Cekura (YC F24) — agentic threat model
Cekura presents a high-risk profile due to its write-access to customer-facing knowledge bases and its active browser-based navigation of SaaS products. A compromise or prompt injection could lead to widespread documentation defacement, XSS injection, or unauthorized actions within the target SaaS applications.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.80 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.50 | |
| 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.
Not certain from the listing — likely relies on commercial vision-language models (like GPT-4o) for UI navigation and text models for documentation analysis. Threats include prompt injection via malicious documentation or UI elements leading to unauthorized actions.
Integrates directly with existing knowledge bases and SaaS product data. Threats include data poisoning where malicious documentation updates are injected, or sensitive SaaS data is exfiltrated through the browser agent.
Orchestrates browser navigation and KB updates. Threats include tool misuse (e.g., the agent performing destructive actions in the SaaS product during navigation) and insecure tool integration with KB APIs.
Not certain from the listing — requires a secure browser execution environment (sandbox) to navigate SaaS products safely. Threats include container escape or credential theft from the browser session.
Not certain from the listing — requires robust logging of browser actions and KB modifications to detect drift or malicious behavior. Gaps here could lead to undetected unauthorized documentation changes.
Not certain from the listing — requires strict RBAC for KB integrations and SaaS product login credentials. Lack of explicit compliance certifications (e.g., SOC2) increases risk.
Not certain from the listing — primarily operates as a single-agent browser automation tool. However, cascading failures could occur if it interacts with other automated customer support agents.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).