Automations
This pillar focuses on cybersecurity workflows where agents patrol network signals, detect suspicious behavior, and trigger containment before threats can spread laterally. Content should position these pages as blueprints for custom SOC automation that reduces dwell time, increases analyst leverage, and connects autonomous action to enterprise security controls.
This page details the foundational architecture for a custom, end-to-end autonomous threat hunting system. It explains how multi-agent orchestration, continuous signal analysis, and automated containment actions reduce attacker dwell time from days to minutes, directly lowering breach impact and analyst fatigue. The blueprint covers integration with SIEM, EDR, and network controls, plus the critical approval gates and observability layers needed for enterprise deployment.
This page outlines a custom workflow where specialized agents collaborate to detect anomalous user and entity behavior (UEBA) across cloud, identity, and data systems. It shows how this architecture reduces false positives by correlating weak signals, automates initial triage, and creates a scalable detection layer that improves over time. Implementation covers agent design, data pipeline integration, and the business case for reducing insider threat and credential compromise risk.
This page provides a blueprint for a custom workflow that autonomously hunts for signs of lateral movement by analyzing authentication logs, network flows, and endpoint process trees. It demonstrates how automated mapping of attack paths and privilege escalation attempts shrinks investigation time and contains breaches faster. The architecture details agents for correlation, graph analysis, and integration with IAM and network segmentation tools.
This page explains a custom build that continuously monitors outbound data flows, file transfers, and cloud storage APIs for signs of exfiltration. It shows how combining DLP policies, anomaly detection, and automated response (like blocking or quarantining) reduces data loss risk and compliance exposure. The implementation covers data lineage tracking, encryption analysis, and integration with email and collaboration security tools.
This page details a custom workflow where agents analyze DNS queries, network traffic patterns, and encrypted flow metadata to identify beaconing activity indicative of compromised systems. It demonstrates how automating this hunt reduces dwell time for advanced persistent threats (APTs) and scales detection beyond signature-based tools. The architecture covers statistical modeling, threat intelligence enrichment, and automated sinkholing or firewall rule deployment.
This page outlines a custom orchestration layer that automatically enriches raw security alerts with threat intelligence, asset context, and user risk scores. It shows how this workflow reduces SOC triage time, improves incident priority scoring, and feeds higher-fidelity signals into automated response playbooks. Implementation details include API integration with TI feeds, CMDB, and UEBA systems, plus confidence scoring for automated decisions.
This page provides the architecture for a custom workflow that ingests alerts, applies ML-based scoring for severity and business impact, and routes incidents to the appropriate queue or automated playbook. It demonstrates how this system reduces manual sorting, accelerates mean time to acknowledge (MTTA), and ensures critical incidents are never buried. The build covers integration with ticketing systems (ServiceNow, Jira), contextual data sources, and human-in-the-loop escalation paths.
This page details a custom workflow where, upon a confirmed incident, agents automatically gather and preserve forensic evidence from endpoints, cloud workloads, and network devices. It shows how this preserves chain-of-custody, accelerates investigation, and reduces the manual effort of evidence acquisition. The architecture covers secure evidence storage, integration with EDR and cloud APIs, and compliance with legal hold procedures.
This page explains a custom build that automatically tests new IOCs (IPs, domains, hashes) against internal telemetry to confirm exposure and scope. It demonstrates how this workflow eliminates manual hunting for each new threat feed item, rapidly identifies compromised assets, and triggers containment actions. Implementation covers integration with threat intelligence platforms, log search APIs, and automated ticket creation for confirmed hits.
This page provides a blueprint for a high-stakes containment workflow where, upon high-confidence detection, an agent automatically isolates a compromised host from the network. It details the safety controls, approval gates, and rollback mechanisms required for enterprise trust, and shows how this reduces blast radius during ransomware or active intrusion. Architecture covers integration with EDR, NAC, and firewall systems.
This page outlines a custom workflow where agents on endpoints or in the cloud identify and kill malicious processes based on behavioral analysis and threat intelligence. It demonstrates how this real-time response contains threats before data theft or encryption, reducing reliance on slower human intervention. The build covers integration with EDR APIs, process ancestry analysis, and exception handling for critical systems.
This page details a custom orchestration workflow that dynamically creates and deploys firewall rules to block malicious IPs, domains, or network segments during an active incident. It shows how this automates a key containment step, reduces configuration latency, and integrates with threat intelligence and NTA systems. Implementation covers change control, rule expiration logic, and integration with next-gen firewalls from Palo Alto, Cisco, or Fortinet.
This page explains a custom build that automatically revokes user sessions, API keys, or privileged access upon detection of credential compromise or malicious behavior. It demonstrates how this workflow instantly reduces an attacker's lateral movement capability and is critical for zero-trust architectures. The architecture covers integration with IAM (Okta, Azure AD), PAM systems, and session monitoring tools.
