NVIDIA Megatron-LM सभी प्लेटफार्मों के लिए एक भेद्यता है 'megatron/training/\narguments.py' घटक में, जहाँ एक हमलावर दुर्भावनापूर्ण इनपुट प्रदान करके एक कोड इंजेक्शन समस्या पैदा कर सकता है। एक स

Successful exploitation of CVE-2025-23306 allows an attacker to inject and execute arbitrary code within the Megatron-LM environment. This could lead to complete system compromise, enabling the attacker to steal sensitive training data, modify model parameters, or even gain control of the underlying infrastructure. The potential for privilege escalation is significant, as the attacker could leverage the injected code to gain higher-level access. Data tampering could corrupt the training process, leading to biased or unreliable models. The blast radius extends to any system utilizing vulnerable versions of Megatron-LM, particularly those involved in sensitive AI model development.

Organizations and researchers actively developing and deploying large language models using NVIDIA Megatron-LM are at risk. This includes those utilizing cloud-based training environments and those with custom integrations or pipelines that process external input into the Megatron-LM framework. Specifically, those relying on older, unpatched versions of Megatron-LM are most vulnerable.

• python / supply-chain:

import os
import subprocess

# Check for vulnerable arguments.py file
process = subprocess.Popen(['find', '/path/to/megatron-lm', '-name', 'arguments.py'], stdout=subprocess.PIPE)
for line in process.stdout:
    print(line.decode('utf-8').strip())

# Monitor for suspicious process executions
# Example: Check for processes executing arguments.py with unusual arguments

• linux / server:

# Check for modifications to arguments.py
find /path/to/megatron-lm -type f -name arguments.py -mtime -1

# Monitor system logs for suspicious activity related to arguments.py
journalctl -f | grep arguments.py

1. 2025-08-13Disclosure

   disclosure

1. आरक्षित2025-01-14
2. प्रकाशित2025-08-13
3. EPSS अद्यतन2026-03-23

The primary mitigation for CVE-2025-23306 is to immediately upgrade to NVIDIA Megatron-LM version 0.12.2 or later. If upgrading is not immediately feasible, carefully sanitize all input provided to the megatron/training/arguments.py component. Implement strict input validation and consider using a Web Application Firewall (WAF) to filter potentially malicious requests. Monitor system logs for unusual activity, specifically looking for unexpected code execution or file modifications. While a specific Sigma or YARA rule isn't readily available, focus on detecting anomalous process behavior associated with the arguments.py script.