← Hugging Face Open Computer Agent
Hugging Face Open Computer Agent — agentic threat model
The Hugging Face Open Computer Agent presents a high-risk profile due to its ability to perform arbitrary GUI and web automation via vision-language models, though this is partially mitigated by its execution within sandboxed E2B virtual desktop environments.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.80 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.90 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.80 | |
| Opacity & Reflexivity | 0.70 |
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.
Powered by vision-language models like Qwen2-VL-72B. Primary threats include visual and textual prompt injection from untrusted web pages, which can hijack the model's reasoning and force malicious desktop actions.
Not certain from the listing — No explicit details on RAG or vector databases are provided, but the agent processes real-time visual and textual data from the active browser session, making it susceptible to indirect prompt injection via web content.
Uses the smolagents framework to orchestrate planning and tool execution. Threats include tool misuse, where the agent translates malicious instructions into harmful mouse clicks, keyboard inputs, or form submissions.
Deploys within an E2B Desktop virtual Linux environment. While this sandboxing mitigates host compromise, threats include sandbox escape, local privilege escalation within the VM, and lateral movement if the VM has network access to internal resources.
Not certain from the listing — No built-in evaluation, logging, or guardrail frameworks are detailed in the description, suggesting potential blind spots in monitoring agent actions in real-time.
Not certain from the listing — The agent is in an experimental phase with no mentioned identity management, access control policies, or compliance audits.
Not certain from the listing — No multi-agent orchestration or marketplace interactions are described, though it operates in a broader web ecosystem where it interacts with external sites.
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.