Topic starter
01/08/2026 9:00 pm
TL;DR: Publishable credentials and other non-secrets can dominate generic secrets scans, according to Aikido, and adding suppression rules for common public-by-design key types cut false positives by 2.37% across a 100GB Common Crawl test, removing 27,886 manual reviews. The operational lesson is that secrets governance now depends as much on precision triage and context as on raw detection volume.
Editorial analysis by NHI Mgmt Group, based on content published by Aikido: “Better generic secrets detection starts with finding non-secrets”.
Key questions
Q: How should security teams reduce false positives in generic secrets scanning?
A: Start by removing credential types that are public by design, then add contextual checks for keys whose risk depends on platform permissions or surrounding code.
Q: Why do publishable API keys create so much noise in secrets scanning?
A: They often look like secrets even though they are intended to be public or embedded in client-side code.
Q: What are the signs that a secrets detection rule is too broad?
A: A queue dominated by known public credentials, repeated reviewer dismissals, and little improvement in true-positive yield are strong signs.
Practitioner guidance
- Implement suppression rules for public-by-design credentials Create detection exclusions for credential types that are intentionally public, such as publishable keys, and document the product- or platform-specific rationale for each rule.
- Use context to distinguish token classes Require nearby keywords, product names, or platform context before classifying a match as a candidate secret when the string shape is ambiguous.
- Keep liveness checks for overlapping formats When a publishable and a secret credential share the same shape, keep the liveness check and only suppress the non-secret result after confirming the access behaviour.
Bottom line: Generic secrets scanners can overwhelm teams with non-secret matches unless public-by-design credential types are filtered early.
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01/08/2026 9:07 pm
Generic secrets detection is now a governance problem, not just a regex problem. Once scanners start catching public-by-design keys, the real control question becomes which findings deserve human attention and which should be suppressed by policy. That moves secrets programmes toward classification, context, and lifecycle governance rather than simply expanding pattern libraries. The practitioner conclusion is that detection precision is a control objective in its own right.
A question worth separating out:
Q: Should teams suppress sandbox and test credentials from secret scans?
A: Not by default. Sandbox keys can still matter if the test environment contains production data, internal systems, or misconfigured permissions. The safer approach is to triage them separately and evaluate the environment behind the credential, rather than assuming every test key is harmless.
👉 Read our full editorial: Better secrets detection starts by filtering non-secrets