAR platforms were able to automate simple tasks like phishing response and threat intel propagation, they ultimately fell short in addressing the core challenges of modern SecOps: threat detection, investigation, and response (TDIR).

SOAR platforms were designed to orchestrate tools, automate workflows, and respond to alerts more efficiently. Theoretically, they should unify disparate technologies into a cohesive system where incidents can be enriched, triaged, and remediated through pre-built playbooks. So what went wrong?

Why SOAR Failed to Automate the SOC 

To understand why SOAR hasn’t met expectations, examining the nature of SOC work is important. Security operations involve a combination of two types of tasks:

  • Thinking tasks: Interpreting alerts, determining scope and impact, and creating response plans.
  • Doing tasks: Activity-based tasks like taking response actions, updating systems, and notifying stakeholders.

SOAR platforms were pretty good at automating “doing” tasks, but they struggle with the more complex, judgment-driven “thinking” tasks. Here’s why:

  • Too complex: Thinking tasks require deep understanding, data synthesis, security expertise, and decision-making. Replicating these traits with static playbooks is nearly impossible.
  • Unpredictable: Security operations deal with highly variable inputs, which leads to an ever-expanding set of edge cases that are difficult to account for in playbooks.
  • Not customizable: Out-of-the-box playbooks rarely meet an organization’s specific needs, leading to expensive custom coding and high maintenance burdens.

Over 80% of organizations agree SOAR is too complex, costly, and time-consuming — and nearly 90% admit that building even basic automation requires a huge upfront investment in time and resources. 

Even GenAI advancements aren’t enough. SOCs need security automation that can adapt and understand the complexities of threat detection and investigation. Automating the “thinking” tasks is the key to achieving true SOC automation.

Instead of solving problems, legacy SOAR platforms created new ones: rigid architectures, limited integrations, disconnected defenses, and overwhelmed analysts drowning in alert noise. Built on monolithic, non-cloud-native infrastructure, SOAR can’t scale, can’t adapt, and definitely can’t keep up with modern threat landscapes.

SOAR isn’t  just outdated — it’s holding security teams back. See why SOAR is dead.

Introducing Hyperautomation: The Only AI SOAR Alternative

As organizations reach their breaking point with traditional SOAR’s shortcomings, they’re turning to the only effective AI SOAR alternative — Hyperautomation. This next-gen approach fuses Gen AI, agentic AI, low-code/no-code orchestration, and cloud-native infrastructure into a single, adaptive engine for modern security operations.

Unlike traditional automation or AI SOAR point solutions, agentic AI-driven Hyperautomation doesn’t just execute tasks — it thinks, learns, and scales. It mimics the analytical reasoning of human analysts, turning high-effort “thinking” functions into fully autonomous, intelligent workflows. From real-time triage to dynamic response, Hyperautomation redefines what’s possible in the modern SOC.

Hyperautomation + AI Agents = A Happy SOC

At the heart of a Hyperautomated SOC are AI agents. While Hyperautomation connects and automates the entire security stack, agentic AI brings the cognitive power — making independent decisions, adapting, and continuously learning from every signal.

This combination transforms traditional automation into something far more powerful: a fully autonomous SOC workflow that mimics human judgment at machine speed. The outcome isn’t replacing human analysts — it’s making their lives in the SOC less stressful and more engaging.

Benefits of AI agents in the SOC include:

  • Finding more real threats: Agentic AI can process and correlate every alert at machine speed, allowing SOCs to uncover real threats that might otherwise go unnoticed.
  • Reducing MTTR: By eliminating manual bottlenecks in triage and investigation, agentic AI can drastically reduce response times, helping SOC teams resolve incidents in minutes instead of days.
  • Boosting analyst productivity: Automating repetitive tasks frees up analysts to focus on higher-value work, such as investigating complex incidents or working on strategic initiatives.
  • Increased efficiency: With agentic AI handling the mundane tasks, analysts can shift their focus to more meaningful work, improving job satisfaction and reducing burnout.

Leading Analysts Agree: SOAR is Dead

Leading industry analysts, including Gartner, GigaOm, and IDC agree that legacy SOAR platforms are obsolete. Modern cybersecurity demands flexibility, speed, and intelligence that only Hyperautomation can provide.

In their recent report, IDC confirms what security teams already know: Legacy SOAR promised efficiency but delivered complexity. IDC specifically highlights AI SOAR replacement, Torq Hyperautomation™, as a game-changing platform that goes beyond automation and enters the realm of true autonomous operations — powered by agentic AI, built-in case management, and real-time orchestration across the entire security stack.

“Hyperautomation is the answer to existing SOAR platforms. Torq’s Hyperautomation capabilities can help improve the efficacy of security teams now and in the future. The agentic AI architecture is disruptive.”

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

Why Torq HyperSOC™ is the Definitive SOAR Replacement

Legacy SOAR platforms promised security automation. Torq HyperSOC delivers it at a scale, speed, and intelligence legacy systems simply can’t match. 

Torq HyperSOC is the industry’s first fully autonomous SOC platform, powered by a Multi-Agent System (MAS) that triages, investigates, and remediates threats. It doesn’t just respond to alerts — it thinks, acts, and learns like a human analyst, but faster and 24/7.

Our cloud-native, AI-powered SOC platform delivers:

  • Limitless integrations: Torq connects with virtually any tool in your security ecosystem — EDR, SIEM, IAM, cloud, SaaS, or legacy — with no-code simplicity. You can integrate and automate stack-spanning workflows in minutes, not months.
  • Real-time threat response:  Powered by agentic AI, Torq doesn’t just wait for alerts — it autonomously triages, investigates, and remediates threats as they emerge.
  • Proactive defense: Torq detects patterns, identifies risks before they escalate, and automates preemptive actions to neutralize threats at the source.
  • Unmatched scalability: Whether you’re processing 100 or 100,000 alerts daily, Torq’s cloud-native, event-driven architecture handles it without sweat.

This isn’t just an AI SOAR — it’s a whole new category. Torq Hyperautomation isn’t trying to fix legacy problems with band-aid solutions. It’s built from the ground up for the AI era, where speed, intelligence, and adaptability aren’t nice-to-haves — they’re SOC survival essentials.

The Torq Difference: What Sets Us Apart from SOAR Vendors

SOAR is Dead: Long Live Hyperautomation

The era of legacy SOAR is over. Organizations are increasingly making the switch to Torq Hyperautomation, the true AI SOAR alternative that can meet the modern SOC’s demand for speed, autonomy, and adaptability.

Ready to step into the future of security operations? Our team has helped major enterprises from every industry make the switch, quickly and easily.

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