Infora AI — agentic threat model
Infora AI is a search, news classification, and knowledge engagement agent with moderate risk, primarily centered around data integrity (news poisoning) and prompt injection via external search results, rather than high-impact autonomous actions.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.40 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.50 | |
| Opacity & Reflexivity | 0.40 |
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 utilizes third-party LLMs for search processing and news classification. Primary threats include prompt injection via untrusted search results and misaligned outputs during user interaction.
Not certain from the listing — relies on dynamic news feeds and search APIs. Highly vulnerable to data/knowledge-base poisoning if malicious actors manipulate external web content indexed by the agent.
Not certain from the listing — orchestration likely manages search queries and result synthesis. Risks include insecure tool integration with external search APIs and potential tool misuse if query parameters can be manipulated.
Not certain from the listing — hosted as a web platform/API. Standard cloud infrastructure risks apply, including API exposure, lack of rate limiting, and potential server-side request forgery (SSRF) via the search functionality.
Not certain from the listing — no mention of output guardrails or monitoring. Gaps here could allow toxic, biased, or hallucinated news summaries to reach users undetected.
Not certain from the listing — no compliance frameworks (e.g., SOC2, GDPR) or robust identity/access management controls are specified for the API or community features.
Not certain from the listing — features 'Community Engagement & Interaction' which could expose users to social engineering or collaborative risks if other automated agents interact within the same ecosystem.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).