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Reachfast.ai — agentic threat model

7.1AIVSS 7.1 · High

Reachfast.ai is a data-intensive contact lookup agent with low agentic autonomy but high data privacy risks due to its handling of a 385M+ professional contact database and user-uploaded CSVs.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 6.5AARS uplift 0.63Factor sum 1.8/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.40
Goal-Driven Planning
0.20
Self-Modification
0.00
Dynamic Tool Use
0.30
Persistent Memory
0.10
Contextual Awareness
0.20
Dynamic Identity
0.10
Multi-Agent Interactions
0.00
Non-Determinism
0.20
Opacity & Reflexivity
0.30

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 uses LLMs for parsing unstructured profile data or matching, but specific models are not disclosed. Threats include prompt injection via malicious LinkedIn profile data.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — relies on a massive database of 385M+ professionals. Threats include data poisoning of the contact database, unauthorized data exfiltration, and privacy/GDPR compliance issues regarding scraped PII.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — likely uses a simple orchestration framework to ingest CSVs, extract URLs, and trigger lookup tools. Threats include insecure CSV parsing (e.g., CSV injection) and insecure tool calling for database lookups.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — hosted web application. Threats include container compromise, exposure of database credentials, and lack of sandboxing during CSV processing.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — no details on logging or guardrails. Gaps could lead to undetected data scraping abuse or prompt injection attacks.

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

Not certain from the listing — handles massive amounts of PII (emails, phone numbers) which raises significant GDPR/CCPA compliance risks. No explicit security certifications (SOC2, etc.) are mentioned.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — operates as a standalone SaaS/open-source tool, with no active multi-agent ecosystem or marketplace interactions described.

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.