CVE-2026-47155: Vllm VLLM's Artifact Pin Decay Allows Vulnerability
MODERATECVE-2026-47155 is a MODERATE (CVSS 6.5) vllm's artifact pin decay allows vulnerability (CWE-345: Insufficient Verification of Data Authenticity) affecting Vllm libraries in the PyPI ecosystem. The issue involves vllm's artifact pin decay allows pinned deployments to load unpinned code, weights, and processors. Remediation is available by upgrading affected packages to version 0.22.0.
CVE-2026-47155 at a Glance
Security Impact
CVSS: 6.5
The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:H/A:N).
How to Fix CVE-2026-47155
To remediate this vulnerability, upgrade all affected Vllm dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.
pip install vllm>=0.22.0
Run the following command in your project directory to verify that all resolved dependencies use the patched release:
pip show vllm
How to Check if You Are Affected
To determine whether your Python environment is affected by CVE-2026-47155, inspect your installed packages using pip:
pip show vllm
Analyze the terminal output to locate any version of Vllm in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 0.22.0), your application is affected.
Note: The pip show vllm command checks currently installed packages in your active Python environment.
Technical Details
Vulnerability Mechanism & Technical Analysis
This vulnerability is classified under CWE-345: Insufficient Verification of Data Authenticity, where the product does not sufficiently verify the origin or authenticity of data, in a way that causes it to accept invalid data. In Vllm, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.
Source Advisory Statement
CVE-2026-47155 Affected Vllm Versions
1 component(s)| Product / Package | Ecosystem | Affected Versions | Fixed Version |
|---|---|---|---|
|
vllm
|
PyPI |
< 0.22.0
|
0.22.0
|
References
Frequently Asked Questions
What is CVE-2026-47155?
Which Vllm versions are affected?
What version fixes CVE-2026-47155?
Is vllm affected?
What is the CVSS score of CVE-2026-47155?
What CWE is associated with CVE-2026-47155?
How can I check PyPI dependencies for CVE-2026-47155?
Machine-readable OSV JSON
OSV v1.5 Schema
{
"schema_version" : "1.4.0",
"id" : "GHSA-3ww4-5jv9-j5gm",
"modified" : "2026-07-17T16:21:38Z",
"published" : "2026-06-10T17:11:38Z",
"aliases" : [ "CVE-2026-47155" ],
"summary" : "vLLM's Artifact Pin Decay allows pinned deployments to load unpinned code, weights, and processors",
"details" : "### Summary\n\nvLLM's revision pinning controls do not consistently apply to all artifacts loaded for a model. A deployment that supplies `--revision` or `--code-revision` can still load dynamic code, GGUF files, image processors, retrieval side weights, or same-repository subfolder weights/config from an unpinned/default revision.\n\nThis is a supply-chain integrity issue for pinned vLLM deployments. Operators can believe they are serving a reviewed model revision while vLLM resolves behavior-affecting nested or sibling artifacts outside that reviewed revision.\n\n### Details\n\nThe expected invariant is:\n\n> When a vLLM operator supplies a model or code revision pin, every code, config, processor, weight file, side weight, and same-repository subfolder artifact loaded as part of that model should resolve under that pin unless vLLM exposes and enforces a separate explicit pin for that artifact.\n\nCurrent `main` was verified affected at commit `3795d7acf431980e62e738493f437ae2a51549da`.\n\nAffected source boundaries:\n\n- `vllm/model_executor/models/registry.py:1045-1051` and `:1058-1064`\n - `_try_resolve_transformers()` passes `revision=model_config.revision` and `trust_remote_code=model_config.trust_remote_code`, but omits `code_revision=model_config.code_revision` for external `auto_map` dynamic module imports.\n- `vllm/model_executor/model_loader/gguf_loader.py:58-60`\n - The direct-file GGUF form `repo/file.gguf` calls `hf_hub_download(repo_id=repo_id, filename=filename)` without passing `revision`.\n- `vllm/model_executor/models/roberta.py:203-209`\n - BGE-M3 secondary sparse and ColBERT side weights are declared with `revision=None`.\n- `vllm/model_executor/models/kimi_k25.py:111-114`\n - Kimi-K2.5 calls `cached_get_image_processor()` without passing `model_config.revision`.\n- `vllm/model_executor/models/kimi_audio.py:92-95`\n - Kimi-Audio loads Whisper config from the `whisper-large-v3` subfolder without a `revision` argument.\n- `vllm/model_executor/models/kimi_audio.py:425-430`\n - Kimi-Audio declares same-repository `whisper-large-v3` secondary weights with `revision=None`.\n- `vllm/model_executor/model_loader/default_loader.py:287-301`\n - The default loader preserves `model_config.revision` for the primary source, then consumes model-supplied secondary sources as declared.\n\nThe strongest example is Kimi-Audio: the primary `moonshotai/Kimi-Audio-7B-Instruct` weights preserve the configured model revision, but the same-repository `whisper-large-v3` audio tower config/weights do not. A pinned Kimi-Audio deployment can therefore load the Whisper subfolder outside the audited revision.