skills/bmad-code-org/bmad-method-test-architecture-enterprise/bmad-testarch-automate/Gen Agent Trust Hub
bmad-testarch-automate
Warn
Audited by Gen Agent Trust Hub on Oct 14, 2026
Risk Level: MEDIUMCOMMAND_EXECUTIONDYNAMIC_EXECUTIONINDIRECT_PROMPT_INJECTIONEXTERNAL_DOWNLOADS
Full Analysis
- [COMMAND_EXECUTION]: The skill is instructed to execute shell commands via
uv runon scripts located in the project's local_bmad/scripts/directory (e.g.,resolve_customization.pyandresolve_config.py). This creates a risk of arbitrary code execution if a malicious script is placed in that directory within an untrusted repository. - [DYNAMIC_EXECUTION]: The skill's 'run-and-heal' functionality automatically executes generated test code using
npx playwright testand modifies source files to fix failures. Executing and modifying code at runtime based on AI-generated content is a significant security boundary that could be exploited. - [INDIRECT_PROMPT_INJECTION]: The skill processes potentially untrusted external data, including story markdown files, technical specifications, and project source code, to drive test generation. This ingestion of unverified content combined with file-writing and command-execution permissions creates an attack surface for indirect prompt injection. Ingestion points: Loads user stories (
{story_file}), product requirements documents (PRDs), and technical specifications. Boundary markers: No explicit delimiters or safety instructions are used to isolate the ingested content when it is passed to subagents. Capability inventory: File system access (write_file,create_directory), repository search, and shell command execution (uv run,npx). Sanitization: The skill does not perform explicit validation or sanitization of the content extracted from story files before incorporating it into the test generation context. - [EXTERNAL_DOWNLOADS]: The skill fetches additional components and sibling skills using
npx skills addfrom the vendor's repository (bmad-code-org/bmad-method-test-architecture-enterprise).
Audit Metadata