CVE-2022-42902 is a high-severity vulnerability affecting the Linaro Automated Validation Architecture (LAVA) prior to version 2022.10. The vulnerability arises from improper input sanitization in the lava_server component, specifically within the lavatable.py module. This flaw allows an anonymous attacker to execute arbitrary code dynamically on the server running the lava-server-gunicorn service. The root cause is classified under CWE-94 (Improper Control of Generation of Code), indicating that user-supplied input is not properly validated or sanitized before being executed as code. Exploitation requires no user interaction and can be performed remotely over the network (AV:N), with low attack complexity (AC:L) and only requires low privileges (PR:L). The vulnerability impacts confidentiality, integrity, and availability (all rated high), as arbitrary code execution can lead to full system compromise, data theft, or service disruption. Although no known exploits are currently reported in the wild, the high CVSS score of 8.8 reflects the critical nature of this vulnerability and the potential for severe impact if exploited. The lack of vendor or product details suggests that LAVA is a specialized tool used primarily in embedded systems testing and validation environments, often by organizations involved in hardware and software integration testing. Since the vulnerability affects a server component that may be exposed to untrusted networks, it presents a significant risk if the affected versions remain in use without patching or mitigation.

For European organizations, especially those involved in embedded systems development, hardware validation, or telecommunications, this vulnerability poses a significant risk. LAVA is commonly used in environments where automated testing of hardware and software integration is critical, including automotive, aerospace, and industrial control sectors prevalent in Europe. Successful exploitation could lead to unauthorized access to sensitive intellectual property, disruption of testing pipelines, and potential compromise of connected infrastructure. Given the high confidentiality, integrity, and availability impact, attackers could exfiltrate proprietary data, inject malicious code into testing workflows, or cause denial of service, thereby affecting operational continuity. The threat is particularly relevant for research institutions, technology manufacturers, and service providers that rely on LAVA for continuous integration and validation processes. Additionally, the ability for an anonymous user to execute code remotely increases the attack surface, especially if the lava-server-gunicorn service is exposed beyond secure internal networks.

Organizations should immediately verify if they are running LAVA versions prior to 2022.10 and plan for an upgrade to the latest patched release once available. In the absence of an official patch, implement strict network segmentation to restrict access to the lava-server-gunicorn service, limiting it to trusted internal hosts only. Employ application-layer firewalls or reverse proxies with input validation to filter and sanitize incoming requests to the lava-server. Conduct thorough code reviews and static analysis on any custom extensions or scripts interacting with lavatable.py to detect unsafe code execution patterns. Enable comprehensive logging and monitoring on the lava-server to detect anomalous activities indicative of exploitation attempts. Additionally, consider deploying runtime application self-protection (RASP) mechanisms or endpoint detection and response (EDR) tools on servers hosting LAVA to detect and prevent unauthorized code execution. Finally, educate development and operations teams about the risks of dynamic code execution vulnerabilities and enforce secure coding practices to prevent similar issues in custom integrations.