A newly disclosed set of safety flaws in NVIDIA’s Triton Inference Server for Home windows and Linux, an open-source platform for working synthetic intelligence (AI) fashions at scale, could possibly be exploited to take over inclined servers.
“When chained collectively, these flaws can probably permit a distant, unauthenticated attacker to realize full management of the server, attaining distant code execution (RCE),” Wiz researchers Ronen Shustin and Nir Ohfeld mentioned in a report revealed at present.
The vulnerabilities are listed beneath –
- CVE-2025-23319 (CVSS rating: 8.1) – A vulnerability within the Python backend, the place an attacker might trigger an out-of-bounds write by sending a request
- CVE-2025-23320 (CVSS rating: 7.5) – A vulnerability within the Python backend, the place an attacker might trigger the shared reminiscence restrict to be exceeded by sending a really massive request
- CVE-2025-23334 (CVSS rating: 5.9) – A vulnerability within the Python backend, the place an attacker might trigger an out-of-bounds learn by sending a request
Profitable exploitation of the aforementioned vulnerabilities might end in info disclosure, in addition to distant code execution, denial of service, knowledge tampering within the case of CVE-2025-23319. The problems have been addressed in model 25.07.
The cloud safety firm mentioned the three shortcomings could possibly be mixed collectively that transforms the issue from an info leak to a full system compromise with out requiring any credentials.
Particularly, the issues are rooted within the Python backend that is designed to deal with inference requests for Python fashions from any main AI frameworks akin to PyTorch and TensorFlow.
Within the assault outlined by Wiz, a risk actor might exploit CVE-2025-23320 to leak the complete, distinctive title of the backend’s inner IPC shared reminiscence area, a key that ought to have remained personal, after which leverage the remaining two flaws to realize full management of the inference server.
“This poses a crucial danger to organizations utilizing Triton for AI/ML, as a profitable assault might result in the theft of worthwhile AI fashions, publicity of delicate knowledge, manipulating the AI mannequin’s responses, and a foothold for attackers to maneuver deeper right into a community,” the researchers mentioned.
NVIDIA’s August bulletin for Triton Inference Server additionally highlights fixes for 3 crucial bugs (CVE-2025-23310, CVE-2025-23311, and CVE-2025-23317) that, if efficiently exploited, might end in distant code execution, denial of service, info disclosure, and knowledge tampering.
Whereas there isn’t a proof that any of those vulnerabilities have been exploited within the wild, customers are suggested to use the most recent updates for optimum safety.
