CVE-2025-33248: 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
- Upgrade NVIDIA Megatron-LM to version 0.15.3 or later immediately, as this version addresses the deserialization vulnerability.
- Implement strict input validation and sanitization on all files and data loaded by the hybrid conversion script to prevent malicious payloads.
- Restrict access to systems running Megatron-LM to trusted users only, minimizing the risk of local exploitation.
- Employ sandboxing or containerization techniques to isolate the execution environment of Megatron-LM, limiting the impact of potential code execution.
- Monitor system logs and behavior for unusual activity indicative of exploitation attempts, such as unexpected file loads or privilege escalations.
- Educate users about the risks of loading untrusted files and enforce policies that prohibit loading files from unverified sources.
- Conduct regular security audits and code reviews focusing on deserialization and input handling practices within AI frameworks.
- Consider using application whitelisting to prevent unauthorized binaries or scripts from executing on systems hosting Megatron-LM.
Description
NVIDIA Megatron-LM contains a vulnerability in the hybrid conversion script 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.