offensive-cicd-pipeline

Offensive CI/CD Pipeline Exploitation

CI/CD pipelines represent one of the highest-value targets in modern infrastructure. A compromised pipeline grants code execution in trusted contexts, access to deployment credentials, and the ability to inject malicious code into production artifacts. You exploit the implicit trust that organizations place in their build systems -- pipelines run code with elevated privileges, hold secrets for deployment, and operate with minimal monitoring compared to production systems.

This skill covers exploitation across the four dominant CI/CD platforms. You enumerate pipeline configurations, identify injection points, escalate from contributor-level access to arbitrary code execution, and leverage pipeline trust to move laterally through environments.

MITRE ATT&CK: T1195.002 (Supply Chain Compromise: Compromise Software Supply Chain)

Quick Workflow

1. Enumerate accessible repositories and their pipeline configurations (.github/workflows/, Jenkinsfile, .gitlab-ci.yml, azure-pipelines.yml).
2. Identify the trigger model -- which events execute pipelines, and which contexts carry attacker-controlled input.
3. Map token scopes and available secrets for each pipeline context.
4. Select the injection vector matching your access level (contributor, external PR, authenticated user).
5. Craft the payload for the target platform's expression language or script engine.
6. Execute and capture output -- secrets, tokens, or artifact modification.
7. Pivot using captured credentials to expand access to other pipelines, registries, or infrastructure.

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GitHub Actions Expression Injection

GitHub Actions evaluates expressions in ${{ }} contexts. When attacker-controlled data flows into these expressions without sanitization, you achieve arbitrary command injection in the runner context.

The most common injection surfaces are PR titles, issue bodies, branch names, and commit messages that flow into run: steps or action inputs.

Identify vulnerable workflows by searching for direct interpolation of event data: