EUVD-2024-38936

Comprehensive Technical Analysis of EUVD-2024-38936

1. Vulnerability Assessment and Severity Evaluation

The vulnerability described in EUVD-2024-38936 pertains to a remote code execution (RCE) flaw in the streamlit-geospatial application. Specifically, the vis_params variable on line 115 in pages/10_🌍_Earth_Engine_Datasets.py accepts user input, which is subsequently used in the eval() function on line 126. This allows an attacker to execute arbitrary code remotely, leading to severe security implications.

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 that this vulnerability is critical due to its potential for remote code execution, which can lead to complete system compromise. The CVSS vector highlights that the attack vector is network-based (AV:N), requires low complexity (AC:L), does not need privileges (PR:N) or user interaction (UI:N), and has a high impact on confidentiality, integrity, and availability (C:H/I:H/A:H).

2. Potential Attack Vectors and Exploitation Methods

Attack Vectors:

• Network-Based Attack: An attacker can exploit this vulnerability over the network without needing physical access to the system.
• User Input Manipulation: The attacker can manipulate the vis_params variable to inject malicious code.

Exploitation Methods:

• Code Injection: By crafting a specially designed input for the vis_params variable, an attacker can inject and execute arbitrary Python code.
• Payload Delivery: The attacker can deliver payloads that perform various malicious actions, such as data exfiltration, system manipulation, or further propagation of malware.

3. Affected Systems and Software Versions

Affected Software:

• Product: streamlit-geospatial
• Vendor: opengeos
• Versions: All versions prior to commit c4f81d9616d40c60584e36abb15300853a66e489

Systems:

• Any system running the vulnerable versions of streamlit-geospatial is at risk. This includes servers, workstations, and cloud environments where the application is deployed.

4. Recommended Mitigation Strategies

Immediate Mitigation:

• Update Software: Ensure that all instances of streamlit-geospatial are updated to the version that includes commit c4f81d9616d40c60584e36abb15300853a66e489 or later.
• Input Validation: Implement strict input validation and sanitization for all user inputs to prevent code injection.
• Disable eval(): Avoid using the eval() function for processing user inputs. Use safer alternatives like ast.literal_eval() or other parsing methods.

Long-Term Mitigation:

• Code Review: Conduct thorough code reviews to identify and remediate similar vulnerabilities.
• Security Training: Provide security training for developers to educate them on secure coding practices and the risks associated with using functions like eval().
• Regular Updates: Ensure that all software dependencies are regularly updated to their latest versions to benefit from security patches.

5. Impact on European Cybersecurity Landscape

The presence of such a critical vulnerability in a widely-used geospatial application can have significant implications for the European cybersecurity landscape. Organizations relying on streamlit-geospatial for geospatial data analysis and visualization are at risk of data breaches, unauthorized access, and potential disruption of services. This underscores the importance of robust vulnerability management and the need for continuous monitoring and updating of software dependencies.

6. Technical Details for Security Professionals

Vulnerability Details:

• File: pages/10_🌍_Earth_Engine_Datasets.py
• Lines: 115 (input handling), 126 (eval() function usage)
• Commit Fix: c4f81d9616d40c60584e36abb15300853a66e489

References:

• GitHub Security Advisory
• Commit Fix
• Vulnerable Code Lines
• Vulnerable Code Lines

Additional Information:

• CVE ID: CVE-2024-41117
• EPSS Score: 2 (indicating a low likelihood of exploitation in the wild, but still a critical risk due to the nature of the vulnerability)

Conclusion: This vulnerability highlights the importance of secure coding practices and regular software updates. Organizations should prioritize updating their streamlit-geospatial installations and implement robust input validation mechanisms to mitigate the risk of remote code execution. Continuous monitoring and proactive vulnerability management are essential to safeguard against such critical threats.