GitHub Advisoryadvisory · PyPI

GHSA-ph3r-5jfg-f84f vLLM: Mirrored multimodal IPC caches desync after a rejected request — a later request reusing the same media hash trips a receiver assertion in the engine core

MEDIUM Published 2026-10-06 Modified 2026-10-06 Official page ↗
Aliases
CVE-2026-105753
Ecosystem
PyPI
Packages
vllm
Severity
Moderate
CVSS vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weaknesses
CWE-617
Reviewed
2026-10-06

Affected packages

• PyPI vllm: < 0.28.0 → fixed in 0.28.0

Description

Affected • Ecosystem / package: pip / `vllm` • Affected versions: vLLM ≤ 0.25.1 (confirmed on 0.25.1, commit `752a3a504485`). The lower bound predates 0.25.1; maintainers can confirm how far back the mirrored sender/receiver cache protocol reaches. Summary vLLM's default multimodal cache (`mm_processor_cache_type="lru"`) mirrors state across two processes: the frontend (P0) holds only metadata (`MultiModalProcessorSenderCache`) while the engine core (P1) holds the real payload (`MultiModalReceiverCache`). The design invariant is that `get_and_update()` runs on P0 and P1 in lockstep for every request, so eviction order stays mirrored and P0 can answer "is this cached in P1?" without talking to P1. That invariant breaks when a request is rejected after P0 has rendered and hashed the multimodal input (populating the P0 cache) but before P1 receives the item — for example, an oversized chat prompt rejected on `max_model_len` *after* rendering. P0 now believes the media is cached while P1 never got it. A later request reusing the same media hash gets a P0 hit, so P0 sends `None` instead of the payload, and P1 — which has nothing cached — trips `assert mm_item is not None, f"Expected a cached item for {mm_hash=}"`. This is a remotely reachable, request-controlled cache-mirroring desync on the standard multimodal inference path. It requires only the default cache configuration. Affected code Links pinned to the confirmed commit `752a3a504485` (v0.25.1): • P0 metadata cache — `MultiModalProcessorSenderCache` at `vllm/multimodal/cache.py#L379`; `get_and_update_item` at `#L410-L421`, commit assertion at `#L418`. • P1 payload cache (the actual sink) — `MultiModalReceiverCache` at `vllm/multimodal/cache.py#L630`; `get_and_update_item` at `#L652-L663`, with the failing `assert mm_item is not None, f"Expected a cached item for {mm_hash=}"` at `#L660`. • Default `mm_processor_cache_type = "lru"` at `vllm/config/multimodal.py#L132`; dispatch in `vllm/multimodal/registry.py#L294-L307` (sender) and `#L322-L331` (receiver). The `processor_only`, disabled-caching, and `shm` paths are not affected. • Rejection-after-render window — rendering happens before length validation in `vllm/entrypoints/openai/chat_completion/serving.py#L206-L231` (`render_chat_request`), and the length check raises after the render in `vllm/entrypoints/serve/utils/api_utils.py#L171-L189`. • Cache-commit call site — `vllm/multimodal/processing/processor.py#L1347` (`_merge_mm_kwargs`) commits the P0 sender entry during render. • The separate stale-order eviction hang is already fixed via `vllm/utils/cache.py#L120-L121` (`LRUCache.touch()` guarding `if key in self:`) — a different mechanism that does not touch the sender/receiver commit-ordering protocol and does not remediate this assertion. The P1 receiver sink — the assertion that fires when P1 receives `None` for a hash it never cached: ```python vllm/multimodal/cache.py Lines 651-663 @override def get_and_update_item( self, mm_item: MultiModalKwargsItem | None, mm_hash: str, ) -> MultiModalKwargsItem: if (cached_item := self._cache.get(mm_hash)) is not None: return cached_item assert mm_item is not None, f"Expected a cached item for {mm_hash=}" self._cache[mm_hash] = mm_item return mm_item ``` The P0 sender — on a hit it drops the payload (returns `None`) and, on a miss during render, unconditionally commits the metadata entry with no rollback tied to admission: ```python vllm/multimodal/cache.py Lines 409-422 @override def get_and_update_item( self, mm_item: MultiModalProcessorCacheInItem, mm_hash: str, ) -> MultiModalProcessorCacheOutItem: if (cached_item := self._cache.get(mm_hash)) is not None: return None, cached_item.prompt_updates assert mm_item is not None, f"Expected a cached item for {mm_hash=}" self._cache[mm_hash] = MultiModalProcessorCacheItemMetadata(*mm_item) return mm_item ``` Impact A remote client submitting multimodal requests can poison a cache identity — render a media item successfully, then have that request rejected — so a later request reusing the same media hash fails on the P1 receiver assertion. This is an availability failure against a shared serving instance. No code execution, memory corruption, or data disclosure is claimed. On this revision the failure is scoped as a request-level preprocessing error (the engine core catches around `preprocess_add_request`); public reports show the same assertion cascading into further engine-loop assertions on other revisions. It applies to multimodal models running the default mirrored `lru` cache. Suggested Fix Two complementary changes: 1. Make the mirrored commit atomic with admission — insert into the P0 sender cache only after the request has passed all admission checks (length, limits) and P1 has acknowledged the item, or roll back the P0 insert on rejection. 2. Defense in depth — convert the P1 receiver `assert mm_item is not None` into a checked, request-scoped error (fetch-on-miss from P0) so a desync degrades a single request rather than asserting in the engine loop. The core of the rollback half: wrap the post-render length check so a `ValueError` rejection discards the P0 entries the render just committed, before re-raising. Add a `discard_sender_cache_item()` on the processor cache (no-op default, `pop` on the sender) and a `Renderer.discard_mm_cache_entries()` that walks a rendered request's `mm_hashes`: ```python vllm/entrypoints/openai/chat_completion/serving.py (_create_chat_completion) • max_tokens = get_max_tokens( • max_model_len, • ..., • truncate_prompt_tokens=request.truncate_prompt_tokens, • ) + try: + max_tokens = get_max_tokens( + max_model_len, + ..., + truncate_prompt_tokens=request.truncate_prompt_tokens, + ) + except ValueError: + for rendered_input in engine_inputs: + …

Related

Alias · CVE (1)

  • CVE-2026-105753 vLLM is an inference and serving engine for large language models. vulnerability

Weakness · CWE (1)

  • CWE-617 Reachable Assertion weakness

References