Gemini Code Assist — agentic threat model
Gemini Code Assist poses a moderate-to-high risk due to its deep integration into developer IDEs and access to private codebases, where compromised suggestions could lead to supply chain attacks, though risk is mitigated by human-in-the-loop code review.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.40 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.80 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.60 | |
| 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.
Uses Google's Gemini LLMs trained on vast code datasets. Vulnerable to adversarial prompt injection that could bypass safety filters, leading to the generation of insecure or malicious code snippets.
Customizes suggestions using private codebases and local workspace context. Risks include data exfiltration of proprietary IP if the model or its telemetry channels are compromised, or context poisoning if malicious files are introduced to the workspace.
Orchestrates code transformations, smart actions, and Firebase integrations. Vulnerable to insecure tool integration if the IDE extension executes generated commands or API calls without strict validation.
Not certain from the listing — details of the local IDE sandbox or Google Cloud backend isolation are not fully specified, but local execution risks container/host compromise if generated code is executed blindly.
Not certain from the listing — details on real-time guardrails, telemetry, or logging of generated code security are not explicitly detailed.
Not certain from the listing — while it claims enterprise security and privacy protection, specific compliance certifications (e.g., SOC2, ISO) or access controls are not detailed.
Not certain from the listing — multi-agent coordination or marketplace interactions are not explicitly mentioned, though integration with Firebase suggests external ecosystem touchpoints.
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.