Secret and Credential Scanner
Scan pasted text, code, or config files for accidentally exposed API keys, tokens, passwords, and private keys. Detects 50+ secret types across AWS, GitHub, Stripe, OpenAI, and more — all client-side, nothing leaves your browser.
How to Use Secret and Credential Scanner
How to Use the Secret and Credential Scanner
Step 1: Paste Your Text
Paste any text into the scanner: environment variable files, Docker Compose configs, CI/CD pipeline definitions, code snippets, log output, or any other text that might contain credentials. You can also click an example preset to test with sample secrets.
Step 2: Review the Results
The scanner checks your input against more than 50 regex patterns in real time. Results are grouped by severity:
| Severity | Meaning | Example |
|---|---|---|
| Critical | Immediate risk — rotate now | AWS access key, Stripe secret key, RSA private key |
| High | Significant risk — rotate soon | GitHub PAT, Slack bot token, Twilio SID |
| Medium | Review carefully | JWT token, bearer token in header, generic password assignment |
Each finding shows the secret type, the line number it was found on, and a redacted preview (click Show redacted match to reveal the first and last few characters).
Step 3: Rotate and Remove
If the scanner finds real credentials:
- Rotate them immediately in the relevant service dashboard — treat them as compromised regardless of whether they were actually accessed.
- Remove or replace them with environment variable references such as process.env.STRIPE_SECRET_KEY.
- If the file was committed to git, delete is not enough — the secret remains in git history. Use git filter-repo or BFG Repo Cleaner to purge the history, then force-push.
- Review access logs in the affected service for unauthorized use.
Secret Categories Detected
| Category | Examples |
|---|---|
| Cloud | AWS access keys, GCP service accounts, Azure connection strings |
| Version Control | GitHub PATs, GitLab tokens |
| Payment | Stripe, Square, Braintree, Shopify |
| Communication | Slack, Discord, Telegram, SendGrid, Mailgun, Twilio |
| AI / ML | OpenAI, Anthropic, Hugging Face |
| Infrastructure | DigitalOcean, NPM, Databricks |
| Cryptographic Keys | RSA, EC, OpenSSH, PGP private keys |
| Auth Tokens | JWT, Bearer tokens, Basic auth in URLs |
| Database | MongoDB, PostgreSQL, MySQL, Redis connection strings |
| Generic | Password assignments, API key assignments (higher false positive rate) |
About False Positives
Generic patterns such as password = ... or api_key = ... have a higher false positive rate because they match configuration examples and placeholder values. The scanner marks these findings with a note. Specific patterns such as AKIA... for AWS or ghp_... for GitHub have very low false positive rates because the prefix is unique to that service.
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