sglang

Pass

Audited by Gen Agent Trust Hub on Sep 9, 2026

Risk Level: SAFEINDIRECT_PROMPT_INJECTIONEXTERNAL_DOWNLOADS
Full Analysis
  • [INDIRECT_PROMPT_INJECTION]: The skill processes untrusted user queries and articles to drive structured generation and agent workflows.
  • Ingestion points: External data enters the agent context through the user_query, article, and text parameters in the SGLang function examples found in SKILL.md and references/structured-generation.md.
  • Boundary markers: The prompt templates use natural language labels (e.g., User:, Assistant:, Article:) but do not include explicit security instructions or delimiters to prevent embedded instruction overrides.
  • Capability inventory: The skill's logic is constrained to LLM inference and structured output via the SGLang library; no dangerous capabilities like arbitrary filesystem writes or unauthorized network requests are exposed.
  • Sanitization: External content is interpolated directly into prompts without specific filtering or escaping mechanisms.
  • [EXTERNAL_DOWNLOADS]: The documentation provides instructions to install dependencies from the official SGLang GitHub repository and the FlashInfer project's specialized wheel registry.
Audit Metadata
Risk Level
SAFE
Analyzed
Sep 9, 2026, 07:07 PM
Security Audit — agent-trust-hub — sglang