continuous-ai-patterns
Pass
Audited by Gen Agent Trust Hub on Oct 9, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONCOMMAND_EXECUTION
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill instructions define patterns for ingesting and processing untrusted data from external sources such as GitHub issues, pull request comments, and repository code. This creates a surface where malicious instructions embedded in that data could influence the agent's behavior.\n
- Ingestion points: SKILL.md (Examples 2, 4, 5, and 6).\n
- Boundary markers: The skill does not explicitly define delimiters or instructions to ignore embedded commands within the processed data.\n
- Capability inventory: The examples suggest usage of powerful tools including
githubfor API interactions,bashfor command execution, andplaywrightfor browser automation.\n - Sanitization: There are no explicit instructions for sanitizing or escaping external content before processing.\n- [COMMAND_EXECUTION]: The skill provides examples that utilize local shell execution and browser automation to perform repository maintenance and reporting.\n
- Evidence: Example 3 and 7 utilize the
bashtool to run test suites, linters, and dependency checkers. Example 8 utilizesplaywrightto generate visual dashboards.\n - Context: These operations are consistent with the skill's primary purpose of continuous AI-assisted software collaboration.
Audit Metadata