Dgl implements rpc server (startserver() in rpcserver.py) for supporting the RPC communications among different remote users over networks. It relies on pickle serialize and deserialize to pack and unpack network messages. The is a known risk in pickle deserialization functionality that can be used for remote code execution.
TBD.
When running DGL distributed training and inference (DistDGL) make sure you do not assign public IPs to any instance in the cluster.
Issue #7874
Pinji Chen (cpj24@mails.tsinghua.edu.cn) from NISL lab (https://netsec.ccert.edu.cn/about) at Tsinghua University
{ "nvd_published_at": null, "cwe_ids": [ "CWE-502" ], "severity": "HIGH", "github_reviewed": true, "github_reviewed_at": "2025-03-05T19:50:09Z" }