Project Astra — agentic threat model

Powered by Google Gemini models. Highly susceptible to multimodal adversarial attacks, such as visual prompt injections hidden in real-time video streams or audio-based hijacking, which can reprogram the agent's behavior.

Not certain from the listing — the exact storage mechanism for persistent memory and real-time video/audio frame buffering is not detailed. However, there is a high risk of memory poisoning if adversarial inputs are stored and recalled in future sessions.

Not certain from the listing — the specific orchestration framework is not disclosed. The primary threat lies in insecure tool integration, where the agent translates multimodal understanding into actions across connected devices without sufficient validation.

Not certain from the listing — deployment architecture on edge devices versus Google Cloud is unspecified. Risks include unauthorized API access, device-level compromise, and side-channel attacks on local multimodal processing hardware.

Not certain from the listing — real-time evaluation and guardrail mechanisms are not detailed. The continuous stream of video and audio makes real-time content filtering and policy enforcement extremely challenging, creating potential blind spots.

Not certain from the listing — compliance certifications and identity/access management policies are not specified. As a prototype, it may lack rigorous enterprise-grade access controls, increasing the risk of unauthorized device interaction.

Not certain from the listing — multi-agent collaboration or marketplace interactions are not explicitly detailed. However, if integrated into a broader ecosystem, it could suffer from cascading failures if compromised by rogue external agents.