Automation Workflow for Real-Time Threat Intelligence Ingestion and Scenario Creation

Manual phishing scenario authoring is a 4–8 hour bottleneck per campaign, requiring security analysts to research threats, draft lures, and build landing pages. This workflow automates that entire process by ingesting structured (STIX/TAXII) and unstructured (advisory reports, dark web forums) intel feeds, mapping IoCs to pre-built narrative templates, and generating complete, deployment-ready simulations within minutes. The time savings directly translate to higher campaign frequency and analyst capacity for strategic work.

When a new phishing kit or BEC tactic emerges, traditional training programs take weeks to manually develop a relevant simulation, by which time the threat is already active in your environment. This workflow parses real-time feeds from platforms like Recorded Future, CrowdStrike Falcon, or open-source monitors, identifies high-fidelity attack patterns, and triggers the generation of a corresponding simulation campaign. This reduces the defensive lag, ensuring your workforce is tested against—and learns to recognize—threats while they are still current.

Generic, off-the-shelf phishing simulations have diminishing returns as employees become familiar with static templates. By grounding every campaign in fresh, externally-validated threat data, this workflow ensures training remains unpredictable and relevant. The system tracks which real-world TTPs (from frameworks like MITRE ATT&CK) are used in each simulation, allowing you to measure workforce resilience against specific adversary behaviors over time, not just generic 'click rates.' This creates a direct line from threat intelligence spend to quantifiable risk reduction.

Implementation uses a LangGraph or similar orchestration layer to coordinate specialized agents: an Ingestion Agent that polls and normalizes intel feeds, a Parsing & Enrichment Agent that extracts entities and maps to templates, a Scenario Generation Agent that calls LLMs and APIs (e.g., for deepfake synthesis), and a Deployment Agent that interfaces with platforms like KnowBe4 or Proofpoint Security Awareness Training. Critical human-in-the-loop approval gates are configured for new threat categories or high-fidelity impersonations before campaign launch, ensuring ethical and operational control.

The workflow is built as a continuous pipeline, not a batch job. It runs on triggers from intel feed updates or on a scheduled cadence (e.g., daily). Each simulation generated is versioned and logged with full provenance: source intel, template used, and any modifications. A dedicated observability dashboard tracks pipeline health, intel source freshness, campaign generation status, and exception queues for scenarios that failed validation (e.g., for inappropriate content). This operational rigor is essential for running this as a production system, not a proof-of-concept.

A practical build starts by integrating 1-2 high-signal intel feeds (e.g., a commercial TI platform and RSS from CISA) with your existing security awareness training platform's API. Phase 1 automates email phishing generation; Phase 2 adds multi-channel (SMS, social) and deepfake synthesis. Key constraints to solve are data sanitization (removing real victim data from intel), content safety filters for generative AI, and exception routing for low-confidence intel. A typical pilot demonstrates automated generation of 10-15 targeted campaigns within a 6-week window, proving the ROI before enterprise rollout.

This autonomous agent continuously monitors and ingests structured (RSS/API feeds from Recorded Future, AlienVault OTX) and unstructured (dark web forums, security advisories) threat intelligence. It uses NLP to extract key entities: attacker TTPs, target industries, lure themes, and indicator patterns. The parsed data is normalized into a structured knowledge graph, creating the raw material for scenario generation and eliminating the manual daily 'intel digest' review that delays training deployment by days.

A rules-based orchestration layer maps extracted threat intel to a library of scenario templates (e.g., BEC, credential harvest, vishing). It enriches templates with current context—substituting in real-world breach names, spoofed sender domains from recent campaigns, and relevant compliance jargon (e.g., 'HIPAA violation notice'). This component replaces the manual, creative-heavy work of security analysts drafting believable lures, ensuring each simulation is both timely and technically credible.

This stateful agent manages the end-to-end campaign lifecycle. It selects target employee cohorts based on risk profiles or role, schedules deployment via integrated email/SMS/collaboration tool APIs (e.g., Microsoft Graph, Twilio, Slack), and tracks interactions (clicks, reports). It handles conditional logic, such as triggering a follow-up smishing message if the initial email is ignored, simulating multi-stage APT behavior. This automates the administrative burden of campaign management across global subsidiaries.

A critical governance agent acts as a final approval layer before any simulation is deployed. It checks generated content against internal policies, redacts any accidentally ingested real PII, ensures cultural/regional appropriateness, and logs the decision rationale for audit trails. This automated control layer is essential for operational trust, preventing simulation misfires that could cause employee relations issues or compliance violations, a key risk in manual processes.

This component automatically ingests campaign results from the simulation platform (e.g., KnowBe4, Cofense) and security tools (email gateway logs, SIEM). It calculates KPIs (click-rate, report-rate), identifies high-risk individuals or departments, and pushes enriched data to BI dashboards (Tableau, Power BI) and the SIEM for correlation with real incidents. It eliminates days of manual monthly reporting and provides continuous, data-driven visibility into program ROI and workforce risk posture.

The workflow's operational backbone is a set of pre-built, maintainable API connectors and adapters for key systems: Threat Intel Platforms (TIPs), Security Awareness Platforms, HRIS (for employee cohorts), IAM (for risk context), and Collaboration Tools. Built on an orchestration framework like LangGraph or Temporal, this framework ensures reliable execution, error handling, and the ability to incorporate new data sources (e.g., a new dark web monitor) without rebuilding core logic.