What should you measure in a dependency intake queue?
Five metrics show whether dependency intake works: time to decision, queue age, bypass rate, active exceptions and reopen rate. Here is how to track each.
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Five metrics show whether dependency intake works: time to decision, queue age, bypass rate, active exceptions and reopen rate. Here is how to track each.
Track acceptance, revert, rework, review time and rejection reasons during a manual trial. Set thresholds first, then decide whether to raise autonomy.
Log who ran the agent, which tools it called, which files changed and which approvals were given. Keep prompts for a shorter window than action records.
Log request IDs, outcomes, idempotency keys and timings. Never log keys, tokens, card data or message bodies. Review logs often for sensitive leftovers.
Keep tokens, secrets, session IDs and sensitive personal data out of AI agent logs, or mask them. Here is a checklist for prompts, tool calls and outputs.
Give contractors a synthetic dataset, a seed script and a scoped staging account, not a production dump. A package list and a short handover checklist.
Fix what is known to be exploited and reachable first. Check the CISA KEV list, then EPSS, then whether your code uses the flawed part. A simple order.
Before the first scanner, fix the ground it runs on: an inventory, multi-factor sign-in, protected branches, ownership, and a place to track findings.
When a security tool trial ends, export what you need, revoke access, request deletion in writing and confirm it. Here is a close out checklist.
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