Bingeable — agentic threat model
Bingeable acts as an automated agent that executes software workflows on-screen to generate video tutorials. Its primary risk lies in the potential for prompt injection to hijack the on-screen execution, leading to the generation of malicious or unauthorized video content.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.60 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.10 | |
| 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.
Not certain from the listing — likely relies on multimodal foundation models to interpret the user's text prompt, plan the UI workflow, and generate the voiceover narration. Vulnerable to prompt injection that could alter the generated video steps or narration.
Not certain from the listing — requires access to target software interfaces or mock environments to record workflows. If user-specific data or proprietary software interfaces are ingested, there is a risk of data leakage or exposure of sensitive UI elements in the rendered video.
The agent translates text prompts into a sequence of software actions (workflow execution) and narrates them. Insecure tool integration or weak validation of the generated workflow steps could allow an attacker to manipulate the agent into executing unintended UI actions during recording.
Not certain from the listing — the agent must run the target software workflow in a sandboxed browser or virtual desktop environment to capture the screen. If this execution environment is not properly isolated, it could be vulnerable to container escape or unauthorized network access.
Not certain from the listing — requires robust monitoring to ensure the automated UI actions align with the user's prompt and do not navigate to sensitive, inappropriate, or malicious external web pages during the automated recording process.
Not certain from the listing — there is no mention of enterprise security controls, access policies, or compliance certifications (e.g., SOC2) to govern how user credentials or target application sessions are managed during automated workflows.
Not certain from the listing — operates primarily as a standalone horizontal tool translating prompts to videos, with no explicit multi-agent or marketplace integrations described.
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.