raisindb-functions-triggers
Pass
Audited by Gen Agent Trust Hub on Apr 3, 2026
Risk Level: SAFEPROMPT_INJECTIONCOMMAND_EXECUTIONDATA_EXFILTRATIONREMOTE_CODE_EXECUTION
Full Analysis
- [PROMPT_INJECTION]: The skill describes a pattern for processing database content using AI models, which introduces an indirect prompt injection surface.
- Ingestion points: Data is retrieved from the database using
raisin.nodes.getas shown in theindex.jsexamples. - Boundary markers: The provided examples do not demonstrate the use of delimiters or instructions to ignore embedded commands in the processed data.
- Capability inventory: The runtime environment has extensive capabilities including database operations (
raisin.sql), network requests (raisin.http), and AI completions (raisin.ai). - Sanitization: No sanitization or validation logic is present in the examples to filter external content before it is interpolated into AI prompts.
- [COMMAND_EXECUTION]: Instructions include the use of
npm installfor obtaining type definitions andnpm run validatefor project configuration checks during development. - [DATA_EXFILTRATION]: Documents the intended use of network APIs (
fetch,raisin.http) and database query tools (raisin.sql) for implementing server-side logic and data persistence. - [REMOTE_CODE_EXECUTION]: Outlines a sandboxed JavaScript runtime environment that explicitly prevents the use of Node.js globals (e.g.,
Buffer), filesystem access (fs), and arbitrary npm module imports to mitigate unauthorized code execution.
Audit Metadata