data-specialist

Fail

Audited by Gen Agent Trust Hub on Feb 17, 2026

Risk Level: CRITICALEXTERNAL_DOWNLOADSSAFE
Full Analysis
  • [EXTERNAL_DOWNLOADS] (LOW): The vLLM configuration guide (references/cursor_rules_vllm.md) recommends installing wheel packages directly from the 'vllm-project' GitHub organization. While this is common for specialized CUDA builds, the organization is not on the trusted list.
  • [COMMAND_EXECUTION] (SAFE): Several files discuss agents with code execution capabilities (e.g., autogen, smolagents). The instructions correctly identify and warn against unsafe practices like using eval() on untrusted input.
  • [DATA_EXFILTRATION] (SAFE): No exfiltration vectors were identified. External calls in examples are directed to legitimate telemetry endpoints (OpenLIT) or placeholders.
  • [CREDENTIALS_UNSAFE] (SAFE): The skill follows security best practices by instructing users to load API keys from environment variables instead of hardcoding them.
  • [INDIRECT_PROMPT_INJECTION] (LOW): The skill processes external data (customer support tickets, database query results) which creates a potential surface for indirect injection. This is mitigated by the skill's own strong recommendations for parameterized queries and strict boundary management.
Recommendations
  • Contains 1 malicious URL(s) - DO NOT USE
Audit Metadata
Risk Level
CRITICAL
Analyzed
Feb 17, 2026, 06:11 PM