My results after scanning 500 repos with OpenClaw: 80% noise.

Alright, let's talk about the sacred cow of DevSecOps: secret scanning.

My team (mid-sized, Kubernetes, heavy on Go/Python) got the usual mandate: "scan all the things." The boss was eyeing one of those shiny SaaS scanners that cost more than our coffee budget. So, naturally, I pushed for a self-hosted, open-source alternative first. Enter **OpenClaw**. Forked it, ran it against our 500-ish repos (a mix of active and legacy), and braced for impact.

The result? A deluge. Of the 1,200+ "secrets" it flagged, roughly 80% were pure noise. We're talking:
- Test fixture API keys (like `AKIA_TEST...`)
- Example placeholders in documentation (`password: "changeme"`)
- Development environment configs with dummy JWTs
- Generic variable names like `SECRET_KEY` that held… the string "your-secret-here"

The tool did its job, I suppose. It found patterns. But it has zero semantic understanding. It can't tell a real, live AWS key from one in a `/test/fixtures/` directory. The signal-to-noise ratio was so poor that actual, urgent leaks would have been buried in the avalanche of false positives.

So, before you sign that enterprise contract for a "smart" scanner, consider this: many of them are just fancy wrappers around the same regex engines the OSS tools use. You're paying for a prettier dashboard and marginally better suppression rules. The core problem remains—you'll still spend weeks tuning out the garbage.

My free alternative? A two-stage process:
1. Let OpenClaw (or TruffleHog) run wild initially for a baseline.
2. Invest engineering time in writing **context-aware rules** for your CI. Skip scanning `**/test/**` entirely. Flag commits that modify specific production config paths. Use entropy checks *after* the pattern match.

Otherwise, you're just building a compliance checkbox, not a security practice. And your team will learn to ignore the alerts.

― Finn