skills-skills
Warn
Audited by Gen Agent Trust Hub on Feb 27, 2026
Risk Level: MEDIUMREMOTE_CODE_EXECUTIONEXTERNAL_DOWNLOADSCOMMAND_EXECUTIONPROMPT_INJECTION
Full Analysis
- [REMOTE_CODE_EXECUTION]: The script
scripts/skill-seekers-update.shis designed to fetch a source code archive from an external, non-whitelisted GitHub repository (yusufkaraaslan/Skill_Seekers), extract it, and synchronize the files into the skill's local directory. This provides a mechanism for arbitrary remote code updates that could alter the tool's behavior after deployment. - [EXTERNAL_DOWNLOADS]: The skill performs automated network operations across several components: 1.
scripts/skill-seekers-bootstrap.shinstalls multiple Python dependencies from PyPI. 2.src/skill_seekers/cli/doc_scraper.pyandgithub_scraper.pyfetch documentation content and repository data from the internet. 3.scripts/skill-seekers-update.shperforms a direct download of a code archive from GitHub. - [COMMAND_EXECUTION]: The MCP server implementation in
src/skill_seekers/mcp/server.pyuses thesubprocessmodule to construct and execute system commands for scraping and packaging skills. These commands are built using parameters passed through the agent interface, representing a standard but high-privilege capability. - [PROMPT_INJECTION]: As a generative tool for AI agent instructions, this skill exhibits a high vulnerability to indirect prompt injection (Category 8). According to the evidence chain: 1. Ingestion points:
doc_scraper.py(web content),github_scraper.py(READMEs, issues), andpdf_scraper.py(PDF text). 2. Boundary markers: The generatedSKILL.mdfiles include source headers (seeunified_skill_builder.py), but these are insufficient to prevent adversarial instructions in the source material from being parsed as agent rules. 3. Capability inventory: The tool can write to the local file system and execute subprocesses (mcp/server.py). 4. Sanitization: There is an absence of robust logic to sanitize natural language or executable instructions from scraped sources, allowing malicious content in third-party documentation to potentially manipulate agents that later use the generated skills.
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