signals-scout-anomaly-detection
Pass
Audited by Gen Agent Trust Hub on Sep 10, 2026
Risk Level: SAFEDYNAMIC_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [DYNAMIC_EXECUTION]: The skill utilizes
Bashandpython3to execute statistical routines, specifically the bundledscripts/ks2.pyscript and inline Python heredocs. These components perform Kolmogorov-Smirnov tests and changepoint detection on data retrieved from the environment. This execution is confined to the agent's local sandbox and is a primary functional requirement for anomaly detection.\n- [INDIRECT_PROMPT_INJECTION]: The skill ingests untrusted data from external sources such as PostHog events, insight names, and dashboard descriptions. This ingestion of external content serves as a potential vector for indirect prompt injection. \n - Ingestion points: Data enters via
scout-project-profile-get,dashboard-get,insight-query, andexecute-sqlas specified inSKILL.md.\n - Boundary markers: The instructions do not define explicit prompt delimiters for text data, but emphasize quantitative analysis which mitigates typical linguistic injection.\n
- Capability inventory: The skill can emit reports, create notebooks, and execute SQL/Bash commands.\n
- Sanitization: No specific text sanitization or filtering logic is documented for the data processed by the LLM.
Audit Metadata