This page provides the architecture for a custom workflow that continuously ingests, normalizes, and prioritizes threat intelligence from multiple feeds (commercial, open-source, industry). It shows how automation enriches internal detection logic, populates blocklists, and reduces the manual labor of TI management. Implementation details include parsing STIX/TAXII feeds, deduplication, and confidence scoring for automated action.
This page outlines a custom system that automates the execution of hypothesis-driven threat hunts across log and telemetry data. It demonstrates how scheduled or triggered hunting queries can uncover stealthy threats missed by alerts, turning a manual analyst skill into a scalable, repeatable process. The build covers query generation, result analysis, case creation, and integration with data lakes like Snowflake or Splunk.
This page details a custom workflow that continuously discovers and catalogs external-facing assets, misconfigurations, and shadow IT. It shows how automating attack surface management reduces blind spots, prioritizes remediation, and hardens the organization against opportunistic attacks. Architecture covers agentless scanning, cloud API integration, and correlation with vulnerability data.
This page provides an industry-specific blueprint for a custom threat hunting workflow tailored to the regulatory and threat landscape of financial services. It focuses on automating detection for fraud, ATM jackpotting, SWIFT compromise, and insider trading, with built-in controls for compliance (GLBA, SOX). Implementation covers integration with core banking systems, trading platforms, and fraud detection engines.
This page outlines a custom workflow designed for healthcare, where agents monitor EHR access (Epic, Cerner), medical devices, and PHI data flows for signs of compromise or misuse. It demonstrates how automation enables faster response to HIPAA reportable events and reduces the risk of costly breaches. The architecture emphasizes privacy-aware monitoring, integration with clinical systems, and audit trail generation.
This page details a custom build for industrial control systems, where agents analyze OT network traffic (SCADA, Modbus) for anomalous commands, unauthorized access, and signs of ransomware. It shows how this specialized workflow protects critical infrastructure by detecting threats that bypass IT security tools. Implementation covers passive monitoring, digital twin analysis, and safe integration with OT historians and HMIs.
This page explains a custom workflow that embeds threat hunting and response directly into CI/CD pipelines and runtime environments for containerized and serverless applications. It demonstrates how automating security for cloud-native apps reduces vulnerability window and responds to runtime attacks in real-time. Architecture covers integration with Kubernetes, AWS Lambda, service meshes, and CSPM tools.
This page provides a blueprint for a custom workflow that continuously monitors privileged user and service account behavior (via PAM tools like CyberArk) for anomalies. It shows how automating this detection catches credential misuse and insider threats faster than periodic reviews. Implementation covers behavioral baselining, session recording analysis, and integration with IAM for automated access revocation.
This page outlines a custom workflow where agents detect signs of credential dumping (e.g., Mimikatz), pass-the-hash, and golden ticket attacks across endpoints and domain controllers. It demonstrates how automated detection and containment of these techniques breaks critical attacker kill chains. The architecture covers integration with EDR, Windows Event Logs, and Active Directory for real-time response.
This page details a custom build for securing container orchestration, where agents analyze pod behavior, image provenance, and network policies to detect compromise or crypto-mining. It shows how this workflow reduces the risk of container breakout and lateral movement within clusters. Implementation covers integration with Kubernetes API, service mesh telemetry, and automated pod termination or scaling.
This page explains a custom workflow that continuously detects insecure cloud resource configurations (exposed S3 buckets, permissive IAM roles) and automatically applies fixes or triggers ticketing. It demonstrates how this reduces the window of exposure and operationalizes cloud security posture management (CSPM). Architecture covers multi-cloud API integration, Infrastructure as Code (IaC) scanning, and safe change approval workflows.
This page provides a blueprint for a custom workflow that uses AI to analyze email headers, language patterns, and financial requests to detect sophisticated BEC attacks. It shows how automating this detection prevents executive impersonation and fraudulent wire transfer attempts that bypass traditional spam filters. Implementation covers integration with Microsoft 365, Google Workspace, and financial systems for automated holds or alerts.
This page outlines a custom workflow where agents analyze incoming phishing campaigns, extract IOCs, and automatically deploy blocklists across email gateways, DNS filters, and web proxies. It demonstrates how this rapid response reduces the victim count and operational burden on the SOC. The architecture covers email sandboxing, URL analysis, and integration with security gateways via APIs.
This page details a custom orchestration layer that ingests and triages high-volume EDR alerts from CrowdStrike, SentinelOne, or Microsoft Defender. It shows how correlating endpoint alerts with other context automates false positive filtering and routes true positives to the right playbook, drastically improving SOC efficiency. Implementation covers API integration, alert deduplication, and confidence scoring models.
