Anonymize360 — agentic threat model
Anonymize360 is a local privacy-preserving proxy with low agentic autonomy but high data sensitivity. Its primary risk lies in the local storage of encryption keys and token mappings, where a compromise would expose all intercepted PII.
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 | 0.30 | |
| 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.
Not certain from the listing — the agent acts as an interceptor and may use a local model for PII detection. If so, threats include adversarial prompt injection designed to bypass PII detection filters.
The agent intercepts, tokenizes, and encrypts PII locally using AES-256. Threats include insecure local storage of token mappings, key extraction from memory, and potential leakage of the local database.
Not certain from the listing — the tool functions as a deterministic proxy rather than a complex agent framework. Threats are limited to vulnerabilities in the interception and tokenization logic.
Deployed locally on Windows and macOS. Threats include local privilege escalation, process tampering, and unauthorized local access to the application's memory space where unencrypted PII resides.
Not certain from the listing — no observability or logging features are detailed. If local logs are generated, they present a risk of accidental PII leakage if tokenization errors occur.
Designed for compliance (HIPAA, GDPR) via zero-knowledge local encryption. Threats include compliance violations if the PII detection engine suffers from false negatives, allowing sensitive data to leak to cloud LLMs.
Not certain from the listing — there is no mention of multi-agent coordination or ecosystem integrations. It operates strictly as a standalone local proxy.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).