CVE-2026-24149: NVIDIA Megatron-LM · Code Injection
Affects NVIDIA Megatron-LMSource CVE Database V5
Not known to be exploited · CVSS 7.8 High : upgrade to 0.14.0 soon.
Data as of 25 Oct 2026, 19:02 UTC
- EPSS
- 0.2% chance of exploitation in 30 days – higher than 21% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 0.14.0
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 3 Feb 2026
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 0.14.0.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| NVIDIAMegatron-LM | Affected
| Fixed in
|
AI-suggested
Immediate mitigation should focus on restricting access to the vulnerable Megatron-LM scripts to trusted users only, enforcing strict access controls and monitoring local user activities for suspicious behavior. Organizations should implement rigorous input validation and sanitization within any custom scripts or data pipelines interacting with Megatron-LM. Network segmentation and endpoint protection can reduce the risk of lateral movement if exploitation occurs. Since no official patches are available yet, organizations should prepare to apply updates promptly once released by NVIDIA. Additionally, conducting thorough audits of AI infrastructure and applying principle of least privilege for all users and processes interacting with Megatron-LM will reduce attack surface. Employing runtime application self-protection (RASP) or behavior-based anomaly detection tools can help detect exploitation attempts. Finally, organizations should maintain incident response readiness specific to AI platform compromises.
Description
NVIDIA Megatron-LM for all platforms contains a vulnerability in a script, where malicious data created by an attacker may cause a code injection issue. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, information disclosure, data tampering.