Topic starter
14/09/2026 10:10 am
TL;DR: Claude Code and Codex telemetry can be normalized into OCSF security events so teams can query agent actions, denials, and outcomes alongside existing security data, according to TENZIR. The bigger issue is governance: if agents can act with user access, security teams need consistent records, privacy controls, and session context to make those actions auditable.
Editorial analysis by NHI Mgmt Group, based on content published by TENZIR: “From AI agent actions to OCSF security events”.
Key questions
Q: How should security teams handle AI agent telemetry that is recorded in different harness formats?
A: Security teams should normalize agent telemetry into a shared security event model before relying on it for detection or investigation.
Q: Why does session context matter when investigating AI coding agent activity?
A: Session context ties a command or prompt to the specific agent instance that generated it, which is essential when agents act with user access.
Q: What breaks when AI agent approvals and execution outcomes are logged separately?
A: What breaks is control attribution.
Practitioner guidance
- Normalize agent logs into a shared event model Map tool decisions, tool results, prompts, and session identifiers into a common schema so SIEM queries can work across different agent harnesses.
- Preserve session-bound identity context Retain ai_agent name, instance UID, and command identifiers together so investigators can reconstruct which agent performed which action in which session.
- Separate approval from execution outcome Record human approval, automated policy decisions, sandbox denials, and process success as distinct states so control effectiveness is measurable.
Bottom line: AI coding agents need normalized telemetry because raw harness logs are too inconsistent for security operations to query at scale.
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14/09/2026 10:11 am
AI agent telemetry has to be governed as security evidence, not application noise. If a coding agent can run commands and change files, the telemetry is part of the control plane, not just the product log stream. OCSF mapping makes that evidence usable across SIEM, security lake, and investigation workflows. Practitioners should treat agent event normalization as a security architecture decision, not a logging preference.
A few things that frame the scale:
- 7% of security leaders admit they do not know how often their AI systems are making autonomous changes to infrastructure, according to the 2026 Infrastructure Identity Survey.
- Claude Code-assisted commits leaked secrets at a rate of 3.2%, more than double the human-only baseline of 1.5%, with peaks reaching 31 secrets per 1,000 commits in August 2025, according to the State of Secrets Sprawl 2026.
A question worth separating out:
Q: How should organisations decide whether AI agent telemetry belongs in the SIEM or security lake?
A: Place the normalized telemetry where security teams already investigate, but only after privacy controls and field mapping are in place. The right destination is less important than preserving queryable session context, command detail, and outcome state. If the data cannot support detections or investigations, storing it in a security platform adds noise rather than visibility.
👉 Read our full editorial: AI agent telemetry mapped to OCSF closes an observability gap