AI Cyber Defense / Network detection, DNS and egress analytics
AI Cyber Defense: Protect telemetry when attackers use common cloud endpoints
Allow approved enterprise tenants and workflows using supported controls. Require additional review for transfers to unknown accounts from sensitive systems.
Environment and inputs: Network detection and response using resolver logs, proxy metadata, flow records and optional Zeek or Suricata sensors.
Scenario and goal
Abuse of a popular storage or collaboration service can hide inside ordinary encrypted traffic.
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
Correlate tenant or account identifiers where available, resource access logs, upload activity and endpoint context rather than blocking the provider wholesale.
Validate with an authorized exercise
Exercise a benign test upload to an approved tenant and a policy-denied synthetic external-account transfer; verify the decision identifies the account boundary.
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.