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Caseflood.ai — agentic threat model

8.2AIVSS 8.2 · High

Caseflood.ai presents a moderate-to-high risk profile primarily due to the highly sensitive nature of legal intake data (PII, PHI, and privileged information) combined with a lack of explicit security or compliance disclosures in its public listing.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 7.5AARS uplift 0.68Factor sum 2.7/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.40
Goal-Driven Planning
0.30
Self-Modification
0.00
Dynamic Tool Use
0.30
Persistent Memory
0.20
Contextual Awareness
0.40
Dynamic Identity
0.10
Multi-Agent Interactions
0.10
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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — likely utilizes commercial LLMs to parse and respond to legal intake queries. Primary threats include prompt injection leading to the bypass of intake criteria or leakage of system instructions.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — processes highly sensitive prospective client data (PII, PHI, legal claims). Threats include unauthorized data exfiltration, lack of encryption at rest/in transit, and data leakage within vector databases if RAG is used.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — orchestrates conversational flows to qualify legal leads. Threats include insecure tool integration with external legal CRMs or scheduling tools, allowing malicious inputs to execute unauthorized API calls.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — likely hosted on cloud infrastructure to serve web-based intake widgets. Threats include container escape, insecure API endpoints, and lack of tenant isolation for sensitive legal records.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — requires robust guardrails to prevent the AI from providing unauthorized legal advice (UPL) or hallucinating intake qualifications. Lack of visible monitoring could lead to undetected drift.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — legal intake demands strict compliance with HIPAA, CCPA/GDPR, and attorney-client privilege standards. No compliance certifications (e.g., SOC 2) are detailed in the public listing.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — likely operates as a standalone intake agent but integrates with broader legal tech ecosystems (e.g., Clio, Filevine). Threats include API key exposure and cascading failures if downstream CRM APIs are compromised.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).