AI Cyber Defense / Network detection, DNS and egress analytics
AI Cyber Defense: Join Suricata alerts to flow and application context
Route high-consequence alerts to a case that includes matching connection and application events. Tune only after inspecting representative true and benign matches.
Environment and inputs: Network detection and response using resolver logs, proxy metadata, flow records and optional Zeek or Suricata sensors.
Scenario and goal
An individual network signature may not show whether a suspected request succeeded or reached a sensitive service.
Why it matters
For this scenario, expect behavior to vary across destinations, timing and client software. Network metadata supports a hypothesis, while endpoint and identity records often explain the actor and purpose. Account for encryption, sampling and sensor placement before interpreting absence. A statistical anomaly, protocol fingerprint or unfamiliar domain should remain a supporting observation until its consequence and business context are established.
Evidence to collect
Preserve the alert signature, flow identifier, timestamps and related protocol records together with destination asset context.
Validate with an authorized exercise
Replay a safe stored event fixture with related flow records; verify the case links the records and distinguishes a blocked request from an observed alert with unknown outcome.
Rollout and checks
Preserve event time, source tuple, sensor identity and the original record identifier for every decisive observation. Verify clock alignment and collection health before joining sources. Compare a representative benign workload with the suspected behavior in a lab or stored-event replay. Adjust a detection only after documenting which observed distinction justifies the change.
Scope and limits
This guide proposes a defensive test; it is not a tested production design. Check platform support and local requirements. References explain the mechanisms but do not certify the design. Behavior alone does not prove AI involvement.