GitHub Actions Secret Sprawl Detector
3.00 in critical CI/CD credentials and unmasked secret sprawl exposures identified across across 3 items.
Plaintext AWS Access Key committed to workflow YAML line 42. Violates Rule 1. Requires immediate credential rotation.
Method1Scanned workflow AST parse trees against entropy patterns and API token signatures.
2Generated automated GitHub Secrets migration patches and credential rotation directives.
| Reference | Description | Critical_Exposures |
|---|---|---|
| frontend-web-app | Hardcoded AWS Secret Key in Deployment Workflow | 1.00 |
| build-release.yml | Stripe Live Secret Key Exposed in Mobile Build | 1.00 |
| backend-api-core | Plaintext Production DB Password in Tests | 1.00 |
GitHub Actions workflow YAML definitions and runner build log archives, plus regex secret pattern dictionaries
Remediated workflow YAML patch and exposed credentials revocation worklist (Resolution Dossier, Findings Schedule)
Open GitHub Actions Secret Sprawl Detector on sample data now with no sign-up, then run your own files free for 14 days. $2,500 a month after that, cancel any time. 30% goes to the referring partner.
Read in memory for the session, never stored, never used to train a model.
Outputs are computed from your inputs and the tool's rules. Check them before you rely on them.
14 days on your own files, then $2,500 a month.
Open GitHub Actions Secret Sprawl Detector on sample data now with no sign-up, then run your own files free for 14 days. $2,500 a month after that, cancel any time.
On a sample file: 3.00 in critical CI/CD credentials and unmasked secret sprawl exposures identified across across 3 items.
Why not just use ChatGPT?
Rules that stay current: the rate cards, tariffs, code sets and regulations it checks against are kept up to date for you; a one-off prompt starts from nothing each time. Evidence that stands up: every finding cites the line, the file and the rule, so it holds up with a vendor, a payer or an auditor. The same answer every time: the checks are written rules, not a fresh guess, so this month's result can be compared with last month's. Nobody has to own it: no one inside has to build, test and maintain a home-made tool, and files are not pasted into a public chatbot.
Start on your own files
If you would rather talk it through, write to dev.sathya@baseloom.app; that reaches Dev Sathya, founder.