AuthLetter — agentic threat model
AuthLetter is a low-risk, template-driven document generation assistant with minimal agentic autonomy. Its primary security risks center on the handling of sensitive PII (medical, financial, legal) and the potential for generating fraudulent authorization documents via prompt injection.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.20 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.30 | |
| Opacity & Reflexivity | 0.20 |
Scored with the canonical OWASP AIVSS formula (AIVSS calculator reference); agentic risk factors estimated from the agent’s described capabilities.
MAESTRO 7-layer threat model
Per-layer threats for this agent. Layers tagged “not certain from listing” are general, caveated commentary where the public description didn’t pin that layer.
Not certain from the listing — likely uses a standard commercial LLM for text generation. Threats include prompt injection to generate malicious or fraudulent authorization letters, or to bypass legal compliance guardrails.
Not certain from the listing — likely processes and temporarily stores highly sensitive user-inputted PII (financial, medical, and legal details) to populate templates. Threats include data exfiltration of sensitive authorization details and lack of secure data retention policies.
Not certain from the listing — likely structured as a simple template-filling wrapper around LLM APIs rather than a complex agent framework. Threats include insecure prompt construction leading to injection, though tool misuse risks are minimal.
Not certain from the listing — hosted web application. Threats include standard web application vulnerabilities (OWASP Top 10) and specific risks related to PDF generation libraries, such as Server-Side Request Forgery (SSRF) or local file inclusion during document compilation.
Not certain from the listing — no mention of real-time monitoring, LLM guardrails, or output validation. Threats include blind spots regarding the generation of fraudulent or legally non-compliant authorization letters.
Not certain from the listing — handles highly sensitive data (medical, financial, legal authorizations) but does not specify compliance with regulations like HIPAA, GDPR, or SOC2. Threats include regulatory non-compliance and unauthorized access to generated PDFs.
Not certain from the listing — operates as a standalone vertical tool with no multi-agent or marketplace integrations. Ecosystem threats are currently negligible.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).