ScriptGecko — agentic threat model
ScriptGecko is a low-risk, single-purpose utility agent focused on transcribing public video URLs. Its primary security risks are limited to SSRF via URL inputs and potential model manipulation through adversarial audio/video content.
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 | 0.20 | |
| 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 — likely utilizes an external speech-to-text or multimodal foundation model (e.g., Whisper). Primary threats include adversarial audio inputs designed to cause transcription errors or prompt injection embedded within the video's audio track.
Not certain from the listing — processes transient video/audio data fetched from public URLs. Risks include insecure caching of downloaded media files or transcripts, and lack of data lineage for external content.
The agent uses a simple, non-agentic linear pipeline (fetch, transcribe, format). The main framework risk is Server-Side Request Forgery (SSRF) if the URL fetching tool does not restrict internal IP ranges.
Not certain from the listing — requires secure, sandboxed environments to download and process untrusted media files to prevent remote code execution (RCE) via malformed media codecs.
Not certain from the listing — requires monitoring for high-volume URL scraping attempts and logging of failed transcription jobs without exposing user-submitted URLs in logs.
Employs basic access controls and rate limiting via guest and signed-in daily usage limits, mitigating denial-of-service and resource exhaustion attacks.
Operates as an isolated, self-contained productivity utility with no multi-agent coordination or ecosystem dependencies, resulting in minimal ecosystem risk.
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.