CVE-2024-5980 is a critical security vulnerability classified under CWE-22 (Improper Limitation of a Pathname to a Restricted Directory), affecting the lightning-ai/pytorch-lightning framework version 2.2.4. The flaw exists in the /v1/runs API endpoint when the LightningApp operates with the plugin_server enabled. Attackers can craft malicious tar.gz plugin archives containing files with path traversal sequences (e.g., '../') that bypass directory restrictions during extraction. This improper sanitization allows arbitrary files to be written to any location on the host file system, outside the intended plugin directory. Such unauthorized file writes can lead to remote code execution if attackers overwrite executable files or place malicious scripts in sensitive locations. The vulnerability requires no authentication or user interaction, making it remotely exploitable over the network. The CVSS v3.0 score of 9.1 reflects its criticality, with network attack vector, low attack complexity, no privileges required, and no user interaction needed. While no public exploits are known yet, the potential for severe impact on confidentiality, integrity, and availability is high. The vulnerability poses a significant risk to organizations deploying lightning-ai/pytorch-lightning in AI model training or deployment pipelines, especially when accepting plugins from untrusted sources. The lack of available patches at the time of disclosure necessitates immediate risk mitigation through operational controls and monitoring.

For European organizations, this vulnerability can lead to severe consequences including unauthorized modification or destruction of critical files, insertion of backdoors, and full system compromise. AI research institutions, cloud service providers, and enterprises using lightning-ai/pytorch-lightning for machine learning workflows may face disruption of services, data breaches, and intellectual property theft. The ability to execute arbitrary code remotely without authentication increases the risk of widespread exploitation, potentially affecting supply chains and AI model integrity. Given the increasing reliance on AI frameworks in Europe’s digital economy and research sectors, exploitation could undermine trust in AI deployments and cause regulatory compliance issues under GDPR if personal data is compromised. Additionally, organizations in critical infrastructure sectors leveraging AI could face operational outages or sabotage. The absence of known exploits currently provides a window for proactive defense, but the high severity demands urgent attention.

1. Immediately monitor official lightning-ai channels for patches or updates addressing CVE-2024-5980 and apply them as soon as they become available. 2. Until patched, disable the plugin_server feature or restrict its usage to trusted internal environments only. 3. Implement strict validation and sanitization of all plugin archives before deployment, including scanning for path traversal sequences and verifying archive contents against expected directory structures. 4. Employ network segmentation and firewall rules to limit access to the /v1/runs API endpoint to authorized users and systems only. 5. Use runtime application self-protection (RASP) or host-based intrusion detection systems (HIDS) to detect anomalous file writes or execution attempts. 6. Enforce least privilege principles on the file system permissions for the LightningApp process to minimize the impact of arbitrary file writes. 7. Conduct regular security audits and penetration tests focusing on plugin deployment mechanisms. 8. Educate development and DevOps teams about the risks of accepting untrusted plugins and the importance of secure plugin management.