Receipt Taxer — agentic threat model
Receipt Taxer is a low-risk, single-purpose utility agent focused on OCR and expense categorization. Its primary security risks are data privacy (exposure of financial receipts) and input-based attacks (CSV injection, malicious file uploads) rather than agentic autonomy or systemic propagation.
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 | 0.20 | |
| 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 commercial vision-language model or OCR-specialized LLM. Threats include prompt injection via malicious text embedded in receipts (e.g., instructions to alter tax categorization or exfiltrate data) and model hallucination in financial calculations.
Not certain from the listing — processes uploaded images and PDFs. Threats include insecure storage of sensitive financial documents, lack of data sanitization leading to injection attacks, and potential leakage of PII/financial data if user uploads are used for model fine-tuning.
Not certain from the listing — likely a simple deterministic pipeline rather than a complex agent framework. Threats include insecure parsing of LLM outputs (e.g., JSON parsing errors) and lack of input validation before exporting to CSV/Excel (leading to CSV injection).
Not certain from the listing — hosted as a SaaS. Threats include typical web application vulnerabilities (OWASP Top 10), insecure file upload handling (allowing remote code execution via malicious PDFs/images), and lack of sandboxing for document processing.
Not certain from the listing — no mention of monitoring or guardrails. Gaps in observability could allow silent failures in OCR extraction or categorization to go unnoticed by the user, leading to incorrect tax filings.
Not certain from the listing — claims 'Privacy First' by avoiding bank connections, but lacks explicit compliance certifications (e.g., SOC 2, GDPR). Threats include unauthorized access to user accounts containing sensitive tax documents due to weak authentication.
The agent operates as a standalone SaaS tool with no multi-agent or marketplace integrations described. Ecosystem risks are negligible as it does not interact with other agents or external APIs.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology. Are you the vendor? Factual corrections are free.