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Aphra — agentic threat model

8.5AIVSS 8.5 · High

Aphra is an open-source personal assistant with access to sensitive user capabilities like email, reminders, and web browsing, presenting a moderate-to-high risk profile due to potential tool misuse and data exfiltration without documented security guardrails.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 7.5AARS uplift 1.0Factor sum 4.0/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.50
Goal-Driven Planning
0.40
Self-Modification
0.10
Dynamic Tool Use
0.50
Persistent Memory
0.50
Contextual Awareness
0.50
Dynamic Identity
0.30
Multi-Agent Interactions
0.10
Non-Determinism
0.60
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 — The specific foundation models powering Aphra's 100+ voices and 70 avatars are not disclosed, leaving it vulnerable to standard LLM risks like prompt injection or adversarial reprogramming.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — It is unclear how Aphra stores personal data, emails, or reminders, raising concerns about data poisoning or unauthorized exfiltration of sensitive user context.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — The orchestration framework for handling tools like email, reminders, and web browsing is unspecified, presenting risks of insecure tool calling or memory poisoning.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — While noted as open source, the deployment architecture (local vs. cloud-hosted) is not detailed, impacting the risk of container compromise or credential exposure.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — No built-in guardrails, evaluation metrics, or logging mechanisms are mentioned to detect drift or malicious prompt injections during daily tasks.

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

Not certain from the listing — Compliance with privacy regulations (like GDPR for personal emails/reminders) and identity/authorization controls for accessing third-party APIs are not specified.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — There is no indication of multi-agent interaction or integration with an external agent marketplace, limiting ecosystem-level cascading risks.

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