CVE-2025-23354: NVIDIA Megatron-LM · Code Injection
Affects NVIDIA Megatron-LMSource CVE Database V5
Not known to be exploited · CVSS 7.8 High : upgrade to 0.13.1 soon.
Data as of 25 Oct 2026, 19:02 UTC
- EPSS
- 0.2% chance of exploitation in 30 days – higher than 15% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 0.13.1
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HExploitation evidence
Disclosed: evidence found.
CVE published 24 Sep 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-25.
What to do
Upgrade NVIDIA Megatron-LM to 0.13.1.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| NVIDIA Megatron-LM | Affected
| Fixed in
|
AI-suggested
To mitigate CVE-2025-23354, organizations should immediately upgrade NVIDIA Megatron-LM to versions 0.13.1 or 0.12.3 or later, where the vulnerability has been patched. Until upgrades can be applied, restrict access to systems running Megatron-LM to trusted users only, minimizing the risk of local exploitation. Implement strict input validation and sanitization for any data processed by the ensemble_classifier script, ensuring that untrusted or external data cannot be interpreted as executable code. Employ application whitelisting and runtime application self-protection (RASP) techniques to detect and block anomalous code execution attempts. Monitor system logs and behavior for unusual activities indicative of exploitation attempts, such as unexpected privilege escalations or code execution patterns. Additionally, enforce the principle of least privilege for users and processes interacting with Megatron-LM to limit the potential impact of a successful exploit. Regularly audit and review AI model training pipelines and data sources to detect any signs of tampering or compromise. Finally, integrate vulnerability management processes to track NVIDIA product updates and promptly apply security patches.
Description
NVIDIA Megatron-LM for all platforms contains a vulnerability in the ensemble_classifer script where malicious data created by an attacker may cause an injection. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, Information disclosure, and data tampering.