GHSA-x3m8-f7g5-qhm7 vLLM Allows Remote Code Execution via Mooncake Integration

• PyPI vllm: >= 0.6.5, < 0.8.0 → fixed in 0.8.0

Summary When vLLM is configured to use Mooncake, unsafe deserialization exposed directly over ZMQ/TCP will allow attackers to execute remote code on distributed hosts. Details 1. Pickle deserialization vulnerabilities are well documented. 2. The mooncake pipe is exposed over the network (by design to enable disaggregated prefilling across distributed environments) using ZMQ over TCP, greatly increasing exploitability. ~~Further, the mooncake integration opens these sockets listening on all interfaces on the host, meaning it can not be configured to only use a private, trusted network.~~ Only `sender_socket` and `receiver_ack` are allowed to be accessed publicly, while the data actually decompressed by `pickle.loads()` comes from recv_bytes. Its interface is defined as `self.receiver_socket.connect(f\"tcp://{d_host}:{d_rank_offset + 1}\")`, where `d_host` is `decode_host`, a locally defined address 192.168.0.139,from mooncake.json (https://github.com/kvcache-ai/Mooncake/blob/main/doc/en/vllm-integration-v0.2.md?plain=1#L36). 3. The root problem is `recv_tensor()` calls `_recv_impl` which passes the raw network bytes to `pickle.loads()`. Additionally, it does not appear that there are any controls (network, authentication, etc) to prevent arbitrary users from sending this payload to the affected service. Impact This is a remote code execution vulnerability impacting any deployments using Mooncake to distribute KV across distributed hosts. Remediation This issue is resolved by https://github.com/vllm-project/vllm/pull/14228