CVE-2026-24152: NVIDIA Megatron LM · Deserialization of Untrusted Data
Affects NVIDIA Megatron LMSource CVE Database V5
Not known to be exploited · CVSS 7.8 High : upgrade to 0.15.3 soon.
Data as of 29 Oct 2026, 19:04 UTC
- EPSS
- 0.2% chance of exploitation in 30 days – higher than 11% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 0.15.3
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 Mar 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: 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 29 Oct 2026.
What to do
Upgrade megatron-lm to 0.15.3.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| NVIDIAMegatron LM | Affected
| Fixed in– |
PyPImegatron-lmpkg:pypi/megatron-lmOther threats | Affected
| Fixed in
|
Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.
AI-suggested
To mitigate CVE-2026-24152, organizations should immediately upgrade NVIDIA Megatron-LM to version 0.15.3 or later once available. Until patched, restrict checkpoint file loading to trusted and verified sources only, employing cryptographic signatures or hashes to validate integrity. Implement strict access controls and least privilege principles to limit who can load checkpoints and run Megatron-LM processes. Use sandboxing or containerization to isolate the model loading environment, reducing potential damage from exploitation. Monitor file system and process activity for unusual checkpoint file loads or suspicious behavior. Educate users about the risks of loading untrusted checkpoint files and enforce policies against using files from unknown origins. Employ endpoint detection and response (EDR) tools to detect anomalous code execution patterns. Regularly audit AI infrastructure for unauthorized files or modifications. Collaborate with NVIDIA support and security advisories to stay updated on patches and best practices. Finally, consider network segmentation to isolate AI workloads from sensitive production systems to contain potential breaches.
Description
NVIDIA Megatron-LM contains a vulnerability in checkpoint loading where an Attacker may cause an RCE by convincing a user to load a maliciously crafted file. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, information disclosure, and data tampering.