AI Cyber Defense / Network detection, DNS and egress analytics
AI Cyber Defense: Handle asymmetric routing in network investigations
Document where bidirectional visibility is expected and expose one-sided capture as a data-quality field. Move or supplement sensors only after understanding the traffic path.
Environment and inputs: Network detection and response using resolver logs, proxy metadata, flow records and optional Zeek or Suricata sensors.
Scenario and goal
A sensor seeing only one direction can produce incomplete sessions and misleading byte ratios.
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
Inspect routing changes, capture interfaces, connection state and corroborating firewall observations for both directions.
Validate with an authorized exercise
Route a harmless lab response through a second path and verify the analysis marks partial visibility instead of claiming the remote peer sent no data.
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.