{"schema":"threatline.record/2","record":{"id":"CVE-2026-114050","aliases":["GHSA-p92p-rxj5-7p2x"],"summary":"vLLM: Forged multimodal UUID + P0/P1 processor-cache eviction drift: unauthenticated remote crash of the whole vLLM engine","details":"## Summary\n\nMultimodal content parts (`image_url`, `video_url`, `input_audio`, ...) accept a user-supplied `uuid` field that vLLM uses **verbatim as the item's cache identity** (`mm_hash`). The two frontend/engine processor caches (P0 \"sender\" cache in the API process, P1 \"receiver\" cache in the EngineCore process) are independent LRU caches whose evictions are **not synchronized**, and the P1 hit path performs **zero consistency validation** — it silently substitutes the cached item's tensor data for whatever the current request actually contains.\n\nA single unauthenticated client can exploit this to kill the entire engine, deterministically, with default server flags:\n\n1. **Seed**: send a small image with `uuid=\"U\"`. Both caches now map `U` to an item with **N_A** visual tokens (e.g. 4).\n2. **Drift**: send ~70 requests, each carrying a *unique* uuid, a max-size image, and an over-long text prompt. Each request is rejected with 400 — but **after** its image has been inserted into the P0 cache (insertion happens during chat rendering, before prompt-length validation), so these requests fill P0 **without ever reaching the engine/P1**. `U` is evicted from P0 only.\n3. **Kill**: send a *large* image with `uuid=\"U\"`. P0 misses → the image is freshly processed and the prompt is spliced with **N_B** (e.g. 2048+) placeholder tokens; the request carries full data to the engine, but P1 still has `U` → the engine **discards the fresh data and substitutes the stale N_A-row tensor**. The scheduler plans for N_B encoder slots while the worker merges N_A embeddings into N_B placeholders → `ValueError: Attempted to assign 4 = 4 multimodal tokens to 2048 placeholders` at `vllm/model_executor/models/utils.py:711` → uncaught in the EngineCore busy loop → `_send_engine_dead()` → the EngineCore process dies, every API server reports `EngineDeadError` and shuts down. `/health` never recovers; the deployment needs a full restart.\n\nVerified end-to-end on the official `vllm/vllm-openai:v0.29.0` image with Qwen2.5-VL-3B-Instruct, default configuration (no flags beyond `--served-model-name`/`--gpu-memory-utilization`): after 70 flood requests the kill request returned `500 EngineCore encountered an issue` and `/health` went dead permanently. The vulnerable code is byte-identical on `main` (post-0.29.0).\n\n## Details\n\n**1. The client-controlled `uuid` becomes the cache hash verbatim.** `vllm/entrypoints/chat_utils.py:1677` / `:1884-1886` read `part[\"uuid\"]` per content part and pass it through as `mm_uuids`. In `vllm/multimodal/processing/inputs.py:62-63`, when no `hf_processor_mm_kwargs` are present (the default for chat requests), the uuid string **is** the item hash — no content binding at all:\n\n```python\n# vllm/multimodal/processing/inputs.py:62-63\nelse:\n    hashes.append(uuid_item)        # client string used verbatim as mm_hash\n```\n\n**2. P0 insertion happens before request validation.** In the serving path, `render_chat_request` (`vllm/entrypoints/openai/chat_completion/serving.py:275`) runs full mm processing — `mm_processor.apply` (`vllm/renderers/base.py:759`) → `_cached_apply_hf_processor` → `_merge_mm_kwargs` → `cache.get_and_update_item` (`vllm/multimodal/processing/processor.py:1338`), which inserts the processed item into the P0 sender cache (default `mm_processor_cache_type=\"lru\"`, 4 GiB). Only afterwards does `get_max_tokens` (`vllm/entrypoints/serve/utils/api_utils.py:183-186`) reject over-long prompts with 400. **A request can therefore write to P0 while never reaching the engine** — the primitive that desynchronizes P0 from P1. (Public issue #43941 documented this same asymmetry for the opposite drift direction, which was later handled via `MultiModalCacheMissError`; the P0-miss/P1-hit direction below was never addressed.)