Sora2video — agentic threat model

Utilizes advanced closed-source foundation models for video, audio, and physics simulation. Primary threats include adversarial prompt injection to bypass safety filters, model reprogramming, and generating misaligned or harmful synthetic media.

Not certain from the listing — No details are provided regarding training data ingestion, user upload storage, or vector databases. Potential risks include data exfiltration if user-uploaded assets are stored insecurely, and intellectual property/copyright infringement from the underlying training set.

Not certain from the listing — The orchestration framework for multi-shot storytelling and audio synchronization is unspecified. Threats include insecure tool integration if the orchestration layer interacts with external rendering or editing APIs.

Not certain from the listing — Infrastructure details are absent. The primary threat at this layer is GPU resource exhaustion (denial of service) due to the high computational demands of video rendering, alongside standard container compromise risks.

Not certain from the listing — No mention of content moderation guardrails, output validation, or logging. The lack of automated safety filters for generated video and audio represents a significant blind spot for detecting deepfakes or policy violations.

Not certain from the listing — No compliance frameworks (e.g., EU AI Act compliance for synthetic media) or authentication mechanisms are detailed. The absence of cryptographic watermarking or provenance tracking for generated videos poses a major compliance and trust risk.

Not certain from the listing — The agent operates as a standalone horizontal tool with no described multi-agent or marketplace integrations. Ecosystem risks are currently negligible unless integrated into automated downstream publishing pipelines.