CVE-2025-33247: Nvidia Megatron-lm RCE Vulnerability

CVE-2025-33247 Overview

NVIDIA Megatron LM contains an insecure deserialization vulnerability in the quantization configuration loading functionality. This vulnerability allows attackers to achieve remote code execution by supplying a maliciously crafted quantization configuration file. A successful exploit of this vulnerability could lead to code execution, escalation of privileges, information disclosure, and data tampering on systems running the affected software.

Critical Impact

Successful exploitation enables attackers to execute arbitrary code, escalate privileges, disclose sensitive information, and tamper with data on affected NVIDIA Megatron LM deployments used for large language model training.

Affected Products

• NVIDIA Megatron-LM (all versions prior to patch)

Discovery Timeline

• 2026-03-24 - CVE-2025-33247 published to NVD
• 2026-03-25 - Last updated in NVD database

Technical Details for CVE-2025-33247

Vulnerability Analysis

This vulnerability is classified under CWE-502 (Deserialization of Untrusted Data). The flaw exists in how NVIDIA Megatron LM handles quantization configuration loading, where untrusted input is deserialized without proper validation. When the application processes a maliciously crafted configuration file, it can instantiate arbitrary objects and execute attacker-controlled code.

The vulnerability requires local access to exploit, meaning an attacker must have some level of access to the system or be able to supply malicious configuration files to the application. Once exploited, the impact is severe across all three security pillars: confidentiality, integrity, and availability of the affected system.

Root Cause

The root cause of CVE-2025-33247 lies in the unsafe deserialization of quantization configuration data within NVIDIA Megatron LM. The application fails to properly validate or sanitize configuration input before deserializing it, allowing attackers to inject malicious serialized objects. When these objects are deserialized, they can trigger code execution through gadget chains present in the application's dependencies.

Attack Vector

The attack vector for this vulnerability is local, requiring the attacker to have access to the target system or the ability to supply malicious configuration files. The attack proceeds as follows:

1. The attacker crafts a malicious quantization configuration file containing serialized payloads
2. The attacker delivers the malicious configuration to the target system through available means (file upload, shared storage, or supply chain compromise)
3. When NVIDIA Megatron LM loads the quantization configuration, the insecure deserialization triggers
4. The malicious payload executes with the privileges of the application, enabling code execution, privilege escalation, or data exfiltration

The vulnerability mechanism involves unsafe deserialization of configuration data in the quantization loading component. When a malicious configuration file is processed, the deserializer instantiates objects without proper type restrictions, allowing attackers to leverage existing code gadgets to achieve arbitrary code execution. For detailed technical information, refer to the NVIDIA Security Advisory.

Detection Methods for CVE-2025-33247

Indicators of Compromise

• Unexpected or modified quantization configuration files in Megatron LM directories
• Anomalous process spawning from Megatron LM training processes
• Unusual network connections initiated by the Megatron LM application
• Unauthorized file system access or modifications during model training operations

Detection Strategies

• Monitor file integrity of quantization configuration files used by Megatron LM
• Implement application-level logging to detect unusual configuration loading behavior
• Deploy endpoint detection solutions to identify suspicious process execution chains originating from Megatron LM processes
• Audit access to configuration files and directories used by the training framework

Monitoring Recommendations

• Enable detailed logging for Megatron LM configuration loading operations
• Monitor for deserialization-related exceptions or errors in application logs
• Implement behavioral monitoring on systems running large language model training workloads
• Track file access patterns for quantization configuration files

How to Mitigate CVE-2025-33247

Immediate Actions Required

• Review and apply the security patch from NVIDIA immediately
• Restrict access to quantization configuration files to trusted users only
• Validate the integrity and source of all configuration files before loading
• Implement network segmentation for systems running Megatron LM training workloads

Patch Information

NVIDIA has released a security advisory addressing this vulnerability. Organizations using NVIDIA Megatron LM should review the NVIDIA Support Answer for specific patch information and updated versions. Apply the vendor-provided patches as soon as possible to remediate this vulnerability.

Workarounds

• Implement strict file system permissions to prevent unauthorized modification of configuration files
• Use allowlisting to restrict which configuration files can be loaded by the application
• Run Megatron LM processes with minimal required privileges
• Isolate training environments from untrusted networks and users

# Restrict configuration file permissions
chmod 600 /path/to/megatron-lm/quantization/configs/*
chown root:megatron-lm /path/to/megatron-lm/quantization/configs/*

# Enable file integrity monitoring (example using inotifywait)
inotifywait -m -r /path/to/megatron-lm/quantization/configs/ -e modify,create,delete