\n\n**3. P1 substitutes cached data on hash hit with no consistency check.** In the EngineCore input thread, `preprocess_add_request` (`vllm/v1/engine/core.py:997-1000`) calls `mm_receiver_cache.get_and_update_features`, which only replaces `feature.data` (`vllm/multimodal/cache.py:673-690`) and keeps the request's own `mm_position` (placeholder layout). On a cache hit the receiver cache returns the stale item wholesale:\n\n```python\n# vllm/multimodal/cache.py:739-740  (MultiModalReceiverCache.get_and_update_item)\nif (cached_item := self._cache.get(mm_hash)) is not None:\n    return cached_item              # fresh data silently discarded; no size/modality check\n```\n\nOnly the opposite drift (P0 hit / P1 miss, `data=None`) is handled, via the retryable `MultiModalCacheMissError`. Nothing validates that the cached item's modality, shape, or token count matches the current request's placeholders.\n\n**4. The mismatch is fatal to the engine.** The scheduler plans encoder work from the request's (fresh) placeholder count N_B, while the worker gathers embeddings from the stale N_A-row tensor (encoder-cache hit under the same forged hash, or re-encoding the stale data — both yield N_A rows). `_merge_multimodal_embeddings` then raises:\n\n```python\n# vllm/model_executor/models/utils.py:703-714\ninputs_embeds[is_multimodal] = mm_embeds_flat.to(dtype=input_dtype)   # RuntimeError\n...\nraise ValueError(\n    f\"Attempted to assign {expr} = {num_actual_tokens} \"\n    f\"multimodal tokens to {num_expected_tokens} placeholders\") from e\n```\n\nThis exception is raised inside the worker's input preparation with no per-request containment, propagates to the EngineCore busy loop's top-level handler (`vllm/v1/engine/core.py:1372`), and triggers `_send_engine_dead()`. The API server's `output_handler` receives `EngineDeadError` (`vllm/v1/engine/async_llm.py:819`) and the whole process tree shuts down. (Issue #55546 independently reported this sink — \"one bad multimodal item kills the entire V1 engine tree\" — from an organically occurring stale cache entry; this report provides the missing deterministic, remote, single-attacker trigger.)\n\n**Cost of the attack.** With the default `mm_processor_cache_gb=4`, one max-size Qwen2.5-VL image (12845056 pixels) caches as ~77 MB, so ~56 flood requests suffice; we used 70. Flood requests are CPU-only image decodes (~0.3 s each here) and can be issued sequentially or concurrently; the total wall-clock cost of the kill was under one minute. Models with larger `max_pixels` fill the cache in even fewer requests. Note that issuing the flood with *successful* requests does not work — they would populate P1 as well; rejection after P0 insertion is essential, and the over-long-prompt 400 is one always-available way to get it (no size limits depend on non-default flags).\n\n\n## Impact\n\nAny unauthenticated client that can reach a multimodal vLLM endpoint (`/v1/chat/completions`, `/v1/responses`, etc. — all accept content-part `uuid`) can **deterministically crash the entire serving instance**: the EngineCore process dies, every in-flight request fails, and the API server exits; the deployment stays down until restarted. In data-parallel or multi-API-server deployments the blast radius extends to the whole engine group (cf. the DP8 outage in #55546). The attack requires no special privileges, no non-default server flags, no race conditions, and costs under a minute of sequential requests at default cache sizes.\n\nThis is distinct from the documented \"Multimodal Media UUID Security\" guidance in `docs/usage/security.md`, which covers only **integrity/confidentiality** consequences of uuid collisions (a caller silently receiving another caller's media). The guidance does not mention availability, and following it does not help: the attacker here deliberately collides with *their own* uuid, and the fatal element is the missing consistency check on the P1 hit path plus the unsynchronized eviction of the two caches.