Executive Summary
Menlo Ventures outlines production LLM risks including prompt injection, insecure output handling, data disclosure, insecure plugins, model theft and poisoning.
What Happened
Menlo Ventures outlines concrete security risks in production LLM and agent deployments, including prompt injection, insecure output handling, sensitive information disclosure, insecure plugin design, model theft, and data poisoning attacks.[1] The piece highlights demonstrations such as synthetic ChatGPT compromises at Black Hat and a poisoned GPT-J-6B model on Hugging Face, emphasizing that AI models and their supply chains are becoming primary targets for attackers and a focus area for new security startups.[1]
Vulnerability / Attack Technique
GenAI application risks (overview)
Technical Mechanism
Overview with cited demonstrations.
AI Security Category
LLM01:2025 Prompt Injection
Part of the Prompt Injection topic.
Relevant Frameworks
RealGround Analysis
A readable map of LLM risks aligned with OWASP.
Recommended Controls
- Use the OWASP LLM Top 10 as a checklist
Related RealGround Service
AI Agent SBOM and LLM Mapping · or start with the free AI Agent Security Scanner.
Sources
Menlo Ventures: https://menlovc.com/perspective/security-for-ai-genai-risks-and-the-emerging-startup-landscape/
Summary and analysis written by RealGround from the source above; last updated 2026-10-18.