AI Cyber Defense / Network detection, DNS and egress analytics
AI Cyber Defense: Detect proxy bypass from managed endpoints
Restrict direct outbound paths where the architecture requires a proxy and provide explicit exceptions for services that cannot use it. Monitor bypass attempts independently.
Environment and inputs: Network detection and response using resolver logs, proxy metadata, flow records and optional Zeek or Suricata sensors.
Scenario and goal
An endpoint may reach external services directly after a route or client configuration change.
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
Compare managed proxy configuration, direct egress flows and destination reachability for the same device population.
Validate with an authorized exercise
Use a test host to reach an approved site through the proxy and attempt a disallowed direct path; verify the latter is denied and the event identifies the originating device.
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.