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 vasilyu1983/AI-Agents-public --skill qa-security-testinggit clone --depth 1 https://github.com/vasilyu1983/AI-Agents-publicWrote 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/vasilyu1983/ai-agents-public/qa-security-testing)<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/qa-security-testing"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/qa-security-testing/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/vasilyu1983/ai-agents-public/qa-security-testing"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/qa-security-testing.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 | $0.00033 | $0.03595 |
| Opus 5.5 | $0.00013 | $0.01438 |
| Sonnet 5.5 | $0.00007 | $0.00719 |
| Haiku 4.5 | $0.00003 | $0.00360 |
Grade A, and why
qa-security-testing 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 12d 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA Security Testing
Automated security testing pipelines that integrate scanners into CI/CD, enforce vulnerability gates, and drive findings through remediation. This skill covers the testing automation side of security; for secure design, threat modeling, and architecture review, use software-security-appsec.
Quick Start
- Identify the authorized targets, allowed scan modes, and attack surfaces from the threat model.
- Select tools per category (SAST, SCA, DAST, secrets, container/IaC).
- Integrate into CI with clear gate policies per stage.
- Establish a triage workflow: confirm, classify, assign, track.
- Define vulnerability SLAs as a starting policy, then tune them to exploitability, business impact, and compliance obligations.
- Add security regression tests for every confirmed vulnerability.
Inputs to Gather
- Application type: web app, API, mobile, CLI, infrastructure.
- Languages, frameworks, and build toolchain.
- Deployment model: containers, serverless, VMs, PaaS.
- Current security tooling and CI platform.
- Compliance requirements: SOC 2, PCI DSS, HIPAA, ISO 27001 if applicable.
- Existing vulnerability management process and acceptable risk thresholds.
- Code hosting platform: GitHub, GitLab, Bitbucket (affects native tool availability).
Security Testing Categories
1. SAST (Static Application Security Testing)
Analyze source code for vulnerabilities without executing it.
- Recommended tools: Semgrep (customizable rules), CodeQL (deep dataflow analysis, GitHub-native), Snyk Code.
- CI pattern: run on every PR; a common starter is block merge on high/critical findings, then tune to your risk policy.
- Key practices: maintain custom rules for your codebase patterns, manage suppressions with documented reasons, use baseline files to avoid noise from pre-existing findings.
- Reference: references/sast-integration.md
2. SCA / Dependency Scanning
What ships with it
21 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 365 B
- assets/template-security-gate-checklist.md 1.8 KB
- assets/template-security-test-plan.md 2.6 KB
- assets/template-vulnerability-sla.md 3.2 KB
- data/sample-scan-coverage.json 3.3 KB
- data/sample-vulnerabilities.json 5.9 KB
- data/sources.json 17 KB
- learnings.consolidated.md 595 B
- learnings.md 716 B
- references/container-iac-scanning.md 11 KB
- references/dast-automation.md 9.6 KB
- references/dependency-scanning.md 8.5 KB
- references/game-theory-applied.md 23 KB
- references/owasp-top-10-coverage.md 29 KB
- references/sast-integration.md 9.5 KB
- references/secret-scanning.md 11 KB
- references/security-regression-testing.md 8.7 KB
- references/supply-chain-security.md 5.2 KB
- scripts/README.md 6.1 KB
- scripts/test_vuln_tracker.py 12 KB runs code
- scripts/vuln_tracker.py 26 KB runs code
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.
- 12d ago Changed · -5 tokens per session 0eb77c7d22e1
- 19d ago Changed · -45 lines 9f1823fc036b
- 1mo ago Changed · -3 lines 02639cc1078d
- 1mo ago First seen · 273 lines · 38 tokens per session scan A b6ed587e675f
qa-security-testing is a skill published in the GitHub repository vasilyu1983/AI-Agents-public (101 stars, last pushed 9d ago), licensed MIT. It adds 33 tokens to every session and 3,595 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
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