AgentGPT — agentic threat model
AgentGPT presents a high agentic risk profile due to its high autonomy and goal-driven planning capabilities powered by GPT-4 and Weaviate. The primary risks stem from potential prompt injection leading to unauthorized tool execution or memory poisoning within its vector database.
OWASP AIVSS score rationale
| Autonomy of Action | 0.90 | |
| Goal-Driven Planning | 0.80 | |
| Self-Modification | 0.50 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.80 | |
| Contextual Awareness | 0.80 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.30 | |
| Non-Determinism | 0.80 | |
| Opacity & Reflexivity | 0.70 |
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.
Utilizes GPT-4 as its foundation model. It is highly susceptible to prompt injection, adversarial reprogramming, and jailbreaks that could hijack the agent's autonomous goal-seeking behavior.
Uses Weaviate vector database for advanced memory management. This introduces risks of memory poisoning, where malicious inputs are persisted and continuously feed back into the agent's context window, as well as potential data exfiltration via embedding inversion.
The framework orchestrates autonomous task generation and execution. Vulnerabilities include planning loops, logic flaws in strategy implementation, and insecure tool integration if the agent is permitted to call external APIs to 'deliver results'.
Not certain from the listing — while the frontend runs in the user's web browser, the backend hosting the Weaviate database and managing GPT-4 API keys must be secured against container compromise, SSRF, and credential theft.
Not certain from the listing — there is no mention of real-time guardrails, execution logging, or drift detection to monitor autonomous agent behavior and prevent runaway execution loops.
Features a 'Secure authentication system' to protect user accounts. However, compliance alignments (such as SOC2 or GDPR) and fine-grained authorization policies for agent actions are not detailed.
Not certain from the listing — while users can create and deploy multiple agents, the listing does not specify if these agents can interact, collaborate, or delegate tasks to one another, which would introduce cascading failure risks.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).