Description
MooreThreads torch_musa through all versions contains an unsafe deserialization vulnerability in torch_musa.utils.compare_tool. The compare_for_single_op() and nan_inf_track_for_single_op() functions use pickle.load() on user-controlled file paths without validation, allowing arbitrary code execution. An attacker can craft a malicious pickle file that executes arbitrary Python code when loaded, enabling remote code execution with the privileges of the victim process.
EPSS Score:
0%
Comprehensive Technical Analysis of EUVD-2025-203406
1. Vulnerability Assessment and Severity Evaluation
The vulnerability identified in EUVD-2025-203406 pertains to 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() to deserialize user-controlled file paths without proper validation, leading to arbitrary code execution.
Severity Evaluation:
- Base Score: 9.8 (Critical)
- Base Score Version: CVSS 3.1
- Base Score Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
The high base score indicates a critical vulnerability due to the following factors:
- Attack Vector (AV): Network (N)
- Attack Complexity (AC): Low (L)
- Privileges Required (PR): None (N)
- User Interaction (UI): None (N)
- Scope (S): Unchanged (U)
- Confidentiality (C): High (H)
- Integrity (I): High (H)
- Availability (A): High (H)
This vulnerability allows for remote code execution with the privileges of the victim process, making it highly dangerous.
2. Potential Attack Vectors and Exploitation Methods
Attack Vectors:
- Network-Based Attacks: An attacker can exploit this vulnerability over the network by crafting a malicious pickle file and enticing the victim to load it.
- Phishing and Social Engineering: Attackers may use phishing emails or social engineering tactics to deliver the malicious pickle file to unsuspecting users.
Exploitation Methods:
- Crafting Malicious Pickle Files: An attacker can create a pickle file containing malicious Python code. When this file is loaded by the vulnerable functions, the malicious code is executed.
- Remote Code Execution: The attacker can execute arbitrary code with the same privileges as the victim process, leading to potential data breaches, system compromise, and further lateral movement within the network.
3. Affected Systems and Software Versions
Affected Systems:
- Any system running the
torch_musalibrary through all versions.
Software Versions:
- All versions of
torch_musaare affected by this vulnerability.
4. Recommended Mitigation Strategies
Immediate Mitigation:
- Avoid Using
pickle.load(): Refrain from usingpickle.load()for deserializing user-controlled data. - Input Validation: Implement robust input validation to ensure that only trusted and validated data is processed.
- Use Safer Alternatives: Consider using safer serialization formats such as JSON or YAML, which do not execute arbitrary code during deserialization.
Long-Term Mitigation:
- Patch Management: Ensure that the
torch_musalibrary is updated to a version that addresses this vulnerability once a patch is available. - Security Training: Educate developers and users about the risks associated with unsafe deserialization and the importance of secure coding practices.
- Network Segmentation: Implement network segmentation to limit the spread of potential attacks.
5. Impact on European Cybersecurity Landscape
The impact of this vulnerability on the European cybersecurity landscape is significant due to the following reasons:
- Wide Adoption: The
torch_musalibrary may be widely adopted in various industries, including finance, healthcare, and government, increasing the potential attack surface. - Critical Infrastructure: Compromise of systems running this library could lead to disruptions in critical infrastructure and services.
- Data Breaches: The ability to execute arbitrary code can result in data breaches, leading to the loss of sensitive information and potential regulatory violations.
6. Technical Details for Security Professionals
Vulnerability Details:
- Vulnerable Functions:
compare_for_single_op()andnan_inf_track_for_single_op()intorch_musa.utils.compare_tool. - Unsafe Operation: Use of
pickle.load()on user-controlled file paths without validation.
Detection and Monitoring:
- Log Analysis: Monitor logs for unusual activity related to the deserialization of pickle files.
- Intrusion Detection Systems (IDS): Implement IDS to detect and alert on suspicious network traffic that may indicate an exploitation attempt.
- File Integrity Monitoring: Use file integrity monitoring tools to detect unauthorized changes to critical files.
Incident Response:
- Containment: Isolate affected systems to prevent further spread of the attack.
- Forensic Analysis: Conduct a thorough forensic analysis to determine the extent of the compromise and identify the attack vector.
- Remediation: Patch the vulnerability and restore affected systems to a secure state.
References:
By addressing this vulnerability promptly and implementing robust security measures, organizations can mitigate the risks associated with unsafe deserialization and protect their systems from potential attacks.