CVE-2026-76393

Received Received - Intake

Race Condition in Splunk AI Toolkit

Publication date: 2026-08-19

Last updated on: 2026-08-19

Assigner: Cisco Systems, Inc.

Description

In Splunk AI Toolkit versions below 6.0.0, a user who can upload models could overwrite a model being uploaded by another user by sending a concurrent upload request for the same model name, causing the resulting model lookup entry to reference attacker-controlled content. The race condition is possible because Splunk AI Toolkit does not verify that the uploaded content belongs to the request that creates the model lookup entry. 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.

CVSS Scores

EPSS Scores

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Meta Information

Published

2026-08-19

Last Modified

2026-08-19

Generated

2026-08-20

AI Q&A

2026-08-20

EPSS Evaluated

N/A

NVD

CVE-2026-76393

EUVD

EUVD-2026-62958

Affected Vendors & Products

Vendor	Product	Version / Range
splunk	splunk_ai_toolkit	to 6.0.0 (exc)

Helpful Resources

Exploitability

CWE

KEV

CWE ID	Description
CWE-362	The product contains a concurrent code sequence that requires temporary, exclusive access to a shared resource, but a timing window exists in which the shared resource can be modified by another code sequence operating concurrently.

Attack-Flow Graph

Executive Summary

This vulnerability is a race condition in Splunk AI Toolkit versions below 6.0.0. A user can exploit it by uploading a model with the same name as another user's concurrent upload. This causes the model lookup entry to reference the attacker's content instead of the legitimate one, due to lack of verification that the uploaded content matches the request creating the entry.

Detection Guidance

Detecting this vulnerability requires monitoring for concurrent upload attempts to the Splunk AI Toolkit for the same model name. Check Splunk logs for multiple upload requests with identical model names in a short timeframe. Look for entries in the Splunk internal logs under /var/log/splunk/ for model upload activities.

Impact Analysis

An attacker could replace a legitimate model with malicious content, leading to incorrect data processing, potential data breaches, or unauthorized access. This could disrupt operations or expose sensitive information depending on the model's use case.

Compliance Impact

This vulnerability could lead to unauthorized data access or processing, violating GDPR's data integrity and confidentiality requirements or HIPAA's safeguards for protected health information. Non-compliance risks include legal penalties and reputational damage.

Mitigation Strategies

Upgrade Splunk AI Toolkit to version 6.0.0 or higher immediately. Temporarily restrict model upload permissions to trusted users only. Monitor upload activities closely for suspicious concurrent requests. Review and audit existing model lookup entries for unauthorized changes.

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