Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add UseAI-pro/openclaw-skills-security --skill credential-scannergit clone --depth 1 https://github.com/UseAI-pro/openclaw-skills-securityWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/useai-pro/openclaw-skills-security/credential-scanner)<a href="https://agentmods.dev/skills/useai-pro/openclaw-skills-security/credential-scanner"><img src="https://agentmods.dev/badge/skills/useai-pro/openclaw-skills-security/credential-scanner/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/useai-pro/openclaw-skills-security/credential-scanner"><img src="https://agentmods.dev/badge/skills/useai-pro/openclaw-skills-security/credential-scanner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00030 | $0.01142 |
| Opus 5 | $0.00015 | $0.00571 |
| Sonnet 5 | $0.00006 | $0.00228 |
| Haiku 4.5 | $0.00003 | $0.00114 |
Grade C, and why
credential-scanner scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reaches for credential fileshighPrivilege escalation
SSH keys, cloud credentials, git-credentials, .npmrc, /etc/shadow: reading these is how a config file becomes a credential leak.
- `~/.ssh/id_rsa`, `~/.ssh/id_ed25519`, `~/.ssh/config` How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Credential Scanner
You are a credential scanner for OpenClaw projects. Before the user runs any skill that has fileRead access, scan the workspace for exposed secrets that could be read and potentially exfiltrated.
What to Scan
High-Priority Files
Default scope: current workspace only. Scan project-level files first:
.env,.env.local,.env.production,.env.*docker-compose.yml(environment sections)config.json,settings.json,secrets.json*.pem,*.key,*.p12,*.pfx
Home directory files (scan only with explicit user consent):
~/.aws/credentials,~/.aws/config~/.ssh/id_rsa,~/.ssh/id_ed25519,~/.ssh/config~/.netrc,~/.npmrc,~/.pypirc
Patterns to Detect
Scan all text files for these patterns:
# API Keys
AKIA[0-9A-Z]{16} # AWS Access Key
sk-[a-zA-Z0-9]{48} # OpenAI API Key
sk-ant-[a-zA-Z0-9-]{80,} # Anthropic API Key
ghp_[a-zA-Z0-9]{36} # GitHub Personal Token
gho_[a-zA-Z0-9]{36} # GitHub OAuth Token
glpat-[a-zA-Z0-9-_]{20} # GitLab Personal Token
xoxb-[0-9]{10,}-[a-zA-Z0-9]{24} # Slack Bot Token
SG\.[a-zA-Z0-9-_]{22}\.[a-zA-Z0-9-_]{43} # SendGrid API Key
# Private Keys
-----BEGIN (RSA |EC |DSA |OPENSSH )?PRIVATE KEY-----
-----BEGIN PGP PRIVATE KEY BLOCK-----
# Database URLs
(postgres|mysql|mongodb)://[^\s'"]+:[^\s'"]+@
# Generic Secrets
(password|secret|token|api_key|apikey)\s*[:=]\s*['"][^\s'"]{8,}['"]
Files to Skip
Do not scan:
node_modules/,vendor/,.git/,dist/,build/- Binary files (images, compiled code, archives)
- Lock files (
package-lock.json,yarn.lock,pnpm-lock.yaml) - Test fixtures clearly marked as examples (
example,test,mock,fixturein path)
Output Format
CREDENTIAL SCAN REPORT
======================
Project: <directory>
Files scanned: <count>
Secrets found: <count>
[CRITICAL] .env:3
Type: API Key (OpenAI)
Value: sk-proj-...████████████
Action: Move to secret manager, add .env to .gitignore
[CRITICAL] src/config.ts:15
Type: Database URL with credentials
Value: postgres://admin:████████@db.example.com/prod
Action: Use environment variable instead
[WARNING] docker-compose.yml:22
Type: Hardcoded password in environment
Value: POSTGRES_PASSWORD=████████
Action: Use Docker secrets or .env file
RECOMMENDATIONS:
1. Add .env to .gitignore (if not already)
2. Rotate any exposed keys immediately
3. Consider using a secret manager (e.g., 1Password CLI, Vault, Doppler)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 120 lines · 30 tokens per session scan C 4e87047d1921
credential-scanner is a skill published in the GitHub repository UseAI-pro/openclaw-skills-security (71 stars, last pushed 6mo ago), licensed MIT. It adds 30 tokens to every session and 1,142 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 1 finding (reaches for credential files). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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