CVE-2026-12491
Essential information
- Published
- 17/06/2026 15:20
- Modified
- —
- Author
- The MITRE Corporation
- Creator
- The MITRE Corporation
- CVSS
- 4.8 MEDIUM (v3.1)
- CISA KEV
- No
- CWE
- CWE-115
- CVSS vector
-
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CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:L—
CVSS metrics
- Access vector
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- Access complexity
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- Authentication
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- Confidentiality impact
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- Integrity impact
- —
- Availability impact
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- Exploitability
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- Remediation level
- —
- Report confidence
- —
- Temporal score
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- Attack vector
- NETWORK
- Attack complexity
- HIGH
- Privileges required
- NONE
- User interaction
- NONE
- Scope
- UNCHANGED
- Confidentiality impact
- NONE
- Integrity impact
- LOW
- Availability impact
- LOW
- Exploit code maturity
- —
- Remediation level
- —
- Report confidence
- —
- Temporal score
- —
- Attack vector
- —
- Attack complexity
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- Attack requirements
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- Privileges required
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- User interaction
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- Confidentiality (V)
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- Confidentiality (S)
- —
- Integrity (V)
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- Integrity (S)
- —
- Availability (V)
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- Availability (S)
- —
- Exploit maturity
- —
Description
A flaw was found in vLLM, an open-source library for large language model inference. This vulnerability arises from improper handling of image metadata, specifically EXIF orientation and PNG transparency (tRNS) data, during image processing. When images are converted to RGB, transparency information may be implicitly discarded or remapped, leading to unexpected rendering of transparent pixels and distortion of input content. This can result in the model misinterpreting image content, potentially affecting the integrity of processed data.
NVD status
- NVD
- View on NVD