github-actions-script-injection
Fail
Audited by Gen Agent Trust Hub on Sep 22, 2026
Risk Level: HIGHCREDENTIALS_UNSAFEREMOTE_CODE_EXECUTIONCOMMAND_EXECUTIONDATA_EXFILTRATIONOBFUSCATIONINDIRECT_PROMPT_INJECTIONDYNAMIC_EXECUTIONPRIVILEGE_ESCALATION
Full Analysis
- [REMOTE_CODE_EXECUTION]: The skill provides specific exploit payloads that utilize
curl | bashpatterns to execute remote scripts directly from a URL. - [DATA_EXFILTRATION]: Instructions are provided for exfiltrating the contents of sensitive files (e.g.,
/proc/self/environ) to an external callback server usingcurl. - [CREDENTIALS_UNSAFE]: The skill references accessing
/proc/self/environto harvest environment variables, which often contain sensitive credentials likeGITHUB_TOKENor cloud access keys in CI/CD environments. - [COMMAND_EXECUTION]: Recommends the use of external tools like
lucky-commitfor SHA collisions and subshell execution ($()) to perform unauthorized command execution. - [OBFUSCATION]: Documents various techniques to bypass security filters, including hex-encoded command strings (e.g.,
$'curl'forcurl) and substituting spaces with${IFS}. - [INDIRECT_PROMPT_INJECTION]: Identifies a significant attack surface where untrusted data from GitHub contexts (branch names, PR bodies) is interpolated into shell steps.
- Ingestion points: Target GitHub Actions workflow files (
.github/workflows/) that consume context expressions likegithub.head_ref. - Boundary markers: Vulnerable code snippets lack delimiters; fix patterns use environment variable indirection as a secure boundary.
- Capability inventory: Shell
run:steps in GitHub Actions workflows that allow for arbitrary command execution. - Sanitization: Vulnerable patterns lack sanitization; the skill recommends environment variable indirection and network runtime monitoring as fixes.
- [DYNAMIC_EXECUTION]: Centers on exploiting the dynamic generation of shell scripts in CI/CD pipelines through unsanitized string interpolation of external inputs.
- [PRIVILEGE_ESCALATION]: Details how to escalate from low-privilege contexts to full repository compromise using
pull_request_targettriggers and cache poisoning techniques.
Recommendations
- AI detected serious security threats
Audit Metadata