Edimakor — agentic threat model
Edimakor is a desktop-based AI-assisted video editor with low agentic autonomy, primarily functioning as a human-in-the-loop creative tool. Its primary security risks stem from local data access (screen recording, media files) and potential cloud-based AI processing of user media rather than autonomous decision-making.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.10 | |
| 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 — The specific foundation models used for speech-to-text, translation, and copywriting are not disclosed. Potential threats include adversarial audio/video inputs designed to exploit model vulnerabilities or cause misaligned outputs.
Not certain from the listing — It is unclear whether media processing (translation, avatar generation) occurs locally or via cloud servers. Threats include the potential exfiltration or exposure of sensitive user-recorded video and audio data during transit or cloud storage.
Not certain from the listing — The application does not appear to use an autonomous agent framework, relying instead on direct user commands. Threats are limited to insecure integration of local media processing libraries and command execution vulnerabilities.
Not certain from the listing — As a desktop application for Windows and Mac, the primary infrastructure threats involve local privilege escalation, insecure local file permissions, and lack of sandboxing for executed media codecs.
Not certain from the listing — There is no mention of guardrails or observability mechanisms for AI-generated text or avatars. Threats include the generation of inappropriate, biased, or copyrighted content without administrative oversight.
Not certain from the listing — Compliance certifications (such as SOC2 or GDPR alignment) are not specified. Threats include lack of data deletion policies for uploaded media and insufficient access controls on the local host.
Not certain from the listing — The application operates as a standalone tool without multi-agent orchestration or marketplace integrations, making ecosystem-level threats minimal.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).