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Garnit — agentic threat model

9.1AIVSS 9.1 · Critical

Garnit poses a high security risk due to its direct integration with user email inboxes, making it highly susceptible to indirect prompt injection attacks via malicious promotional emails that could abuse its email-writing and subscription capabilities.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.3AARS uplift 0.79Factor sum 4.4/10Threat ×1.05Mitigation ×1.0
Autonomy of Action
0.70
Goal-Driven Planning
0.40
Self-Modification
0.10
Dynamic Tool Use
0.60
Persistent Memory
0.50
Contextual Awareness
0.60
Dynamic Identity
0.40
Multi-Agent Interactions
0.10
Non-Determinism
0.50
Opacity & Reflexivity
0.50

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 a standard LLM for extraction and classification. The primary threat is indirect prompt injection, where malicious instructions embedded in promotional emails hijack the model's behavior.

L2 · Data Operations✓ mapped

Processes highly sensitive user inbox data. Threats include data exfiltration of personal email content and data poisoning via malicious promotional emails designed to corrupt the extraction pipeline.

L3 · Agent Frameworks✓ mapped

Orchestrates email parsing, saving deals, and executing actions like unsubscribe/subscribe. Vulnerabilities include tool misuse, where the agent could be tricked into unsubscribing the user from critical services or subscribing them to malicious spam lists.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — likely hosted on cloud infrastructure requiring OAuth access to the user's email provider. Threats include the compromise of OAuth tokens, allowing unauthorized access to the user's entire inbox.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — there is no mention of evaluation, monitoring, or guardrails to detect and filter out malicious email payloads before they are processed by the LLM.

L6 · Security & Compliance (cross-cutting)✓ mapped

Requires high-privilege read/write access to user email accounts. No security certifications (e.g., SOC2) or explicit privacy-preserving controls are mentioned in this free, closed-source vertical agent.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — does not explicitly mention multi-agent interactions, though it interacts with external brand subscription systems which could be abused to trigger cascading spam or phishing campaigns.

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.