CVE-2026-76395
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 deserializes sparse matrix data without guarding against embedded pickle content. For more information see Troubleshoot the Splunk Machine Learning Toolkit (https://help.splunk.com/en/splunk-cloud-platform/apply-machine-learning/machine-learning-toolkit-user-guide/5.5.0/troubleshooting-mltk/troubleshoot-the-splunk-machine-learning-toolkit) in the Splunk documentation.
What this means
- Exposure
- Exploitable remotely over the network, with an ordinary user account and with no action from the victim.
- Impact
- An attacker can read sensitive data, modify or destroy data and take the service offline.
- Weakness
- The application rebuilds an object from attacker-controlled data, which often leads to code execution.
- Likelihood
- Its EPSS score stays low: nothing points to imminent exploitation, which is no reason to leave it unpatched.
What to doFold into the next patch cycle.
Read automatically from the CVSS vector, the weakness type (CWE) and the EPSS score. The technical description above remains the one published by NIST.