Incident Analysis

Build me an investigation assistant in Tracecat. For an active case, have an agent query Splunk, CrowdStrike, and Okta sign-in logs around the indicators, assemble a single ordered timeline of process, network, and identity events, and write it to the case with each entry linked to its source query. Have the agent propose root cause hypotheses ranked by the evidence. First help me understand how this maps to RS.AN-03 and what separates a defensible root cause from a plausible story. Ask me which log sources I can query and their retention windows. Talk me through how the agent should mark gaps where evidence is missing.

Build me an evidence preservation automation in Tracecat. For incident cases, record every investigative action in the case timeline automatically, snapshot collected artifacts to a write-once S3 bucket in AWS with hashes computed at capture, and keep a chain-of-custody table of who collected what, when, and from where. First help me understand how this maps to RS.AN-06 and RS.AN-07, and what makes records hold up when legal or insurers ask. Ask me what retention our counsel expects for incident evidence. Talk me through what must be captured at the moment of action versus what can be reconstructed.

Build me a magnitude estimation step in Tracecat. For an active incident, count affected hosts, accounts, and data stores from Splunk queries, cross-check against asset and exposure data from Wiz, and write a magnitude estimate to the case with the queries that produced it. Re-run on demand so the estimate tracks the investigation instead of going stale. First help me understand how this maps to RS.AN-08 and why magnitude needs validation from a second source. Ask me which magnitude bands drive different responses for us. Talk me through presenting uncertainty honestly when counts are still moving.