CVE-2025-1497 is a critical vulnerability classified under CWE-94 (Improper Control of Generation of Code, commonly known as Code Injection) affecting the MLJAR PlotAI product. PlotAI is a software tool that utilizes large language models (LLMs) to generate output, presumably for data visualization or AI-assisted plotting tasks. The vulnerability arises from the lack of validation or sanitization of the LLM-generated output before it is executed as Python code. This flaw allows an attacker to craft malicious input that, when processed by PlotAI, results in arbitrary Python code execution on the host system without any authentication or user interaction. The vendor has commented out the vulnerable code line in the software, effectively disabling the risky functionality by default. However, to use the software fully, users must manually uncomment this line, thereby knowingly accepting the risk of exploitation. The vendor has explicitly stated that no patch will be released to fix this vulnerability, leaving the responsibility for risk acceptance and mitigation to the users. The CVSS 4.0 base score of 9.3 reflects the critical nature of this vulnerability: it is remotely exploitable over the network, requires no privileges or user interaction, and can lead to full compromise of confidentiality, integrity, and availability of affected systems. No known exploits are currently reported in the wild, but the ease of exploitation and severity make it a significant threat once weaponized. The vulnerability affects version 0 of PlotAI, indicating it may be an early or initial release of the product.

For European organizations using MLJAR PlotAI, this vulnerability poses a severe risk. Successful exploitation can lead to remote code execution, enabling attackers to take full control of affected systems, steal sensitive data, manipulate or destroy data, and potentially pivot within internal networks. Given the critical CVSS score and the lack of vendor patching, organizations face a persistent threat if they enable the vulnerable functionality. This is particularly concerning for sectors with high reliance on AI and data analytics tools, such as finance, healthcare, research institutions, and critical infrastructure operators. The ability to execute arbitrary Python code remotely without authentication means attackers can deploy malware, ransomware, or establish persistent backdoors. The absence of a vendor patch increases the likelihood that attackers will develop exploits, especially as PlotAI adoption grows. Additionally, the requirement to uncomment the vulnerable line means some organizations may inadvertently expose themselves if they are unaware of the risk or the vendor's stance. The impact extends beyond individual systems to potentially compromise entire organizational environments, disrupt operations, and cause regulatory compliance issues under GDPR and other data protection laws.

Given the vendor will not release a patch, European organizations must adopt a multi-layered mitigation approach. First, avoid enabling the vulnerable functionality by not uncommenting the risky code line in PlotAI. If usage of this feature is unavoidable, isolate the PlotAI environment in a tightly controlled network segment with strict access controls and monitoring. Employ application whitelisting and runtime application self-protection (RASP) tools to detect and block unauthorized code execution. Regularly audit and monitor logs for suspicious activity related to PlotAI processes. Use containerization or sandboxing to limit the blast radius of potential exploitation. Additionally, implement strict input validation and output sanitization at any integration points where PlotAI outputs are consumed. Organizations should also consider alternative tools without such vulnerabilities or wait for a secure version before deploying PlotAI in production. Finally, maintain up-to-date endpoint detection and response (EDR) solutions to detect exploitation attempts and respond rapidly. Employee awareness and training about the risks of enabling unpatched vulnerable features are also critical.