OneTask — agentic threat model
OneTask is a personal productivity agent with moderate risk, primarily centered around the confidentiality of highly sensitive personal schedules and task data, with potential integrity risks if malicious prompt injections manipulate user priorities.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.40 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.30 | |
| Persistent Memory | 0.70 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.40 | |
| 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.
Not certain from the listing — likely relies on external LLMs (e.g., OpenAI) to parse and prioritize tasks. Primary threats include prompt injection that could manipulate task urgency or leak sensitive task descriptions via system prompt extraction.
Not certain from the listing — requires a persistent database or vector store to manage user tasks, schedules, and historical preferences. Risks include unauthorized data exfiltration of highly personal daily routines and ADHD-related coping notes.
Not certain from the listing — orchestrates task management and prioritization logic. Insecure tool integration is a key threat if the framework connects to external calendar APIs (Google Calendar, Outlook) without strict write-permission scoping.
Not certain from the listing — being open-source, it may be self-hosted or cloud-hosted. Threats include insecure default configurations, exposed API keys for LLM providers, and lack of sandboxing for local execution environments.
Not certain from the listing — no public details on guardrails or logging mechanisms. Gaps in observability could allow silent failures in task prioritization or undetected prompt injection attacks.
Not certain from the listing — requires robust OAuth and session management to protect user accounts. Compliance with privacy regulations (GDPR/CCPA) is critical given the highly personal nature of ADHD productivity tracking.
Not certain from the listing — does not explicitly feature multi-agent collaboration or marketplace integrations, limiting ecosystem-level cascading failure risks.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).