vLLM is an inference and serving engine for large language models. Prior to 0.32.0, an authenticated caller can place forged shared-memory address and monotonic_id values in public multimodal features.kwargs_data. In scale-out deployments with shared-memory multimodal caching enabled, workers trust those values and pass attacker-selected bytes to pickle.loads(), allowing arbitrary Python execution even when insecure serialization is disabled. This issue is fixed in version 0.32.0.

Affected: PyPI: vllm

## Affected

- **Ecosystem / package:** pip / `vllm` - **Affected versions:** vLLM < 0.32.0.

## Summary

When `--mm-processor-cache-type shm` is enabled, vLLM's multimodal SHM cache represents a cached item with an `address` and `monotonic_id` pair and treats that pair as authority to dereference shared memory in the worker. A public scale-out request can supply its own multimodal `features.kwargs_data`, so an authenticated caller can forge an inner SHM carrier that points at attacker-controlled bytes already staged in the ring buffer. The worker then reaches `pickle.loads()` while deserializing the forged object.

This is reachable through ordinary public HTTP routes and does not require `VLLM_ALLOW_INSECURE_SERIALIZATION=1`. The live chain used `/v1/chat/completions/render` to obtain a valid feature envelope, `/v1/chat/completions` to stage attacker-chosen bytes into SHM, and `/inference/v1/generate` to submit the forged inner carrier.

## Affected code

Links pinned to the confirmed commit [`752a3a504485`](https://github.com/vllm-project/vllm/tree/752a3a504485790a2e8491cacbb35c137339ad34) (v0.25.1):

- [`vllm/distributed/device_communicators/shm_object_storage.py#L375-L400`](https://github.com/vllm-project/vllm/blob/752a3a504485790a2e8491cacbb35c137339ad34/vllm/distributed/device_communicators/shm_object_storage.py#L375-L400) — SHM object deserialization reaches `pickle.loads(serialized_data)` for byte objects. - [`vllm/multimodal/cache.py#L567-L581`](https://github.com/…

Affected: PyPI: vllm

vLLM is an inference and serving engine for large language models. Prior to 0.32.0, an authenticated caller can place forged shared-memory address and monotonic_id values in public multimodal features.kwargs_data. In scale-out deployments with shared-memory multimodal caching enabled, workers trust those values and pass attacker-selected bytes to pickle.loads(), allowing arbitrary Python execution even when insecure serialization is disabled. This issue is fixed in version 0.32.0.