Written by: Christopher Romano, Codi Starks, Garrett Mahoney, John Wolfram, Josh Murchie, K Singh, Mathew Potaczek, Mike Lombardi, Rik Dolfing Introduction Mandiant responded to multiple incidents in 2026 in which threat actors hijacked enterprise access to Large Language Models (LLMs), a tactic known as "LLMJacking." Spanning a variety of cloud and LLM providers, these intrusions impacted organizations in North America, South America, and Asia Pacific across the financial services, retail,…
LiteLLM, an open-source tool widely used by artificial intelligence developers, said a key accidentally exposed in May was behind a supply-chain attack that is believed to have hit tens of thousands of users last week.
TL;DR; Our security assessment of LiteLLM (v1.77.7), a widely used open-source LLM gateway, uncovered multiple high-impact vulnerabilities (tracked as CVE-2026-35029, CVE-2026-59823) which have been resolved as of LiteLLM version 1.83.9. The most significant issues stemmed from a missing authorization check on the /config/update endpoint, which allowed any authenticated user (including low-privileged accounts) to modify the proxy’s runtime configuration. This single flaw enabled arbitrary file…
In this article AI workloads are becoming high-value control pointsCase study 1: LiteLLM gateway compromiseCase study 2: RAGFlow compromiseCase study 3: Kestra compromiseMitigation and protection guidanceMITRE ATT&CK techniques observedReferencesLearn more AI is creating a new layer of enterprise infrastructure. Gateways, retrieval platforms, orchestration services, and containerized runtimes now sit between users, applications, data, and models. These systems concentrate credentials, data…