VibeCode — agentic threat model
VibeCode presents a significant supply-chain and infrastructure risk because it automatically generates and deploys full-stack applications (frontend, backend, database) from natural language prompts. A compromise of its generation engine could lead to widespread injection of vulnerabilities or malicious code into customer applications.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.60 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.70 | |
| 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.
Not certain from the listing — The specific foundation models used for code generation are not disclosed. Threats include prompt injection that bypasses safety filters to generate malicious code, and model reprogramming.
Not certain from the listing — The data operations, training sets, and codebase repositories used to train the generator are proprietary. Threats include training data poisoning that introduces subtle backdoors into generated code.
Not certain from the listing — The orchestration framework translating prompts into full-stack code is opaque. Threats include insecure tool integration where the generator might execute unsafe system commands during the build process.
VibeCode hosts and deploys generated apps on its own 'enterprise-grade infrastructure'. This creates high risks of container escape, lateral movement between tenant applications, and hosting-level privilege escalation if the deployment environment is not strictly sandboxed.
Not certain from the listing — There is no mention of automated static analysis (SAST), dynamic analysis (DAST), or guardrails to inspect the generated code before deployment, creating a blind spot for vulnerable code deployment.
The platform claims 'enterprise-grade infrastructure' and eliminates third-party API dependencies, which reduces external data leakage risks, but specific compliance certifications (e.g., SOC2, ISO 27001) are not verified in the listing.
Not certain from the listing — The platform operates as a closed, horizontal app builder with no explicit multi-agent ecosystem or marketplace, minimizing agent-to-agent trust abuse risks at this stage.
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.