Agentic Actions Auditor: Secure Your AI-Driven Workflows
Secure your CI/CD pipelines with 1 specialized skill.
Detect attack vectors in Claude Code and Gemini workflows. Start auditing today!
AI Security
GitHub Actions
Static Analysis
Agentic Workflows
CI/CD
About This Skill
Master the art of static security analysis with this specialized skill. Learn to audit complex GitHub Actions workflows, covering 4 critical areas of AI agent integration and vulnerability detection.
Quick Start
1Identify target GitHub Actions workflow files
2Trace AI action steps and cross-file references
3Analyze data flow from event context to AI prompts
Identify high-risk repositories where AI agents are invoked via Claude Code, Gemini, or OpenAI.
When NOT to Use
Avoid using this skill for non-AI workflows or standalone composite actions without a caller context.
Workflow Analysis
Follow cross-file references to composite actions and reusable workflows containing hidden agents.
Data Flow Tracking
Capture security-relevant configuration and detect attacker-controlled input reaching AI prompts.
Usage Examples
Input
A workflow using `pull_request_target` with an OpenAI Codex step.
Output
Detected high-risk attack vector: attacker-controlled PR input reaches AI prompt.
Input
A standard GitHub Actions workflow with no AI agents.
Output
No agentic actions detected; use general security tools instead.
Before
Workflow relies on opaque remote `uses:` syntax.
After
Audited configuration of tool permissions and user allowlists.
SKILL.md
---
name: agentic-actions-auditor
description: >
Audits GitHub Actions workflows for security
vulnerabilities in AI agent integrations
including Claude Code Action,
Gemini CLI, OpenAI Codex, and GitHub AI
Inference.
Detects attack vectors where attacker-controlled
input reaches.
AI agents running in CI/CD pipelines.
risk: safe
source: community
date_added: 2026-03-18
---
# Agentic Actions Auditor
Static security analysis guidance for GitHub Actions workflows that invoke AI coding agents. This skill teaches you how to discover workflow files locally or from remote GitHub repositories, identify AI action steps, follow cross-file references to composite actions and reusable workflows that may contain hidden AI agents, capture security-relevant configuration, and detect attack vectors where attacker-controlled input reaches an AI agent running in a CI/CD pipeline.
## When to Use
- Auditing a repository's GitHub Actions workflows for AI agent security
- Reviewing CI/CD configurations that invoke Claude Code Action, Gemini CLI, or OpenAI Codex
- Checking whether attacker-controlled input can reach AI agent prompts
- Evaluating agentic action configurations (sandbox settings, tool permissions, user allowlists)
- Assessing trigger events that expose workflows to external input (`pull_request_target`, `issue_comment`, etc.)
- Investigating data flow from GitHub event context through `env:` blocks to AI prompt fields
## When NOT to Use
- Analyzing workflows that do NOT use any AI agent actions (use general Actions security tools instead)
- Reviewing standalone composite actions or reusable workflows outside of a caller workflow context (use this skill when analyzing a workflow that references them via `uses:`)
- Performing runtime prompt injection testing (this is static analysis guidance, not exploitation)
- Auditing non-GitHub CI/CD systems (Jenkins, GitLab CI, CircleCI)
- Auto-fixing or modifying workflow files (this skill reports findings, does n
Frequently Asked Questions
FAQ
Is this compatible with all GitHub Actions?
It is specifically optimized for workflows that invoke AI coding agents like Claude Code or Gemini CLI.
Who is the target audience for this skill?
Developers, DevOps engineers, and Security researchers focusing on AI-integrated CI/CD pipelines.
How does this differ from standard GitHub security tools?
Unlike general tools, this focuses specifically on the 'agentic' attack surface where AI agents process input.
Does it support all programming languages?
Yes, as it performs static analysis on the YAML workflow configuration itself, regardless of the language used in steps.
What are the expected results after an audit?
A detailed report of potential attack vectors where external input reaches AI agent prompts or tool permissions.
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Trigger Phrases
Use these phrases to activate this skill in your AI coding assistant:
