vllm-project vLLM up to 0.30.x API AutoProcessor.from_pretrained code_revision eval injection
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 7.5 | $0-$5k | 1.61 |
Summary
A vulnerability described as critical has been identified in vllm-project vLLM up to 0.30.x. Impacted is the function AutoProcessor.from_pretrained of the component API. Such manipulation of the argument code_revision leads to eval injection.
This vulnerability is referenced as CVE-2026-114053. It is possible to launch the attack remotely. No exploit is available.
Upgrading the affected component is recommended.
Details
A vulnerability was found in vllm-project vLLM up to 0.30.x. It has been rated as critical. Affected by this issue is the function AutoProcessor.from_pretrained of the component API. The manipulation of the argument code_revision with an unknown input leads to a eval injection vulnerability. Using CWE to declare the problem leads to CWE-95. The product receives input from an upstream component, but it does not neutralize or incorrectly neutralizes code syntax before using the input in a dynamic evaluation call (e.g. "eval"). Impacted is confidentiality, integrity, and availability. CVE summarizes:
vLLM from 0.7.3 before 0.31.0 forwards the request-supplied mm_processor_kwargs.code_revision to Transformers AutoProcessor.from_pretrained, letting clients select which revision of a model's dynamic processor code is imported when trust_remote_code is enabled. An attacker controlling a revision in the served model repository can send a multimodal request to the unauthenticated /tokenize endpoint to execute arbitrary Python in the vLLM API process.
The advisory is available at github.com. This vulnerability is handled as CVE-2026-114053 since 10/20/2026. The exploitation is known to be easy. The attack may be launched remotely. No form of authentication is required for exploitation. Technical details are known, but there is no available exploit.
Upgrading to version 0.31.0 eliminates this vulnerability.
If you want to get best quality of vulnerability data, you may have to visit VulDB.
Product
Type
Vendor
Name
Version
- 0.1
- 0.2
- 0.3
- 0.4
- 0.5
- 0.6
- 0.7
- 0.8
- 0.9
- 0.10
- 0.11
- 0.12
- 0.13
- 0.14
- 0.15
- 0.16
- 0.17
- 0.18
- 0.19
- 0.20
- 0.21
- 0.22
- 0.23
- 0.24
- 0.25
- 0.26
- 0.27
- 0.28
- 0.29
- 0.30
Website
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒
CVSSv3
VulDB Meta Base Score: 7.7VulDB Meta Temp Score: 7.5
VulDB Base Score: 7.3
VulDB Temp Score: 7.0
VulDB Vector: 🔒
VulDB Reliability: 🔍
CNA Base Score: 8.1
CNA Vector (VulnCheck): 🔒
CVSSv2
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Eval injectionCWE: CWE-95 / CWE-94 / CWE-74
CAPEC: 🔒
ATT&CK: 🔒
Physical: No
Local: No
Remote: Yes
Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: UpgradeStatus: 🔍
0-Day Time: 🔒
Upgrade: vLLM 0.31.0
Timeline
10/20/2026 CVE reserved10/21/2026 Advisory disclosed
10/21/2026 VulDB entry created
10/21/2026 VulDB entry last update
Sources
Product: github.comAdvisory: github.com
Status: Confirmed
CVE: CVE-2026-114053 (🔒)
GCVE (CVE): GCVE-0-2026-114053
GCVE (VulDB): GCVE-100-423890
Entry
Created: 10/21/2026 04:26Changes: 10/21/2026 04:26 (79)
Complete: 🔍
Cache ID: 216::103
If you want to get best quality of vulnerability data, you may have to visit VulDB.
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