DigiParser — agentic threat model
DigiParser presents a moderate security risk primarily driven by its integration with downstream business tools and the processing of sensitive document data, though this is significantly mitigated by its built-in Human-in-the-Loop (HITL) review features.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.40 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.50 | |
| Opacity & Reflexivity | 0.40 |
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 utilizes third-party LLMs or proprietary OCR models for extraction. Key threats include indirect prompt injection via uploaded documents or emails designed to hijack the extraction schema or bypass parsing rules.
Not certain from the listing — processes incoming documents, emails, and extracted JSON data. Risks include data exfiltration of sensitive PII/financial data contained in documents, and potential data leakage if customer documents are used for model fine-tuning without consent.
Uses a no-code workflow builder to orchestrate document ingestion, schema-based extraction, and export. Vulnerabilities include insecure tool integration and logic flaws in the workflow builder that could allow unauthorized data routing.
Not certain from the listing — operates as a cloud-hosted SaaS with API access. Threats include insecure storage of uploaded documents, exposure of API keys used to connect to external business tools, and lack of sandboxing during document parsing.
Features 'Human-in-the-Loop Review' which serves as a critical manual evaluation gate. However, there may be blind spots in automated drift detection if OCR extraction accuracy degrades over time with new document formats.
Not certain from the listing — mentions team collaboration but lacks explicit details regarding Role-Based Access Control (RBAC), data encryption at rest/in transit, or compliance certifications (e.g., SOC2, GDPR) for handling sensitive documents.
Not certain from the listing — primarily interacts with standard business APIs rather than autonomous agent marketplaces. Risks are limited to cascading failures or unauthorized data injection into connected downstream applications.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).