GHSA-83vm-p52w-f9pw MEDIUM pip/vllm

CVE: CVE-2026-44223

Summary

The extract_hidden_states speculative decoding proposer in vLLM returns a tensor with an incorrect shape after the first decode step, causing a RuntimeError that crashes the EngineCore process. The crash is triggered when any request in the batch uses sampling penalty parameters (repetition_penalty, frequency_penalty, or presence_penalty).

A single request with a penalty parameter (e.g., "repetition_penalty": 1.1) is sufficient to crash the server. The crash is deterministic and immediate — no concurrency, race condition, or special workload is required.

Details

In vLLM v0.17.0, the extract_hidden_states proposer's propose() method returned sampled_token_ids.unsqueeze(-1), producing a tensor of shape (batch_size, 1).

In PR #37013 (first released in v0.18.0), the KV connector interface was refactored out of propose(). The return type changed from tuple[Tensor, KVConnectorOutput | None] to Tensor, and the .unsqueeze(-1) call was removed along with the KV connector output:

# Before (v0.17.0):
return sampled_token_ids.unsqueeze(-1), kv_connector_output  # shape (batch_size, 1)

# After (v0.18.0+):
return sampled_token_ids  # shape (batch_size, 2) after first decode step

The refactor missed that sampled_token_ids changed semantics between the first and subsequent decode steps. After the first decode step, the rejection sampler allocates its output as (batch_size, max_spec_len + 1). With num_speculative_tokens=1, this produces shape (batch_size, 2) instead of the expected (batch_size, 1), causing a broadcast shape mismatch during penalty application.

Impact

Any vLLM deployment between v0.18.0 and v0.19.1 (inclusive) configured with extract_hidden_states speculative decoding is affected. A single API request containing any penalty parameter immediately and permanently crashes the EngineCore process, resulting in complete loss of service avai

📌 来源: GitHub-Advisory | 🆔 CVE-2026-44223 | 📅 2026-05-06