AI Risk Report: Fast-Growing Threats in AI Runtime
Summary
Runtime attacks on large language models are rapidly increasing, with jailbreak techniques (methods that bypass AI safety restrictions) and denial-of-service exploits (attacks that make systems unavailable) becoming more sophisticated and widely shared through open-source platforms like GitHub. The report explains that these attacks have evolved from isolated research experiments into organized toolkits accessible to threat actors, affecting production AI deployments across enterprises.
Classification
Related Issues
CVE-2024-27444: langchain_experimental (aka LangChain Experimental) in LangChain before 0.1.8 allows an attacker to bypass the CVE-2023-
CVE-2026-47482: NVIDIA Triton Inference Server for Linux contains a vulnerability where an attacker can cause missing release of memory
Original source: https://protectai.com/blog/ai-risk-report-fast-growing-threats-in-ai-runtime
First tracked: March 13, 2026 at 12:56 PM
Classified by LLM (prompt v3) · confidence: 85%