AttackRuleMap vs Query.AI Federated Detections: Side-by-Side Comparison (2026)
Features, pricing, ratings, and pros & cons — compared head-to-head.
AttackRuleMap is a free detection engineering tool by ATT&CK Rule Map. Query.AI Federated Detections is a commercial detection engineering tool by Query.AI. Compare features, ratings, integrations, and community reviews side by side to find the best detection engineering fit for your security stack.
CST VerdictBased on our analysis of NIST CSF 2.0 coverage, core features, integrations, company size fit, here is our conclusion:
Startup security teams building threat models from scratch should use AttackRuleMap to connect MITRE ATT&CK techniques directly to testable atomic actions, compressing what usually takes weeks of manual mapping into hours. The tool is free and cloud-deployed, removing budget and infrastructure friction at the stage where most startups can't afford a dedicated threat modeling platform. Skip this if your team needs automated detection rules or response playbooks; AttackRuleMap is a planning and validation tool, not an operational security control.
Mid-market and enterprise security teams with fragmented data across multiple SIEMs, data lakes, and cloud platforms will get the most from Query.AI Federated Detections because it runs threat hunts and detections without forcing you to centralize or ingest everything into a single repository. The library of 1,000+ pre-built FSQL recipes lets you start detecting in days rather than months of tuning custom correlation rules. Skip this if your organization has already consolidated on a single SIEM with deep historical retention and wants tight coupling to your existing detection workflow; Query.AI shines when data governance or cost makes centralization impractical, not when you already have it.
