How does amaise protect against prompt injection attacks?
amaise uses multiple measures to prevent prompt injection attacks through malicious content in documents:
Server-side prompt construction: LLM prompts are created server-side using controlled templates. Users do not have direct access to prompt creation.
Separation of instructions and data: Document contents are passed as data context, clearly separated from system instructions.
Structured extraction: The pipeline performs schema-bound extraction tasks — no free text generation. This significantly limits the potential impact of injection attempts.
Input validation: Validation at the API level for all incoming requests.
Output validation: LLM outputs are validated and sanitized before storage and display.
No user-provided URLs: The application does not accept user-supplied URLs for server-side fetching, preventing data exfiltration via SSRF.
Tenant-isolated outputs: AI results are strictly isolated per tenant. Queries are restricted to the respective tenant context, so a prompt injection attempt in one document cannot access data from other tenants or cases.