\n\n**Suggested remediation** (any one of these breaks the kill chain):\n\n1. On a P1 receiver-cache hit, validate the cached item against the request's `mm_position` (modality and expected embedding count); on mismatch, treat it as a miss (`MultiModalCacheMissError`) or reject the request — never substitute silently.\n2. Make the feature/placeholder count mismatch in `_merge_multimodal_embeddings` a per-request error instead of a fatal engine exception (also requested by #55546).\n3. Bind server-side cache identity to content even when a uuid is provided (e.g. `hash(content) + uuid`), eliminating forged-hash cache hits entirely.\n4. Synchronize P0/P1 evictions (the engine already pushes `invalidate` to P0 on cache-miss; eviction-direction sync would close the remaining drift).\n\nA public fix is available here: https://github.com/vllm-project/vllm/pull/57833","categories":["Libraries & packages"],"product":"vllm","vendor":"vllm-project","ecosystem":"pip","affected_ranges":[{"source":"GitHub Advisory Database","source_url":"https://github.com/advisories/GHSA-p92p-rxj5-7p2x","source_modified_at":"2026-10-23T20:43:45Z","fetched_at":"2026-10-23T21:10:45.942435Z","package":{"ecosystem":"pip","name":"vllm"},"range":"< 0.31.0"},{"source":"CVE 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0.31.0"},{"source":"OSV","source_url":"https://osv.dev/vulnerability/GHSA-p92p-rxj5-7p2x","source_modified_at":"2026-10-23T21:00:05.244406085Z","fetched_at":"2026-10-23T21:10:45.942435Z","package":{"name":"vllm","ecosystem":"PyPI","purl":"pkg:pypi/vllm"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"0.31.0"}]}],"versions":["0.0.1","0.1.0","0.1.1","0.1.2","0.1.3","0.1.4","0.1.5","0.1.6","0.1.7","0.10.0","0.10.1","0.10.1.1","0.10.2","0.11.0","0.11.1","0.11.2","0.12.0","0.13.0","0.14.0","0.14.1","0.15.0","0.15.1","0.16.0","0.17.0","0.17.1","0.18.0","0.18.1","0.19.0","0.19.1","0.2.0","0.2.1","0.2.1.post1","0.2.2","0.2.3","0.2.4","0.2.5","0.2.6","0.2.7","0.20.0","0.20.1","0.20.2","0.21.0","0.22.0","0.22.1","0.23.0","0.24.0","0.25.0","0.25.1","0.26.0","0.27.0"]}],"fixed_versions":[{"source":"GitHub Advisory 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record"},{"source":"OSV","source_url":"https://osv.dev/vulnerability/GHSA-p92p-rxj5-7p2x","source_modified_at":"2026-10-23T21:00:05.244406085Z","fetched_at":"2026-10-23T21:10:45.942435Z","package":{"name":"vllm","ecosystem":"PyPI","purl":"pkg:pypi/vllm"},"version":"0.31.0"}],"cvss":6.5,"severity":"Medium","kev":{"listed":false},"epss":{"probability":0.0017,"percentile":0.06054,"score_date":"2026-10-23"},"published_at":"2026-10-21T00:36:27.641Z","modified_at":"2026-10-23T21:00:05.244406085Z","provenance":[{"source":"GitHub Advisory Database","url":"https://github.com/advisories/GHSA-p92p-rxj5-7p2x","fetched_at":"2026-10-23T21:10:45.942435Z","source_modified_at":"2026-10-23T20:43:45Z"},{"source":"CVE List","url":"https://www.cve.org/CVERecord?id=CVE-2026-114050","fetched_at":"2026-10-23T18:45:31.882637Z","source_modified_at":"2026-10-21T15:50:53.921Z"},{"source":"GitHub Advisory 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Database"},{"url":"https://github.com/vllm-project/vllm/releases/tag/v0.31.0","source":"GitHub Advisory Database"},{"url":"https://nvd.nist.gov/vuln/detail/cve-2026-114050","source":"GitHub Advisory Database"},{"source":"CVE List","url":"https://www.vulncheck.com/advisories/vllm-before-0.31.0-remote-engine-crash-via-forged-multimodal-uuid","tags":["third-party-advisory"]},{"url":"https://github.com/advisories/GHSA-p92p-rxj5-7p2x","source":"GitHub Advisory Database"}],"locations":[],"motoko_assessment":{"status":"requires_architecture_review","automatic_remediation":false},"cve_state":"PUBLISHED","ssvc":{"exploitation":"none","automatable":"no","technical_impact":"partial","assessed_at":"2026-10-21T14:24:53.707222Z"},"classification":{"method":"product-first software-layer 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