CVE-2024-41117

Comprehensive Technical Analysis of CVE-2024-41117

1. Vulnerability Assessment and Severity Evaluation

CVE ID: CVE-2024-41117

Description: The vulnerability exists in the streamlit-geospatial application, specifically in the pages/10_🌍_Earth_Engine_Datasets.py file. Prior to commit c4f81d9616d40c60584e36abb15300853a66e489, the vis_params variable on line 115 takes user input, which is later used in the eval() function on line 126. This leads to remote code execution (RCE).

CVSS Score: 9.8

Severity Evaluation:

• Critical: The CVSS score of 9.8 indicates a critical vulnerability. The use of eval() with user input allows an attacker to execute arbitrary code, potentially leading to full system compromise.
• Impact: High. The vulnerability can be exploited to gain unauthorized access, execute malicious code, and compromise the integrity and confidentiality of the system.

2. Potential Attack Vectors and Exploitation Methods

Attack Vectors:

• Remote Code Execution (RCE): An attacker can craft malicious input for the vis_params variable, which is then evaluated by the eval() function. This allows the attacker to execute arbitrary Python code on the server.
• Injection Attacks: The vulnerability can be exploited through injection attacks, where malicious code is injected into the input parameters.

Exploitation Methods:

• Crafted Input: An attacker can send specially crafted input to the application, which will be evaluated by the eval() function. This can include commands to execute system-level operations, download and execute malware, or exfiltrate data.
• Automated Scripts: Attackers can use automated scripts to exploit the vulnerability, making it easier to target multiple instances of the application.

3. Affected Systems and Software Versions

Affected Systems:

• Any system running the streamlit-geospatial application prior to the commit c4f81d9616d40c60584e36abb15300853a66e489.

Software Versions:

• All versions of streamlit-geospatial before the fix was applied in commit c4f81d9616d40c60584e36abb15300853a66e489.

4. Recommended Mitigation Strategies

Immediate Actions:

• Update Software: Ensure that the streamlit-geospatial application is updated to include the fix from commit c4f81d9616d40c60584e36abb15300853a66e489.
• Input Validation: Implement strict input validation and sanitization to prevent malicious input from being processed by the eval() function.
• Avoid eval(): Refactor the code to avoid using the eval() function, especially with user input. Use safer alternatives like ast.literal_eval for evaluating literals.

Long-Term Strategies:

• Code Review: Conduct thorough code reviews to identify and mitigate similar vulnerabilities.
• Security Training: Provide security training for developers to avoid common pitfalls like using eval() with user input.
• Regular Updates: Ensure that all software dependencies are regularly updated to include the latest security patches.

5. Impact on Cybersecurity Landscape

Immediate Impact:

• Increased Risk: Organizations using the affected versions of streamlit-geospatial are at high risk of RCE attacks, which can lead to significant data breaches and system compromises.
• Reputation Damage: Successful exploitation can result in reputational damage and loss of trust from users and stakeholders.

Long-Term Impact:

• Enhanced Awareness: This vulnerability highlights the importance of secure coding practices and the risks associated with using functions like eval() with user input.
• Improved Security Posture: Organizations may adopt stricter security measures and more rigorous code review processes to prevent similar vulnerabilities in the future.

6. Technical Details for Security Professionals

Vulnerable Code:

# pages/10_🌍_Earth_Engine_Datasets.py
vis_params = user_input  # Line 115
eval(vis_params)  # Line 126

Fixed Code:

# pages/10_🌍_Earth_Engine_Datasets.py
vis_params = user_input  # Line 115
# Safe alternative to eval()
safe_params = ast.literal_eval(vis_params)  # Line 126

References:

• GitHub Commit Fix
• GitHub Security Advisory

Conclusion: CVE-2024-41117 is a critical vulnerability that underscores the importance of secure coding practices and input validation. Organizations should prioritize updating their systems and adopting robust security measures to mitigate the risk of similar vulnerabilities in the future.