Fansloader — agentic threat model
Fansloader is a browser-based media downloader rather than an autonomous AI agent, presenting minimal agentic risk but high client-side security risks due to its execution environment and DRM-bypass capabilities.
OWASP AIVSS score rationale
| Autonomy of Action | 0.00 | |
| Goal-Driven Planning | 0.00 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.10 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.00 | |
| Opacity & Reflexivity | 0.10 |
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 — Fansloader appears to be a traditional programmatic browser extension for media scraping rather than an LLM-powered agent; there is no evidence of foundation model usage.
Not certain from the listing — The tool processes media streams and session cookies locally to download files, but there is no indication of vector databases, RAG, or training data operations.
Not certain from the listing — No agentic orchestration framework (like LangChain or AutoGPT) is mentioned. The 'tools' are hardcoded browser automation scripts for bulk downloading and DRM recording.
Runs as a local Chrome extension. The primary infrastructure threat is client-side extension compromise, which could allow malicious updates to exfiltrate sensitive OnlyFans session cookies or user credentials.
Not certain from the listing — As a closed-source, client-side browser extension, there is no public evidence of security logging, telemetry, or guardrails to prevent unauthorized distribution of downloaded media.
The tool operates in a high-risk compliance area, bypassing platform DRM and terms of service. There are no documented compliance frameworks, access controls, or audit logs.
Does not participate in any multi-agent ecosystem or marketplace; it operates strictly as a standalone browser utility.
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 — every score is re-derived by the same automated method as an agent's public evidence changes.