Gha Security Review logo

Gha Security Review

OrganizationPopular
getsentry
gha-security-review

GitHub Actions security review for workflow exploitation vulnerabilities. Use when asked to "review GitHub Actions", "audit workflows", "check CI security", "GHA security", "workflow security review", or review .github/workflows/ for pwn requests, expression injection, credential theft, and supply chain attacks. Exploitation-focused with concrete PoC scenarios.

Overview

Publishergetsentry
Repositoryskills
Skill namegha-security-review
Stars
1K
Forks
53
Bundled files
9
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 9 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by getsentry on GitHub. Read the source before you install it.

Installation

Install the Gha Security Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/getsentry/skills/tree/main/skills/gha-security-review
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/getsentry/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/gha-security-review .claude/skills/gha-security-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gha Security Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Gha Security Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Gha Security Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

GitHub Actions Security Review

Find exploitable vulnerabilities in GitHub Actions workflows. Every finding MUST include a concrete exploitation scenario — if you can't build the attack, don't report it.

This skill encodes attack patterns from real GitHub Actions exploits — not generic CI/CD theory.

Scope

Review the workflows provided (file, diff, or repo). Research the codebase as needed to trace complete attack paths before reporting.

Files to Review

  • .github/workflows/*.yml — all workflow definitions
  • action.yml / action.yaml — composite actions in the repo
  • .github/actions/*/action.yml — local reusable actions
  • Config files loaded by workflows: CLAUDE.md, AGENTS.md, Makefile, shell scripts under .github/

Out of Scope

  • Workflows in other repositories (only note the dependency)
  • GitHub App installation permissions (note if relevant)

Threat Model

Only report vulnerabilities exploitable by an external attacker — someone without write access to the repository. The attacker can open PRs from forks, create issues, and post comments. They cannot push to branches, trigger workflow_dispatch, or trigger manual workflows.

Do not flag vulnerabilities that require write access to exploit:

  • workflow_dispatch input injection — requires write access to trigger
  • Expression injection in push-only workflows on protected branches
  • workflow_call input injection where all callers are internal
  • Secrets in workflow_dispatch/schedule-only workflows

Confidence

Report only HIGH and MEDIUM confidence findings. Do not report theoretical issues.

ConfidenceCriteriaAction
HIGHTraced the full attack path, confirmed exploitableReport with exploitation scenario and fix
MEDIUMAttack path partially confirmed, uncertain linkReport as needs verification
LOWTheoretical or mitigated elsewhereDo not report

For each HIGH finding, provide all five elements:

  1. Entry point — How does the attacker get in? (fork PR, issue comment, branch name, etc.)
  2. Payload — What does the attacker send? (actual code/YAML/input)
  3. Execution mechanism — How does the payload run? (expression expansion, checkout + script, etc.)
  4. Impact — What does the attacker gain? (token theft, code execution, repo write access)
  5. PoC sketch — Concrete steps an attacker would follow

If you cannot construct all five, report as MEDIUM (needs verification).


Step 1: Classify Triggers and Load References

For each workflow, identify triggers and load the appropriate reference:

Trigger / PatternLoad Reference
pull_request_targetreferences/pwn-request.md
issue_comment with command parsingreferences/comment-triggered-commands.md
${{ }} in run: blocksreferences/expression-injection.md
PATs / deploy keys / elevated credentialsreferences/credential-escalation.md
Checkout PR code + config file loadingreferences/ai-prompt-injection-via-ci.md
Third-party actions (especially unpinned)references/supply-chain.md
permissions: block or secrets usagereferences/permissions-and-secrets.md
Self-hosted runners, cache/artifact usagereferences/runner-infrastructure.md
Any confirmed findingreferences/real-world-attacks.md

Load references selectively — only what's relevant to the triggers found.

Step 2: Check for Vulnerability Classes

Check 1: Pwn Request

Does the workflow use pull_request_target AND check out fork code?

  • Look for actions/checkout with ref: pointing to PR head
  • Look for local actions (./.github/actions/) that would come from the fork
  • Check if any run: step executes code from the checked-out PR

Check 2: Expression Injection

Are ${{ }} expressions used inside run: blocks in externally-triggerable workflows?

  • Map every ${{ }} expression in every run: step
  • Confirm the value is attacker-controlled (PR title, branch name, comment body — not numeric IDs, SHAs, or repository names)
  • Confirm the expression is in a run: block, not if:, with:, or job-level env:

Check 3: Unauthorized Command Execution

Does an issue_comment-triggered workflow execute commands without authorization?