\n\nThis report does not claim a `trust_remote_code=False` bypass, unauthenticated RCE, or real artifact compromise. The issue is improper propagation of explicit artifact pins across supported loader paths.\n\n### Impact\n\nAffected users are operators who pin vLLM model deployments to a reviewed Hugging Face revision for safety review, provenance, rollback, or reproducibility. The impact is that the pin does not reliably describe the full set of artifacts vLLM serves. Even when the operator selects an audited revision, vLLM can resolve behavior-affecting secondary artifacts from the repository default branch or another mutable ref.\n\nDepending on the model path, the unpinned artifact can be dynamic model code, a GGUF file, an image processor, retrieval side weights, or the same-repository Kimi-Audio Whisper subfolder weights/config.\n\nThis breaks the operational guarantee of a pinned deployment: \"serve the exact artifact set I reviewed.\" A later change to an unpinned secondary artifact can alter model behavior without changing the operator's configured revision, making review, rollback, incident response, and audit records unreliable.\n\n### Occurrences\n\n- `vllm/model_executor/models/kimi_k25.py` L111-L114 — Kimi-K2.5 loads its image processor with `cached_get_image_processor()` but does not pass `self.ctx.model_config.revision`. The processor can therefore resolve from the default repository revision even when the model deployment is pinned.\n- `vllm/model_executor/models/kimi_audio.py` L425-L430 — Kimi-Audio declares same-repository `whisper-large-v3` secondary weights with `revision=None`. A pinned Kimi-Audio deployment can therefore load the Whisper audio tower weights from an unpinned/default revision.\n- `vllm/model_executor/models/kimi_audio.py` L92-L95 — Kimi-Audio loads Whisper config from the same repository's `whisper-large-v3` subfolder without passing the top-level model revision. The config for this behavior-affecting subcomponent can be resolved outside the audited model revision.\n- `vllm/model_executor/models/registry.py` L1058-L1064 — The later dynamic model-class resolution repeats the same pin-decay pattern: it forwards `revision` and `trust_remote_code`, but omits `code_revision`. This means an operator-provided code pin is not enforced at the dynamic module loader boundary.\n- `vllm/model_executor/model_loader/gguf_loader.py` L58-L60 — The direct GGUF form `repo/file.gguf` calls `hf_hub_download(repo_id=repo_id, filename=filename)` without passing `model_config.revision`. A deployment that pins the model revision can therefore resolve this GGUF file from the repository default revision.\n- `vllm/model_executor/models/registry.py` L1045-L1051 — `try_get_class_from_dynamic_module()` is called for external `auto_map` config/model classes with `revision=model_config.revision`, but without forwarding `model_config.code_revision`. When `--code-revision` is set, this dynamic module resolution can still fall back to the default code revision instead of the audited code revision.\n- `vllm/model_executor/models/roberta.py` L203-L209 — `BgeM3EmbeddingModel` creates same-repository secondary sparse/ColBERT weight sources with `revision=None`. The primary model revision is not propagated to these side weights, so they can be downloaded outside the operator-selected model revision.\n\n### Fixes\n\nThis was fixed in: https://github.com/vllm-project/vllm/pull/42616\n\n___\n\nOriginally filed via huntr: https://huntr.com/bounties/3f1e24c0-87d2-4f6c-a705-820f380879ac.\n\nThe vLLM maintainer (Russell Bryant) redirected the report to the private GHSA channel. Offline proof bundle (`vllm_artifact_pin_decay_bundle_verify.py` + `bundle-verification-20260430T143506Z.json`) is available upon request.",
"severity" : [ {
"type" : "CVSS_V3",
"score" : "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:H/A:N"
} ],
"affected" : [ {
"package" : {
"ecosystem" : "PyPI",
"name" : "vllm"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "0"
}, {
"fixed" : "0.22.0"
} ]
} ]
} ],
"references" : [ {
"type" : "WEB",
"url" : "https://github.com/vllm-project/vllm/security/advisories/GHSA-3ww4-5jv9-j5gm"
}, {
"type" : "ADVISORY",
"url" : "https://nvd.nist.gov/vuln/detail/CVE-2026-47155"
}, {
"type" : "WEB",
"url" : "https://github.com/vllm-project/vllm/pull/42616"
}, {
"type" : "WEB",
"url" : "https://github.com/vllm-project/vllm/commit/d26a28ab033697f55a1414b5b0435de7cd6045b6"
}, {
"type" : "WEB",
"url" : "https://github.com/pypa/advisory-database/tree/main/vulns/vllm/PYSEC-2026-2301.yaml"
}, {
"type" : "PACKAGE",
"url" : "https://github.com/vllm-project/vllm"
}, {
"type" : "WEB",
"url" : "https://huntr.com/bounties/3f1e24c0-87d2-4f6c-a705-820f380879ac"
} ],
"database_specific" : {
"cwe_ids" : [ "CWE-345" ],
"severity" : "MODERATE",
"github_reviewed" : true,
"github_reviewed_at" : "2026-06-10T17:11:38Z",
"nvd_published_at" : "2026-06-22T23:16:30Z"
}
}