Automations
This pillar focuses on response workflows that isolate systems, revoke keys, trigger backups, and notify the right stakeholders as soon as a confirmed incident is detected. Pages should explain how a custom incident workflow standardizes remediation, reduces blast radius, and connects API orchestration, security logic, and approval gates into a usable enterprise operating model.
This foundational page details the architecture for a custom, multi-agent incident response system that standardizes containment, evidence collection, and stakeholder notification. It explains how orchestrating API calls to security tools, IAM systems, and communication platforms reduces mean time to respond (MTTR) and operationalizes playbook execution across hybrid environments for enterprise security teams.
This page outlines a workflow where specialized agents automatically identify and revoke compromised credentials, API keys, and certificates across cloud IAM, vaults, and directory services. It covers the integration logic, blast radius reduction, and the critical approval gates needed to safely execute mass revocation without disrupting legitimate services, directly addressing post-breach credential exposure.
This page explains a custom orchestration layer that, upon confirmed incident detection, triggers immutable backups of critical datasets across on-prem and cloud storage. It details the architecture for prioritizing backup jobs, verifying integrity, and isolating backup sets from the primary network to ensure recoverability and reduce ransomware impact.
This page describes an intelligent notification system that parses incident severity and type to dynamically route alerts via SMS, email, and collaboration tools to the correct legal, executive, and technical teams. It focuses on reducing communication latency, ensuring regulatory compliance, and maintaining an auditable comms trail during a crisis.
This page covers a workflow where AI agents automatically correlate alerts, validate incidents, and execute initial containment actions like network segmentation or endpoint isolation. It explains how this reduces analyst toil, limits lateral movement, and provides a scalable triage architecture for SOCs facing high-volume alerting.
This page details the build of a unified orchestration engine that executes conditional response actions across AWS, Azure, and GCP security APIs. It addresses the complexity of multi-cloud incident response, showing how a custom workflow standardizes commands for resource isolation, policy enforcement, and log collection to improve consistency and speed.
This page explains a workflow that automatically enforces micro-segmentation policies in response to threat detection, dynamically updating firewall and SD-WAN rules to isolate compromised segments. It connects the business outcome of contained breaches to the technical implementation across tools like Palo Alto Networks, Cisco ACI, or cloud-native firewalls.
This page describes a proactive response system where agents continuously scan for misconfigurations, compare them against benchmarks, and trigger automated fixes. It covers the integration with CSPM and vulnerability management tools, and the governance required for safe, automated remediation that reduces the attack surface without manual intervention.
This page outlines a custom automation that ingests threat intelligence (e.g., malicious IPs, domains) and dynamically deploys blocking rules across perimeter and host-based firewalls. It focuses on the architecture for rapid IOC dissemination, rule validation, and rollback procedures to respond to DDoS or brute-force attacks in near real-time.
This page details a workflow that automatically centralizes and enriches logs from disparate sources (EDR, cloud, network) upon incident detection to accelerate forensic analysis. It explains the pipeline for normalization, correlation, and feeding a unified data lake, reducing the manual effort for investigators and improving incident context.
This industry-specific page covers a workflow where agents detect fraudulent transactions, automatically freeze accounts, trigger regulatory filings, and initiate internal investigations. It details the integration with core banking, fraud detection systems, and compliance platforms to reduce financial loss and meet strict reporting deadlines.
This page explains a HIPAA-aware response workflow where agents identify breached PHI, automatically enact data access locks, notify internal privacy officers, and prepare breach notification materials. It addresses the unique compliance requirements and system integrations (EHR, IAM) needed for healthcare incident response automation.
This page details a workflow designed for operational technology, where agents detect ransomware encryption patterns and automatically isolate affected PLCs, SCADA systems, and HMIs from the corporate network. It covers the safety-critical logic, integration with OT security monitors, and the manual override mechanisms required for plant floor environments.
This page outlines a workflow for retail where agents respond to threats like gift card fraud, credential stuffing, or inventory system compromises by blocking malicious IPs, revoking session tokens, and triggering fraud review queues. It connects the architecture to e-commerce platforms (Shopify, Magento) and CDN/WAF services to protect revenue and customer data.
This page describes a workflow where agents continuously monitor SaaS security posture (e.g., exposed S3 buckets, overly permissive IAM roles) and automatically apply least-privilege fixes. It focuses on the build for integrating with AWS Config, Azure Policy, or internal CI/CD pipelines to prevent data leaks and maintain compliance at scale.
This page covers a high-stakes workflow for energy/utilities where agents coordinate response across IT and OT, triggering isolation of control systems, rerouting grid load, and notifying NERC CIP compliance teams. It details the fail-safe design, integration with historian data, and regulatory reporting automation required for this sector.
This page explains a workflow where agents detect anomalous data exfiltration from R&D systems, automatically lock down sensitive files, revoke researcher access, and initiate legal hold procedures. It addresses integration with data loss prevention (DLP) tools, document management systems, and the chain-of-custody requirements for IP protection.
This page details a workflow for media companies where agents detect volumetric attacks, automatically scale up CDN and edge capacity, deploy scrubbing rules, and switch traffic to mitigation providers. It focuses on the architecture for maintaining service availability, integrating with Akamai/Cloudflare APIs, and cost-control during attacks.
