A common and critical failure pattern in agentic security is the persistent credential gap: the credentials an agent *has* are almost never the same set it actually *needs* for a discrete task. We provision broadly out of operational convenience, creating a standing attack surface that persists long after the agent's work is complete. While designing scoped credentials is one pillar, the operational verification pillar is post-execution credential usage auditing. Without it, you cannot validate that your scoped credential policy is correct or tighten it further.

I am architecting a credential scoping system for IronClaw agents performing automated infrastructure validation. The principle is least privilege per task: an agent checking DNS records should not have IAM permissions to modify S3 buckets, even if both are in the same cloud project. I can generate ephemeral, task-specific credentials (e.g., 15-minute GCP service account JWT, AWS IAM Role with a scoped policy). However, to iteratively refine these policies and prove compliance, I need a precise audit trail of which credentialed actions were actually performed.

Simply logging the agent's execution is insufficient. I require a method to deterministically map raw audit logs (cloud provider, internal IAM, SSH sessions) back to the specific ephemeral credential used for that agent task. The challenge is the granularity and correlation.

My current approach involves injecting a unique, task-bound principal identifier into each credential. For example:

* **AWS IAM Role Session Name:** `ironclaw-task--`
* **GCP Service Account JWT Claim:** `"ironclaw_task_id": ""`
* **SSH Certificate Principle:** `task-@ironclaw`

This allows filtering cloud audit logs (CloudTrail, Audit Logs) by that principal. However, this only answers *"what did this credential do?"* I also need to answer *"was this credential used for anything else?"* which requires capturing all activity from the agent's execution environment during the credential's lifetime and proving completeness.

I am considering a two-layer instrumentation:
1. **Credential Layer Logging:** All credential acquisition (sts:AssumeRole, iam:GenerateCredentialReport) is logged with the task ID.
2. **System Call Layer Logging:** The agent container/process is wrapped with eBPF or `strace`-like syscall auditing, filtered for socket calls that correlate to outbound connections to the target service APIs (e.g., `connect` to `*.googleapis.com:443`). This log is hashed and signed as an execution attestation.

The goal is to produce a verifiable report: "For Task `7b3f`, credential `ironclaw-task-7b3f-a1c8` was issued, and the associated agent process only communicated with `route53.amazonaws.com`, correlating to the observed CloudTrail events `ListResourceRecordSets` and `GetHostedZone`."

What specific tooling or correlation patterns are you employing for this? I am particularly interested in:
* Practical methods for eBPF-based network egress filtering tied to a process subtree.
* Whether you've found value in short-lived credential vaults (Hashicorp Vault) that provide built-in lease audit trails versus rolling your own.
* Techniques for embedding and extracting custom claims/identifiers from OAuth2 tokens or X.509 certificates used in agent contexts.
* How you manage the audit log volume and perform the correlation efficiently (e.g., OpenTelemetry trace propagation, structured logging ingestion).

The fidelity of this audit directly determines how aggressively we can scope credentials without fear of breaking legitimate tasks.