CVE-2025-65213

Comprehensive Technical Analysis of CVE-2025-65213

1. Vulnerability Assessment and Severity Evaluation

CVE ID: CVE-2025-65213 CVSS Score: 9.8

The vulnerability in question is an unsafe deserialization issue in the torch_musa library, specifically within the compare_for_single_op() and nan_inf_track_for_single_op() functions. These functions utilize pickle.load() on user-controlled file paths without proper validation, leading to arbitrary code execution.

Severity Evaluation:

• CVSS Base Score: 9.8 (Critical)
• Impact: High
• Exploitability: High

The high CVSS score indicates a critical vulnerability that can be easily exploited, resulting in significant impact. The ability to execute arbitrary code with the privileges of the victim process makes this vulnerability particularly dangerous.

2. Potential Attack Vectors and Exploitation Methods

Attack Vectors:

1. Malicious File Upload: An attacker could upload a crafted pickle file to a location where the vulnerable functions will load it.
2. Phishing: An attacker could trick a user into downloading and loading a malicious pickle file.
3. Supply Chain Attack: An attacker could compromise a third-party library or tool that interacts with torch_musa, injecting a malicious pickle file.

Exploitation Methods:

• Crafting Malicious Pickle Files: An attacker can create a pickle file that contains malicious Python code. When this file is loaded by the vulnerable functions, the code will be executed.
• Remote Code Execution: The executed code can perform various malicious actions, such as data exfiltration, system compromise, or further propagation of malware.

3. Affected Systems and Software Versions

Affected Software:

• MooreThreads torch_musa through all versions

Affected Systems:

• Any system running applications that utilize the torch_musa library, particularly those that handle user-controlled file paths.

4. Recommended Mitigation Strategies

Immediate Mitigation:

1. Avoid Using pickle for Deserialization: Replace pickle with safer serialization formats like JSON or YAML.
2. Input Validation: Implement strict validation on file paths and inputs to ensure they are from trusted sources.
3. Patch Management: Apply patches or updates provided by MooreThreads as soon as they are available.
4. Access Controls: Restrict access to the vulnerable functions and ensure that only trusted users can interact with them.

Long-Term Mitigation:

1. Code Review: Conduct thorough code reviews to identify and remediate similar vulnerabilities.
2. Security Training: Educate developers on the risks associated with unsafe deserialization and best practices for secure coding.
3. Regular Audits: Perform regular security audits and vulnerability assessments to identify and mitigate potential risks.

5. Impact on Cybersecurity Landscape

The discovery of this vulnerability highlights the ongoing risks associated with unsafe deserialization practices. It underscores the importance of secure coding practices and the need for continuous monitoring and updating of software dependencies. The high CVSS score and the potential for remote code execution make this vulnerability a significant concern for organizations relying on the torch_musa library.

6. Technical Details for Security Professionals

Vulnerable Functions:

• compare_for_single_op()
• nan_inf_track_for_single_op()

Vulnerable Code Snippet:

import pickle

def compare_for_single_op(file_path):
    with open(file_path, 'rb') as f:
        data = pickle.load(f)
    # Further processing

def nan_inf_track_for_single_op(file_path):
    with open(file_path, 'rb') as f:
        data = pickle.load(f)
    # Further processing

Exploitation Example: An attacker can create a pickle file with the following content:

import os
os.system('malicious_command')

When this file is loaded by the vulnerable functions, the malicious_command will be executed.

Mitigation Example: Replace pickle with json for safer deserialization:

import json

def compare_for_single_op(file_path):
    with open(file_path, 'r') as f:
        data = json.load(f)
    # Further processing

def nan_inf_track_for_single_op(file_path):
    with open(file_path, 'r') as f:
        data = json.load(f)
    # Further processing

Conclusion: CVE-2025-65213 represents a critical vulnerability that requires immediate attention. Organizations should prioritize patching and implementing the recommended mitigation strategies to protect against potential exploitation. Continuous vigilance and adherence to secure coding practices are essential to safeguard against similar vulnerabilities in the future.