llm-cost-optimization

Pass

Audited by Gen Agent Trust Hub on Mar 9, 2026

Risk Level: SAFEEXTERNAL_DOWNLOADSPROMPT_INJECTION
Full Analysis
  • [EXTERNAL_DOWNLOADS]: Fetches pre-trained models from trusted and well-known sources (Hugging Face and Microsoft) via the sentence-transformers and llmlingua libraries.\n- [PROMPT_INJECTION]: Identified an indirect prompt injection surface (Category 8) in code snippets that process external context to be sent to an LLM.\n
  • Ingestion points: Reads from local context files (e.g., large-context.txt) and accepts user-provided strings for caching and compression.\n
  • Boundary markers: None are explicitly implemented in the simplified code examples.\n
  • Capability inventory: Functionality is restricted to file system reading and making requests to LLM provider APIs (OpenAI, Anthropic).\n
  • Sanitization: No data sanitization is performed in the examples as they focus on cost metrics and routing logic.
Audit Metadata
Risk Level
SAFE
Analyzed
Mar 9, 2026, 11:44 PM