  • Is there an author_association check?
  • Can any GitHub user trigger the command?
  • Does the command handler also use injectable expressions?

Check 4: Credential Escalation

Are elevated credentials (PATs, deploy keys) accessible to untrusted code?

  • What's the blast radius of each secret?
  • Could a compromised workflow steal long-lived tokens?

Check 5: Config File Poisoning

Does the workflow load configuration from PR-supplied files?

  • AI agent instructions: CLAUDE.md, AGENTS.md, .cursorrules
  • Build configuration: Makefile, shell scripts

Check 6: Supply Chain

Are third-party actions securely pinned to full SHAs?

  • Pin third-party / external actions and reusable workflows only
  • Do not flag first-party actions/* or github/* on version tags
  • Do not flag same-repo / vendored (./.github/actions/...) as supply-chain pinning issues
  • Only report when the job has secrets, OIDC, write token, release, deploy, package, or signing power — unprivileged read-only CI is not a finding

Check 7: Permissions and Secrets

Are workflow permissions minimal? Are secrets properly scoped?

Check 8: Runner Infrastructure

Are self-hosted runners, caches, or artifacts used securely?

Safe Patterns (Do Not Flag)

Before reporting, check if the pattern is actually safe:

PatternWhy Safe
pull_request_target WITHOUT checkout of fork codeNever executes attacker code
${{ github.event.pull_request.number }} in run:Numeric only — not injectable
${{ github.repository }} / github.repository_ownerRepo owner controls this
${{ secrets.* }}Not an expression injection vector
${{ }} in if: conditionsEvaluated by Actions runtime, not shell
${{ }} in with: inputsPassed as string parameters, not shell-evaluated
Third-party actions pinned to full SHAImmutable reference
First-party actions/* / github/* on version tagsOutside third-party pinning policy — do not flag
Same-repo / vendored local actionsNot third-party supply chain (review pwn-request separately)
pull_request trigger (not _target)Runs in fork context with read-only token
Any expression in workflow_dispatch/schedule/push to protected branchesRequires write access — outside threat model

Key distinction: ${{ }} is dangerous in run: blocks (shell expansion) but safe in if:, with:, and env: at the job/step level (Actions runtime evaluation).

Step 3: Validate Before Reporting

Before including any finding, read the actual workflow YAML and trace the complete attack path:

  1. Read the full workflow — don't rely on grep output alone
  2. Trace the trigger — confirm the event and check if: conditions that gate execution
  3. Trace the expression/checkout — confirm it's in a run: block or actually references fork code
  4. Confirm attacker control — verify the value maps to something an external attacker sets
  5. Check existing mitigations — env var wrapping, author_association checks, restricted permissions, SHA pinning

If any link is broken, mark MEDIUM (needs verification) or drop the finding.

If no checks produced a finding, report zero findings. Do not invent issues.

Step 4: Report Findings

markdown
## GitHub Actions Security Review

### Findings

#### [GHA-001] [Title] (Severity: Critical/High/Medium)
- **Workflow**: `.github/workflows/release.yml:15`
- **Trigger**: `pull_request_target`
- **Confidence**: HIGH — confirmed through attack path tracing
- **Exploitation Scenario**:
  1. [Step-by-step attack]
- **Impact**: [What attacker gains]
- **Fix**: [Code that fixes the issue]

### Needs Verification
[MEDIUM confidence items with explanation of what to verify]

### Reviewed and Cleared
[Workflows reviewed and confirmed safe]

If no findings: "No exploitable vulnerabilities identified. All workflows reviewed and cleared."

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Gha Security Review AI skill do?

GitHub Actions security review for workflow exploitation vulnerabilities. Use when asked to "review GitHub Actions", "audit workflows", "check CI security", "GHA security", "workflow security review", or review .github/workflows/ for pwn requests, expression injection, credential theft, and supply chain attacks. Exploitation-focused with concrete PoC scenarios.

Why use Gha Security Review on TypingMind?

Because you install it once and use it with any model. Gha Security Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Gha Security Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/getsentry/skills/tree/main/skills/gha-security-review. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Gha Security Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Gha Security Review?

As many as you like. As long as a model supports skills, you can use Gha Security Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Gha Security Review AI skill free?

Yes. It is published on GitHub by getsentry under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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