This page outlines a sensitive workflow where agents analyze user behavior analytics (UEBA) alerts, automatically disable accounts, preserve forensic evidence from endpoints, and escalate to legal/HR. It covers the careful orchestration between IAM, endpoint detection, and HR systems, balancing security with employment law considerations.
This page describes a workflow that triggers when a compromised software vendor or third-party is detected, automatically blocking related network traffic, quarantining deployed artifacts, and notifying procurement. It explains the integration with software composition analysis (SCA), network controls, and vendor risk management platforms.
This page details a workflow that transforms validated security alerts into fully populated tickets in ServiceNow or Jira, automatically assigning them based on skill, workload, and incident type. It reduces manual SOC overhead, ensures audit trails, and integrates SIEM/SOAR platforms with IT service management tools.
This page explains a risk-based workflow where agents prioritize and deploy patches for vulnerabilities that are actively exploited in the wild, integrating threat feeds with vulnerability scanners and patch management systems. It covers the approval gates, rollback plans, and maintenance windows needed for safe, automated remediation.
This page outlines a workflow where agents automatically collect and preserve forensic evidence (memory dumps, disk images, log files) from compromised systems in a legally defensible manner. It details the chain-of-custody logging, integration with EDR tools, and secure storage architecture required for incident investigation and potential litigation.
This page describes a workflow where agents monitor outbound data flows, detect patterns indicative of exfiltration, and automatically block connections or throttle bandwidth. It covers integration with DLP, network proxies, and cloud access security brokers (CASB) to prevent data loss before sensitive information leaves the perimeter.
This page details a workflow that automatically enforces security policies (e.g., disabling unused accounts, enforcing MFA) and routes policy violation exceptions through a structured approval process. It explains the orchestration between IAM, HR systems, and ticketing platforms to maintain a strong security posture while managing business exceptions.
This page outlines a proactive response workflow where agents automatically deprovision orphaned accounts, revoke stale permissions, and remove excessive privileges identified post-incident. It focuses on integration with HR systems, Active Directory, and cloud IAM to reduce the attack surface and enforce least privilege continuously.
This page explains a workflow that ingests findings from CSPM tools like Wiz or Prisma Cloud and automatically executes remediation scripts for common misconfigurations. It details the safety controls, environment-specific logic, and integration with infrastructure-as-code repos to maintain secure cloud configurations at scale.
This page describes a proactive workflow where hunting agents analyze telemetry for IOCs, automatically enrich them with threat intelligence, and push blocking rules to security controls across the enterprise. It covers the architecture for scaling threat hunting efforts and reducing the time from discovery to enterprise-wide protection.
This page details a workflow where agents, upon detecting malware communication or phishing campaigns, automatically update internal DNS resolvers and firewalls to sinkhole or block malicious domains. It explains the integration with threat intelligence platforms and the rapid response mechanism to disrupt adversary command and control.
This page outlines a workflow that automatically aggregates incident metrics, response times, and business impact data into formatted reports for executive and board review. It focuses on the data pipeline from SIEM/SOAR, the narrative generation logic, and the secure distribution mechanisms that save dozens of manual hours per reporting cycle.
This page describes a workflow that orchestrates breach and attack simulation (BAS) tools, interprets the results, and automatically triggers remediation playbooks for failed controls. It connects continuous security validation to automated response, creating a closed-loop system for improving defensive effectiveness and reducing manual testing overhead.
This page details a critical workflow where agents automatically back up the configurations of key security tools (firewalls, SIEM, EDR) during an incident, and can restore them if tools are compromised. It addresses resilience planning, secure storage, and the recovery procedures needed to maintain security operations during a crisis.
This page explains a DevSecOps response workflow where agents, upon detecting an incident linked to a recent deployment, automatically trigger a rollback to a previous, known-good version in the CI/CD pipeline. It covers integration with GitHub Actions, GitLab, Jenkins, and the approval gates needed for safe, rapid remediation.
This page outlines a compliance-focused workflow where agents assess if an incident involves personal data, automatically trigger data mapping, draft required notifications for data protection authorities, and manage data subject requests. It details integration with privacy management platforms and the legal review loops required for regulated automation.
This page describes a workflow where AI agents analyze raw alerts, cross-reference them with asset criticality and historical data, and automatically close or escalate incidents, drastically reducing alert fatigue. It explains the logic, feedback mechanisms, and integration with SOAR platforms to improve SOC efficiency and focus.
This page details a workflow that, upon declaring a major incident, automatically spins up dedicated collaboration spaces (Slack/Teams channels), bridges communication tools, and provisions investigation resources. It focuses on reducing the chaotic setup time at the start of a crisis and ensuring all responders have immediate, structured access to tools and information.
This page explains a workflow where agents identify systems and data relevant to an incident and automatically place them under a legal hold, preventing deletion or modification. It covers integration with email archives, cloud storage, and endpoint management tools to preserve forensic integrity and meet e-discovery obligations automatically.
