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EPSS 0.2%top 93%

CVE-2026-76393: The program contains a code sequence that can run concurrently with other code, and the code sequence 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 that is operating concurrently. in Splunk Splunk AI Toolkit

0
Medium
Published: 08/19/2026 (08/19/2026, 21:35:10 UTC)
Source: CVE Database V5
Vendor/Project: Splunk
Product: Splunk AI Toolkit

Description

A race condition vulnerability exists in Splunk AI Toolkit versions 5.7 up to but not including 6.0.0. This flaw allows a user who can upload models to overwrite a model being uploaded by another user by sending concurrent upload requests with the same model name. The vulnerability arises because the toolkit does not verify that the uploaded content corresponds to the request creating the model lookup entry, potentially causing the lookup to reference attacker-controlled content.

CVSS v3.1

Score 5.9medium

Attack Vector
Network
Attack Complexity
High
Privileges Required
Low
User Interaction
Required
Scope
Unchanged
Confidentiality
Low
Integrity
High
Availability
Low
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:L/I:H/A:L

Affected software

Splunk

Splunk AI Toolkit

Affected versions
>=5.7 <6.0.0
GitHub Actionsmore threats →ai
splunk/splunk-ai-toolkit
pkg:github/splunk/splunk-ai-toolkit
Affected versions
=5.7

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AI-Powered Analysis

Machine-generated threat intelligence

AILast updated: 09/11/2026, 06:03:56 UTC

Technical Analysis

CVE-2026-76393 describes a race condition in Splunk AI Toolkit versions >=5.7 and <6.0.0 where concurrent uploads of models with the same name can lead to one user's upload overwriting another's. This occurs because the software fails to verify that the uploaded content belongs to the request that creates the model lookup entry, allowing an attacker to cause the resulting model lookup entry to reference malicious content.

Potential Impact

An attacker with the ability to upload models can overwrite models uploaded by other users, causing the system to reference attacker-controlled content. This can lead to integrity issues where malicious or unintended models are used, potentially impacting the reliability and trustworthiness of the AI toolkit's outputs. The CVSS score of 5.9 (medium severity) reflects limited confidentiality impact but high integrity impact and low availability impact.

Mitigation Recommendations

No explicit patch or remediation details are provided in the input data. Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Until a fix is applied, restrict model upload permissions to trusted users only and monitor for concurrent upload attempts with the same model name to reduce risk.

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Technical Details

Data Version
5.2
Assigner Short Name
cisco
Date Reserved
2026-08-19T12:02:03.631Z
Cvss Version
3.1
State
PUBLISHED

Threat ID: 6a862260acd9273b49a7047b

Added to database: 08/19/2026, 21:38:40 UTC

Last enriched: 09/11/2026, 06:03:56 UTC

Last updated: 10/04/2026, 10:02:29 UTC

Views: 35

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