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Nullify's secrets detection catches hardcoded credentials in code review, then tests each one against the real provider. Live keys go to the top of the queue with an owner attached.
Illustrative example. Real ratios depend on your codebase.
Keys get rotated, revoked and re-used. Nullify checks each one against the live provider, and every answer names the evidence it came from.
It can't tell a live key from a dead one.

Checked against the provider itself.
Yes. It authenticated against AWS just now and can write to the exports bucket. The owner has been notified with the rotation steps.
SourcesPattern matching catches credentials with a known format. NLP catches free-form secrets that don't follow one, like a password left in a comment.
Each candidate is tested by authenticating with the provider that issued it. A key that works is an active exposure, not a pattern match.
Each step cuts the list. By the time a finding reaches someone, it's confirmed live, ranked, and addressed to the person who can rotate it.
The finding names a suspected owner and comes with rotation guidance, so the right person acts first.
Secrets detection runs as part of Nullify's code review, so a hardcoded credential is flagged on the pull request that adds it. Live keys are escalated to their suspected owner ahead of everything else.
Live AWS key found in payments-api. Suspected owner @j.chen, rotation guidance attached.
This change adds a live AWS key. Removing it from the commit won't revoke it, so rotate it at the provider first.
Nullify authenticates with each candidate and captures evidence of what the credential can access.
AI-native static analysis across 16 languages, including business-logic flaws.
Prioritize by reachability and impact, then ship merge-ready fixes.
Secrets Detection docs · Supported secret categories · Code Security · Triage & Remediation
Most secrets scanners stop at pattern matching, which means every finding still needs a human to check whether the credential actually works. Nullify goes a step further: after pattern matching and NLP find a candidate, Nullify attempts to authenticate with it against the real provider — AWS, GCP, Azure, GitHub, GitLab, Stripe, Slack. A confirmed-live secret is treated as an active exposure and prioritized; a dead or already-rotated key is still reported, just not paged as urgent.
The finding is tagged with a suspected owner and rotation guidance, so the person who can actually rotate the credential is pointed at it directly instead of the whole team getting a generic alert. Live secrets are prioritized ahead of everything else in the queue.
No — rotating a live credential is a provider-side action Nullify doesn't have standing access to perform. Nullify finds the secret, confirms whether it's live, identifies a suspected owner, and provides rotation guidance; a human completes the rotation.
Findings are sorted into 5 categories, including PII — so hardcoded personal data gets flagged alongside API keys, tokens and other credentials. The full category breakdown is in the docs.
The AI harness that finds leaked secrets, proves whether they work and routes each one to its owner.