ScriptMind — agentic threat model
ScriptMind presents a low-to-moderate agentic risk profile, primarily acting as a reactive utility for video transcription and summarization. The main security vectors involve indirect prompt injection via untrusted video transcripts and potential Server-Side Request Forgery (SSRF) through its multi-platform video parsing capabilities.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.30 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.30 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.40 | |
| Opacity & Reflexivity | 0.30 |
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 utilizes third-party LLMs for translation, summarization, and interactive chat. Risks include indirect prompt injection via malicious video transcripts and misaligned outputs during content reshaping.
Not certain from the listing — processes video metadata, transcripts, and user-submitted URLs. Risks include data leakage if users process sensitive/private videos, and lack of data lineage controls for parsed content.
Not certain from the listing — orchestrates transcription, translation, and chat. Risks include insecure tool integration with video-fetching APIs, potentially allowing command injection or parameter tampering via malformed URLs.
Not certain from the listing — requires backend infrastructure to fetch and process videos from YouTube, TikTok, and Instagram. Risks include Server-Side Request Forgery (SSRF) when parsing user-supplied video links, and resource exhaustion.
Not certain from the listing — no mention of monitoring, logging, or guardrails for the interactive chat or translation outputs, leading to potential blind spots in detecting abusive or poisoned inputs.
Not certain from the listing — no explicit security certifications, access controls, or compliance frameworks (such as SOC2 or GDPR) are mentioned for handling user data or API integrations.
Not certain from the listing — operates primarily as a standalone tool or API without explicit multi-agent or marketplace interactions, minimizing ecosystem-level cascading risks.
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.