ElizaOS — agentic threat model

Not certain from the listing — ElizaOS supports 'Flexible AI model support' but does not specify a default foundation model. Threats include adversarial prompt injection bypassing character constraints, or model reprogramming if local models are used.

ElizaOS features an 'Advanced RAG system for memory management'. This introduces risks of vector database poisoning, where malicious inputs are persisted into long-term memory, leading to persistent downstream exploitation or data exfiltration via RAG context.

As a TypeScript-based orchestration framework, vulnerabilities in tool execution, character prompt parsing, or insecure state transitions could allow attackers to hijack agent planning or trigger unauthorized tool calls.

Not certain from the listing — The deployment infrastructure is managed by the user. However, running autonomous agents with Web3/blockchain capabilities and multi-platform integrations (Discord, Telegram) without strict sandboxing poses high host compromise and credential theft risks.

Not certain from the listing — The framework's description does not detail built-in guardrails, evaluation suites, or observability logging, creating potential blind spots for detecting drift, prompt injection, or anomalous agent behavior.

Not certain from the listing — There is no mention of built-in compliance frameworks, role-based access control (RBAC), or audit logging for agent actions, which is critical given its target Web3 and multi-platform deployment environments.

ElizaOS explicitly supports a 'Multi-agent architecture'. This introduces threats of cascading failures, agent-to-agent trust abuse, and lateral movement where a single compromised agent compromises the entire multi-agent network.