EUVD-2024-47099

Comprehensive Technical Analysis of EUVD-2024-47099

1. Vulnerability Assessment and Severity Evaluation

The vulnerability described in EUVD-2024-47099 is a path traversal issue in the gaizhenbiao/chuanhuchatgpt software. This vulnerability arises from unsanitized input handling in multiple features, including user upload, directory creation, and template loading. The specific functions affected are load_chat_history in modules/models/base_model.py, get_history_names in utils.py, and load_template in utils.py.

Severity Evaluation:

• Base Score: 9.1
• Base Score Vector: CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H

The CVSS score of 9.1 indicates a critical vulnerability. The high impact on integrity (I:H) and availability (A:H) underscores the potential for remote code execution (RCE) and arbitrary file uploads, which can lead to significant security breaches.

2. Potential Attack Vectors and Exploitation Methods

Attack Vectors:

1. Arbitrary File Uploads: An attacker can exploit the load_chat_history function to upload malicious files, potentially leading to RCE.
2. Arbitrary Directory Creation: The get_history_names function can be manipulated to create directories arbitrarily, which can disrupt the file system and potentially lead to data corruption.
3. Information Leakage: The load_template function can be exploited to leak the first column of CSV files, which may contain sensitive information.

Exploitation Methods:

• Path Traversal: By manipulating input parameters, an attacker can traverse directories and access unauthorized files or directories.
• Remote Code Execution: Uploading malicious scripts or executables can lead to RCE, allowing the attacker to execute arbitrary commands on the server.
• Data Exfiltration: Leaking sensitive information from CSV files can provide attackers with valuable data for further attacks.

3. Affected Systems and Software Versions

Affected Software:

• gaizhenbiao/chuanhuchatgpt
• Versions: Unspecified versions prior to 20240918

Affected Systems:

• Any system running the vulnerable versions of gaizhenbiao/chuanhuchatgpt.
• Systems that handle user uploads, directory creation, and template loading using the affected functions.

4. Recommended Mitigation Strategies

Immediate Mitigation:

1. Patching: Apply the latest patches and updates provided by the vendor. The commit 952fc8c3cbacead858311747cddd4bedcb4721d7 addresses the vulnerability.
2. Input Sanitization: Ensure all user inputs are properly sanitized and validated before processing.
3. Access Controls: Implement strict access controls and permissions to limit the impact of potential exploits.

Long-Term Mitigation:

1. Code Review: Conduct thorough code reviews to identify and fix similar vulnerabilities.
2. Security Training: Provide security training for developers to understand the importance of input sanitization and secure coding practices.
3. Regular Audits: Perform regular security audits and vulnerability assessments to identify and mitigate potential threats.

5. Impact on European Cybersecurity Landscape

The vulnerability in gaizhenbiao/chuanhuchatgpt poses a significant risk to organizations using this software within the European Union. Given the critical nature of the vulnerability, it can lead to data breaches, unauthorized access, and potential disruption of services. This underscores the need for robust cybersecurity measures and continuous monitoring to protect against such threats.

6. Technical Details for Security Professionals

Vulnerable Functions:

• load_chat_history in modules/models/base_model.py
• get_history_names in utils.py
• load_template in utils.py

Technical Details:

• The vulnerability stems from improper sanitization of user inputs concatenated with directory paths using os.path.join.
• The load_chat_history function allows arbitrary file uploads, which can be exploited for RCE.
• The get_history_names function permits arbitrary directory creation, leading to potential data corruption.
• The load_template function can leak the first column of CSV files, exposing sensitive information.

References:

• Huntr Bounty
• GitHub Commit

Aliases:

• CVE-2024-5982

Assigner:

• @huntr_ai

EPSS:

• 1

ENISA ID Product:

• ed573925-a4b6-3d94-99d0-311f79309f78

ENISA ID Vendor:

• 95033a9f-bb4f-3225-ad47-60e2dacd7765

By addressing these vulnerabilities promptly and implementing robust security measures, organizations can mitigate the risks associated with this critical vulnerability.