Ask-AI — agentic threat model
Ask-AI presents a moderate-to-high agentic risk primarily driven by its deep integration into sensitive enterprise data silos (Slack, Tickets, KBs) and its automation capabilities. While its autonomy is bounded by assistant-style interactions, a compromise could lead to significant data exfiltration or unauthorized communication.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.80 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.20 | |
| 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 — The specific foundation models powering Ask-AI are not disclosed. Standard LLM threats such as prompt injection, jailbreaking, and misaligned outputs remain a baseline risk for any generative AI assistant.
Ask-AI connects directly to enterprise knowledge bases including Slack, Tickets, Docs, and KBs. This creates a high risk of data exfiltration, knowledge-base poisoning, and unauthorized access if the RAG pipeline does not strictly enforce source-system access controls.
The platform orchestrates custom AI applications and Slack automation. Vulnerabilities in the agent framework could allow malicious prompt injections to trigger unauthorized Slack actions, API calls, or tool misuse.
Not certain from the listing — The hosting infrastructure, network isolation, secrets management, and sandboxing mechanisms for executing custom AI applications are not detailed in the public directory.
The listing highlights 'AI Analytics', suggesting some level of interaction monitoring and usage reporting. However, specific real-time guardrails, prompt filtering, or drift detection mechanisms are not detailed.
Not certain from the listing — While high-profile customers like Snyk and Rapid7 imply enterprise-grade security, the listing does not explicitly detail RBAC, authentication standards, or compliance certifications (e.g., SOC2, ISO 27001).
Not certain from the listing — The platform supports 'custom AI Applications' and 'Slack Automation', but it is unclear if these operate in a multi-agent ecosystem or if there are risks of cascading failures and agent-to-agent trust abuse.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).