CVE-2026-76395 Remote Code Execution (RCE) through Deserialization of Untrusted Data in the Model Loading REST API in Splunk AI Toolkit

In Splunk AI Toolkit versions below 6.0.0, a user who holds the "power" Splunk role could execute arbitrary code on the Splunk server by loading a model file containing crafted sparse matrix data. The deserialization of untrusted data is possible because a model codec in Splunk AI Toolkit...

CVE-2026-76395

Splunk AI Toolkit versions below 6.0.0 deserialize sparse matrix data containing embedded pickle payloads without validation, allowing a user with the "power" role to execute arbitrary code via the model-loading REST API. The fix is to upgrade to version 6.0.0 or later. No in-the-wild exploitatio...

EUVD-2024-52178

Malicious code in bioql PyPI...

The vulnerability of the Model Loading API component in NVIDIA Triton Inference Server (previously known as TensorRT Inference Server) allows a malicious actor to trigger a service failure.

The vulnerability of the Model Loading component of NVIDIA Triton Inference Server previously known as TensorRT Inference Server is related to a numerical overflow issue. Exploiting this vulnerability could allow an attacker to cause a service failure...

CVE-2024-53880

NVIDIA Triton Inference Server contains a vulnerability in the model loading API, where a user could cause an integer overflow or wraparound error by loading a model with an extra-large file size that overflows an internal variable. A successful exploit of this vulnerability might lead to denial ...

CVE-2024-53880

The CVE-2024-53880 entry pertains to NVIDIA Triton Inference Server. A vulnerability in the model loading API can trigger an integer overflow/wraparound when loading a model with an extra-large file size, overflow an internal variable, and potentially cause a denial of service. Exploitation detai...

CVE-2024-53880

NVIDIA Triton Inference Server contains a vulnerability in the model loading API, where a user could cause an integer overflow or wraparound error by loading a model with an extra-large file size that overflows an internal variable. A successful exploit of this vulnerability might lead to denial ...