This page explains a custom, high-speed workflow that detects ransomware encryption behaviors (mass file renaming, shadow copy deletion) on endpoints and automatically blocks the process and isolates the host. It demonstrates how this automated containment can stop an encryption event in progress, minimizing data loss. Architecture covers integration with EDR, file system monitoring, and pre-configured isolation commands.
This page provides a blueprint for a custom workflow where agents analyze full packet capture or netflow data to detect beaconing, data exfiltration, and protocol anomalies missed by perimeter tools. It shows how automating deep packet inspection and baselining improves detection for encrypted and east-west traffic. Implementation covers integration with tools like Zeek, Corelight, and network taps.
This page outlines a custom workflow that automates the deployment, monitoring, and response for honeypots and deception assets. It shows how agents can dynamically adapt decoys based on attacker behavior, automatically collect forensic data, and launch countermeasures, maximizing the ROI of deception platforms. Architecture covers integration with tools like Attivo, and automated IOC extraction from attacker interactions.
This page details a custom workflow that continuously scans data repositories (file shares, databases, cloud storage) to discover and classify sensitive information (PII, PCI, IP). It demonstrates how automating this foundational security task improves data governance, targets protection efforts, and supports compliance reporting. Implementation covers integration with data loss prevention (DLP) tools and classification engines.
This page explains a custom build that monitors database queries and transactions in real-time to detect SQL injection, unauthorized data access, and suspicious bulk exports. It shows how automating this monitoring protects crown jewel data assets and generates alerts for potential breaches. Architecture covers integration with database audit logs, DAM tools, and SIEM for correlated alerting.
This page provides a blueprint for a custom workflow that analyzes WAF logs and application traffic to automatically suggest or deploy optimized rule sets, reducing false positives and blocking novel attacks. It demonstrates how this closes the loop between detection and protection for web apps. Implementation covers integration with WAFs from Cloudflare, AWS, or F5, and safe testing in staging environments.
This page outlines a custom workflow where agents continuously test APIs for vulnerabilities (broken object level authorization, injection) and monitor runtime traffic for abuse and data scraping. It shows how automating API security integrates shift-left testing with runtime protection for modern applications. Architecture covers integration with API gateways, DAST/SAST tools, and anomaly detection models.
This page details a custom workflow designed to automate the repetitive tasks of a SOC Tier-1 analyst: alert enrichment, initial investigation, and closure of false positives or low-severity events. It demonstrates how this 'virtual analyst' increases team capacity, reduces burnout, and allows human analysts to focus on complex threats. Implementation covers playbook automation, integration with SOAR platforms, and supervised learning feedback loops.
This page explains a custom build for a dynamic, AI-augmented playbook system that executes complex incident response sequences across disparate security tools. It shows how conditional logic, agentic decision-making, and integration with ticketing and communication systems standardize and accelerate response. Architecture covers tools like Swimlane, Splunk SOAR, or custom LangGraph orchestration with human approval checkpoints.
This page provides a blueprint for a custom workflow that sits atop alerting systems, using ML to analyze alert context, historical outcomes, and environmental factors to suppress or downgrade false positives before they reach analysts. It demonstrates how this directly improves SOC signal-to-noise ratio and operational efficiency. Implementation covers feedback integration, model retraining pipelines, and transparency into suppression logic.
This page outlines a custom workflow where agents correlate low-fidelity events from disparate sources (network, endpoint, cloud) to build high-fidelity incident narratives. It shows how automating this correlation uncovers multi-stage attacks that single alerts miss, reducing dwell time. Architecture covers graph database integration, temporal analysis, and automated case creation in the SIEM or SOAR platform.
This page details a custom workflow that automatically enriches raw vulnerability scan data with asset criticality, threat intelligence, exploit availability, and network exposure. It demonstrates how this automates risk prioritization, turning overwhelming scan reports into actionable remediation tickets. Implementation covers integration with scanners (Nessus, Qualys), CMDB, and threat feeds like Exploit-DB.
This page explains a custom, high-velocity workflow that detects volumetric or application-layer DDoS attacks and automatically triggers mitigation scripts with cloud providers (AWS Shield, Cloudflare) or on-prem scrubbing centers. It shows how reducing response time from minutes to seconds preserves service availability during attacks. Architecture covers traffic baselining, anomaly detection, and API-based mitigation orchestration.
This page provides a blueprint for a custom workflow that continuously evaluates access requests against user behavior, device health, and contextual risk to dynamically grant, deny, or step-up authentication. It demonstrates how this enforces a true zero-trust model by automating policy decisions across IAM and network access controls. Implementation covers integration with ZTNA providers, SIEM, and endpoint security platforms.
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