This page outlines a workflow that automatically provisions clean, isolated virtual machines, forensic toolkits, and data storage for investigators at the onset of a major incident. It details the cloud orchestration and security controls needed to give analysts immediate, scalable resources without manual IT ticket delays.
This page describes a workflow that dynamically routes incident alerts to different teams (L1, L2, threat intel, legal) based on real-time analysis of severity, data classification, and team availability. It explains the decision logic, on-call calendar integrations, and fallback procedures that ensure the right people are engaged without manual triage.
This page details a workflow where a central orchestrator executes pre-defined, conditional runbooks for incidents like phishing, malware, or account compromise. It breaks down the architecture for parsing incident context, calling APIs across security tools, and handling exceptions, providing a blueprint for scalable, repeatable response.
This page explains a workflow where agents automatically identify affected third-party vendors in a supply chain incident, draft and send notification emails, and track responses. It addresses the complexity of vendor communication, integrating with vendor risk management platforms and ensuring consistent, timely outreach for compliance and partnership.
This page outlines a workflow where agents ingest logs from multiple sources and automatically construct a chronological timeline of attacker activities. It focuses on the data fusion, normalization, and visualization logic that accelerates root cause analysis and saves investigators countless hours of manual log correlation.
This page describes a workflow where agents automatically assess the business impact of an incident by mapping affected assets to criticality databases, revenue systems, and regulatory scope. It explains how this automated scoring prioritizes response efforts and provides executives with immediate, data-driven impact analysis.
This page details a workflow that closes the loop between security and IT by automatically updating service desk tickets (e.g., for a compromised user's account) with remediation status and resolution notes. It integrates SOAR with ServiceNow or Jira Service Desk to improve operational transparency and reduce manual status updates.
This page outlines a workflow that monitors analyst capacity and incident queue depth, dynamically reassigning or escalating tickets to prevent burnout and bottlenecks during major incidents. It covers the integration with ticketing systems and on-call schedules to optimize SOC resource allocation under pressure.
This page explains a critical recovery workflow where agents automatically test the integrity and recoverability of backups after a ransomware or destructive attack. It details the architecture for scanning backups for malware, performing test restores, and reporting readiness, ensuring the last line of defense is actually functional.
This page describes a sensitive workflow where agents draft initial external communications (customer notifications, press statements) based on incident facts, adhering to pre-approved templates and legal guidelines. It focuses on the collaboration loop with PR and legal teams for rapid review, accelerating controlled public disclosure.
This page details a compliance workflow where agents populate regulatory report templates (e.g., for SEC, NYDFS, GDPR) with incident details, gather required evidence, and route the package through internal approval chains for submission. It automates a high-overhead, error-prone process, ensuring timely and accurate reporting.
This page outlines a cloud-native response workflow where agents automatically identify and terminate compromised Kubernetes pods, scale down affected replica sets, and deploy clean versions from secure registries. It details the integration with container security platforms and K8s APIs to contain threats in dynamic orchestration environments.
This page explains a workflow for responding to database attacks (e.g., SQL injection, credential abuse) where agents automatically kill malicious queries, reset compromised connections, and temporarily block offending IPs. It covers integration with database activity monitoring tools and the safety checks needed to avoid disrupting legitimate business transactions.
This page describes a workflow where agents, upon detecting lateral movement within a subnet, automatically update network access control lists (ACLs) or SDN policies to quarantine the entire subnet. It details the integration with NDR tools and the architecture for rapid, network-level containment to stop widespread breaches.
This page details a workflow for responding to compromised remote access, where agents automatically terminate active VPN sessions for a user or device, revoke their certificates, and force re-authentication. It explains integration with VPN concentrators (Cisco, Palo Alto) and IAM systems to quickly sever an attacker's remote foothold.
This page outlines a proactive workflow where agents analyze SIEM alert volumes and false positive rates, then automatically suggest or implement tuning adjustments to detection rules. It focuses on reducing noise for analysts and maintaining the effectiveness of the detection pipeline through continuous, data-driven optimization.
This page explains a workflow where agents ingest new attack signatures or vulnerability data and automatically deploy corresponding blocking rules in the WAF (Cloudflare, AWS WAF). It details the testing and staging process to prevent service disruption, enabling rapid protection against emerging web application threats.
This page describes a DevSecOps response workflow where agents continuously scan container registries, and upon finding a critical vulnerability in a running image, automatically pull it from production and trigger a rebuild. It integrates tools like Trivy or Clair with orchestration platforms to enforce image hygiene and prevent runtime exploitation.
This page details a workflow where agents dynamically update DNS records—for example, to point a compromised service's domain to a sinkhole or a maintenance page—as part of the containment process. It covers the integration with DNS providers (Route 53, Cloud DNS) and the rollback procedures for post-remediation recovery.
This page outlines a workflow for network resilience where agents detect DDoS or path-based attacks and automatically re-route enterprise SD-WAN traffic through alternative, clean network paths or cloud gateways. It explains integration with SD-WAN controllers to maintain business connectivity while under sustained network assault.
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One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
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We understand the task, the users, and where AI can actually help.
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We define what needs search, automation, or product integration.
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We implement the part that proves the value first.
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We add the checks and visibility needed to keep it useful.
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