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 adriannoes/awesome-agentic-ai --skill integrating-sast-into-github-actions-pipelinegit clone --depth 1 https://github.com/adriannoes/awesome-agentic-aiWrote 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/adriannoes/awesome-agentic-ai/integrating-sast-into-github-actions-pipeline)<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/integrating-sast-into-github-actions-pipeline"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/integrating-sast-into-github-actions-pipeline/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/adriannoes/awesome-agentic-ai/integrating-sast-into-github-actions-pipeline"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/integrating-sast-into-github-actions-pipeline.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 | $0.00084 | $0.02807 |
| Opus 5 | $0.00042 | $0.01404 |
| Sonnet 5 | $0.00017 | $0.00561 |
| Haiku 4.5 | $0.00008 | $0.00281 |
Grade A, and why
integrating-sast-into-github-actions-pipeline scanned grade A 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 8d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run(cmd_list, capture_output=True, text=True, shell=False) How it starts
The opening of the file, as written. The whole thing — 335 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Integrating SAST into GitHub Actions Pipeline
When to Use
- When development teams need automated code-level vulnerability detection on every pull request
- When security teams require consistent SAST enforcement across all repositories in an organization
- When migrating from manual or periodic security reviews to continuous security testing
- When compliance frameworks (SOC 2, PCI DSS, NIST SSDF) require evidence of automated code analysis
- When multiple languages coexist in a monorepo and need unified scanning under one workflow
Do not use for runtime vulnerability detection (use DAST instead), for scanning third-party dependencies (use SCA tools like Snyk), or for infrastructure-as-code scanning (use Checkov or tfsec).
Prerequisites
- GitHub repository with GitHub Actions enabled
- GitHub Advanced Security license (required for CodeQL on private repos; free for public repos)
- Semgrep account for managed rules and Semgrep App dashboard (free tier available)
- Repository code in a supported language: Python, JavaScript/TypeScript, Java, C/C++, C#, Go, Ruby, Swift, Kotlin
Workflow
Step 1: Configure CodeQL Analysis Workflow
Create a CodeQL workflow that runs on pull requests and on a weekly schedule to catch vulnerabilities in existing code.
# .github/workflows/codeql-analysis.yml
name: "CodeQL Analysis"
on:
push:
branches: [main, develop]
pull_request:
branches: [main]
schedule:
- cron: '30 2 * * 1' # Weekly Monday 2:30 AM
jobs:
analyze:
name: Analyze (${{ matrix.language }})
runs-on: ubuntu-latest
permissions:
actions: read
contents: read
security-events: write
strategy:
fail-fast: false
matrix:
language: ['javascript', 'python']
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Initialize CodeQL
uses: github/codeql-action/init@v3
with:
languages: ${{ matrix.language }}
queries: security-extended,security-and-quality
- name: Autobuild
uses: github/codeql-action/autobuild@v3
- name: Perform CodeQL Analysis
uses: github/codeql-action/analyze@v3
with:
category: "/language:${{ matrix.language }}"
What ships with it
7 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.
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.
- 8d ago First seen · 335 lines · 84 tokens per session scan A 5767c9ddf1fe
integrating-sast-into-github-actions-pipeline is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 14d ago), licensed MIT. It adds 84 tokens to every session and 2,807 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
integrating-sast-into-github-actions-pipeline
This skill covers integrating Static Application Security Testing (SAST) tools—CodeQL and Semgrep—into GitHub Actions CI/CD pipelines. It addresses configuring automated code scanning on pull requests and pushes, tuning rules to reduce false positives, uploading SARIF results to GitHub Advanced Security, and…
integrating-sast-into-github-actions-pipeline
This skill covers integrating Static Application Security Testing (SAST) tools—CodeQL and Semgrep—into GitHub Actions CI/CD pipelines. It addresses configuring automated code scanning on pull requests and pushes, tuning rules to reduce false positives, uploading SARIF results to GitHub Advanced Security, and…
implementing-devsecops-security-scanning
Integrates Static Application Security Testing (SAST), Dynamic Application Security Testing (DAST), and Software Composition Analysis (SCA) into CI/CD pipelines using open-source tools. Covers Semgrep for SAST, Trivy for SCA and container scanning, OWASP ZAP for DAST, and Gitleaks for secrets detection. Activates for…
scanning-containers-with-trivy-in-cicd
This skill covers integrating Aqua Security's Trivy scanner into CI/CD pipelines for comprehensive container image vulnerability detection. It addresses scanning Docker images for OS package and application dependency CVEs, detecting misconfigurations in Dockerfiles, scanning filesystem and git repositories, and…
implementing-infrastructure-as-code-security-scanning
This skill covers implementing automated security scanning for Infrastructure as Code (IaC) templates using tools like Checkov, tfsec, and KICS. It addresses detecting misconfigurations in Terraform, CloudFormation, Kubernetes manifests, and Helm charts before deployment, establishing policy-based governance, and…
implementing-semgrep-for-custom-sast-rules
Write custom Semgrep SAST rules in YAML to detect application-specific vulnerabilities, enforce coding standards, and integrate into CI/CD pipelines.