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.md that use the trust_remote_code=True parameter 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.md and references/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, and pydantic through standard package managers.
Audit Metadata
Risk Level
SAFE
Analyzed
Sep 16, 2026, 05:50 AM