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Secret audit & metrics

In a Zero Trust model, every secret access must be attributable to an identity and a purpose. Alquimia Platform emits telemetry that lets you compare secret-fetch rates against actual task volume, so you can spot credential harvesting, misconfiguration, or confused-deputy attacks.

The runtime resolves many secrets during inference: API keys, database credentials, signing keys, and channel tokens. If a role fetches secrets without a matching task volume, or if a master instance fetches secrets during inference, something is wrong.

SignalWhat it tells you
Secret resolution rateHow often each role, agent, and runtime mode resolves secrets.
Task volumeHow many inference tasks are started per agent and agentspace.
Fetch outcomeWhether fetches succeeded, failed because the secret was missing, or errored.
Source of fetchWhether the fetch happened during registry inspection or agent execution.
PatternPossible cause
Secret fetch rate spikes without task-volume growthA tool or loop is resolving secrets repeatedly, or credentials are being harvested.
Idle role fetching secretsA compromised or misconfigured workload is accessing credentials.
Inference-mode fetches on a masterThe master deployment is incorrectly running worker logic.
High missing-secret rateA secret was not registered or a reference name is wrong.
  1. Identify the role, agent, and source labels from the alert.
  2. Compare secret-fetch metrics with task-start metrics for the same scope.
  3. Inspect the worklog for the affected sessions to see what the agent was doing.
  4. Check Kafka topic ACLs and event signatures to rule out unauthorized producers.
  5. Verify the runtime mode and deployment topology of the affected pods.
  • Rotate credentials for the affected role or agentspace.
  • Narrow Vault policies to limit unnecessary access.
  • Fix misconfigurations that cause repeated secret fetches.
  • Separate master and worker deployments if they are mixed.
  • Add or tune alerts based on your baseline traffic patterns.