CyberRota Analysis
AI-GeneratedElasticsearch's native inference process is vulnerable due to improper validation of memory offsets in uploaded machine learning models, allowing users with model upload privileges to manipulate memory allocation. This can lead to heap corruption, potentially resulting in crashes and arbitrary code execution within the inference process. Organizations using Elasticsearch for machine learning should prioritize addressing this vulnerability to mitigate risks of exploitation.
Public Exploit Signal
A public exploit, PoC, GitHub repository or Metasploit reference was detected for this CVE.
Note: these links are listed for security research and verification purposes only.
Original NVD Description
The native inference process that Elasticsearch uses to evaluate uploaded machine learning models accepts a model operation that computes a memory address from an offset supplied inside the model, without validating that the offset stays within the bounds of the underlying storage. A user with the privileges required to upload and deploy a trained model can craft a model that reads and writes memory outside the intended allocation. The result is heap corruption that crashes the inference process, and, with sufficient control over the heap layout, could allow arbitrary code execution in the context of that process.