Researchers Find Serious AI Bugs Exposing Meta, Nvidia, and Microsoft Inference Frameworks

Cybersecurity researchers have uncovered critical remote code execution vulnerabilities impacting major artificial intelligence (AI) inference engines, including those from Meta, Nvidia, Microsoft, and open-source PyTorch projects such as vLLM and SGLang.

“These vulnerabilities all traced back to the same root cause: the overlooked unsafe use of ZeroMQ (ZMQ) and Python’s pickle deserialization,” Oligo Security researcher Avi Lumelsky said in a report published Thursday.

At its core, the issue stems from what has been described as a pattern called ShadowMQ, in which the insecure deserialization logic has propagated to several projects as a result of code reuse.

The root cause is a vulnerability in Meta’s Llama large language model (LLM) framework (CVE-2024-50050, CVSS score: 6.3/9.3) that was patched by the company last October. Specifically, it involved the use of ZeroMQ’s recv_pyobj() method to deserialize incoming data using Python’s pickle module.

This, coupled with the fact…