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Seedance25AI — agentic threat model

5.5AIVSS 5.5 · Medium

Seedance25AI is a low-risk, browser-based video generation agent with minimal agentic autonomy, primarily functioning as a deterministic creative tool with limited exposure to critical enterprise systems.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 4.3AARS uplift 1.25Factor sum 2.3/10Threat ×0.95Mitigation ×1.0
Autonomy of Action
0.10
Goal-Driven Planning
0.20
Self-Modification
0.10
Dynamic Tool Use
0.10
Persistent Memory
0.20
Contextual Awareness
0.30
Dynamic Identity
0.00
Multi-Agent Interactions
0.00
Non-Determinism
0.80
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.

L1 · Foundation Models✓ mapped

Utilizes proprietary text-to-video and image-to-video foundation models. Vulnerable to prompt injection designed to bypass safety filters, leading to the generation of deepfakes, copyrighted material, or explicit content.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — likely processes user-uploaded image references and text prompts via standard web forms. Potential risks include data exfiltration of uploaded assets or poisoning of downstream model fine-tuning if user inputs are reused for training.

L3 · Agent Frameworks✓ mapped

Orchestrates a simple workflow of prompt enhancement and video generation. The framework is highly constrained with minimal tool-calling capabilities, reducing the risk of arbitrary code execution or tool misuse.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — operates as a browser-based SaaS application. Standard web infrastructure threats apply, including server-side rendering vulnerabilities, insecure API endpoints for video rendering, and lack of sandboxing for user-uploaded media processing.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — requires input/output guardrails to detect and block generation of harmful, abusive, or infringing video content, but specific evaluation or observability mechanisms are not detailed.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — lacks explicit mention of compliance certifications (e.g., SOC2, GDPR) or content moderation policies, which are critical for managing copyright and synthetic media regulations.

L7 · Agent Ecosystem✓ mapped

Operates as a standalone horizontal creative tool with no multi-agent coordination or marketplace integrations described, resulting in negligible 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.