fintech-web-systems
Pass
Audited by Gen Agent Trust Hub on Sep 4, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTION
Full Analysis
- [SAFE]: The skill demonstrates secure coding practices for financial data, specifically using the decimal.js library to prevent floating-point precision errors that are critical in trading systems.\n- [SAFE]: The OHLCV data ingestion pipeline implements robust protection against SQL injection by using parameterized queries with Cloudflare D1's .prepare().bind() method.\n- [SAFE]: Credential management is handled appropriately via environment variables (env.DATA_PROVIDER_KEY), avoiding the storage of hardcoded secrets or sensitive API keys within the skill instructions.\n- [SAFE]: The WebSocket implementation for real-time market data uses secure session identifiers (UUIDs) and follows standard patterns for data distribution without exposing the underlying infrastructure to unauthorized access.\n- [INDIRECT_PROMPT_INJECTION]: The skill has a low attack surface for indirect prompt injection. Ingestion occurs in fetchAndStoreOHLCV (SKILL.md) which reads external API data. Boundary markers are inherently present as data is used for structured database storage rather than prompt interpolation. Capability inventory includes network fetching and database writes. Sanitization is effectively performed using SQL parameter binding.
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