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 oyi77/1ai-skills --skill security-agentgit clone --depth 1 https://github.com/oyi77/1ai-skillsWrote 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/oyi77/1ai-skills/security-agent)<a href="https://agentmods.dev/skills/oyi77/1ai-skills/security-agent"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/security-agent/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/oyi77/1ai-skills/security-agent"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/security-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector 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 | $0.00019 | $0.01218 |
| Opus 5 | $0.00010 | $0.00609 |
| Sonnet 5 | $0.00004 | $0.00244 |
| Haiku 4.5 | $0.00002 | $0.00122 |
Grade A, and why
security-agent scanned grade A with 0 findings 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 9d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Agent
Quick Reference — see parent for full agent ecosystem.
The Security Agent scans code changes, endpoints, and configurations for vulnerabilities before they reach production. It combines static analysis (Semgrep, CodeQL), secret scanning (Gitleaks, TruffleHog), dependency auditing, and dynamic probing to surface findings ranked by severity with evidence and fix recommendations. Its adversarial mindset assumes every input is malicious and every exposed endpoint is an attack surface.
When Not to Use
- Simple or one-off tasks — if the task is straightforward, direct execution is faster than structured methodology.
- Already established workflows — follow existing team conventions rather than introducing new frameworks.
- When automation overhead exceeds benefit — for very small scopes, the setup cost may not be justified.
Dependencies
- Python 3.8+ or Node.js 18+
- Access to relevant APIs/services for your specific use case
- Basic understanding of the domain concepts
Commands
# Refer to the skill's usage section for specific commands
# Adapt these to your workflow
Key Responsibilities
- Static vulnerability scanning: Run SAST rules for injection (SQL, command, template), XSS, SSRF, insecure deserialization, auth bypass, and cryptography misuse across every changed file
- Secret detection: Scan diffs, commit history, and config files for hardcoded credentials, API keys, tokens, and private keys — including encoded/obfuscated secrets
- Dependency audit: Check for known CVEs in direct and transitive dependencies; flag supply chain risks from typosquatting, abandoned packages, and suspicious maintenance patterns
Code Example
"""Minimal security agent pattern — scan a diff for vulnerabilities."""
import json, sys, re
def scan_diff(diff_text: str) -> dict:
findings = []
lines = diff_text.split("\n")
patterns = {
"P1": {
"eval": r"\beval\s*\(",
"exec": r"\bexec\s*\(",
"raw_sql": r"\.execute\(.*['\"].*SELECT|INSERT|UPDATE|DELETE",
"hardcoded_key": r"(?:sk-|pk-|AKIA|-----BEGIN (?:RSA |EC )?PRIVATE KEY-----)",
},
"P2": {
"pickle_load": r"pickle\.loads?\(",
"assert_true": r"assert True",
"debug_endpoint": r"@app\.route\(.*['\"]/debug",
"insecure_hash": r"hashlib\.md5|hashlib\.sha1",
}
}
for severity, checks in patterns.items():
for name, pattern in checks.items():
for i, line in enumerate(lines):
if line.startswith("+") and re.search(pattern, line):
findings.append({
"file": "changed_file", "line": i,
"severity": severity, "type": name,
"finding": f"Potential {name} detected",
"recommendation": "See OWASP cheat sheet for safe alternatives"
})
return {
"findings": findings,
"summary": {
"P1": len([f for f in findings if f["severity"] == "P1"]),
"P2": len([f for f in findings if f["severity"] == "P2"]),
"P3": len([f for f in findings if f["severity"] == "P3"])
},
"verdict": "blocked" if any(f["severity"] == "P1" for f in findings) else "needs_review" if findings else "clean"
}
if __name__ == "__main__":
diff = sys.stdin.read()
result = scan_diff(diff)
print(json.dumps(result, indent=2))
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.
- 9d ago First seen · 134 lines · 19 tokens per session scan A 88a7cc27628a
security-agent is a skill published in the GitHub repository oyi77/1ai-skills (12 stars, last pushed yesterday), licensed MIT. It adds 19 tokens to every session and 1,218 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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