kragent.ai — agentic threat model
kragent.ai presents a high-risk profile due to its combination of autonomous browser interaction and code execution capabilities, which could be exploited via prompt injection or sandbox escape to compromise user environments or exfiltrate API keys.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.80 | |
| Self-Modification | 0.30 | |
| Dynamic Tool Use | 0.90 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.80 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.60 |
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 external commercial and open-source foundation models (such as Claude) via model mixing. Primary threats include adversarial prompt injection via untrusted web content and potential model misalignment during autonomous execution.
Processes external data dynamically through web search, document uploads, and image analysis. This introduces significant risks of data poisoning from malicious web pages and data exfiltration of sensitive user-uploaded documents.
Orchestrates complex tasks including code prototyping, debugging, and browser navigation. The primary threat is tool misuse, where an attacker manipulates the agent's planning framework to execute unauthorized browser actions or malicious code.
Features a code execution sandbox to run and debug code safely. However, infrastructure threats persist around potential sandbox escape, container compromise, and the exposure of user-configured API keys used for model mixing.
Not certain from the listing — there is no explicit mention of real-time monitoring, guardrails, or logging mechanisms to detect anomalous agent behavior or drift during deep research tasks.
Not certain from the listing — while it supports flexible API key configurations (suggesting user-managed credentials), there is no detailed information regarding enterprise identity management, access controls, or regulatory compliance.
Not certain from the listing — the agent is described as a general-purpose autonomous assistant, but there is no mention of multi-agent collaboration, delegation, or interaction within a broader agent ecosystem.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).