outlines
Pass
Audited by Gen Agent Trust Hub on Sep 16, 2026
Risk Level: SAFEREMOTE_CODE_EXECUTIONDYNAMIC_EXECUTIONINDIRECT_PROMPT_INJECTIONEXTERNAL_DOWNLOADS
Full Analysis
- [REMOTE_CODE_EXECUTION]: The documentation includes examples in
references/backends.mdthat use thetrust_remote_code=Trueparameter when loading models via vLLM. This is a standard but security-sensitive feature of the Hugging Face and vLLM ecosystems that allows the execution of custom modeling code provided by a model repository. - [DYNAMIC_EXECUTION]: Several files, including
SKILL.mdandreferences/examples.md, provide examples for generating Python functions, SQL queries, and API specifications. While the skill does not execute this generated code itself, users should apply strict validation before executing any LLM-produced code in their own environments. - [INDIRECT_PROMPT_INJECTION]: The skill describes patterns for extracting data from untrusted external sources such as emails, resumes, and news articles (e.g., in
references/examples.md). These ingestion points represent an attack surface where embedded instructions in the source text could attempt to influence the structured output, although Pydantic validation provides a layer of schema-level filtering. - [EXTERNAL_DOWNLOADS]: The skill references and provides installation instructions for well-known, legitimate machine learning libraries such as
outlines,transformers,vllm, andpydanticthrough standard package managers.
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