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AI agent vulnerability · vLLM

CVE-2026-12491: vLLM: image EXIF Rotation & PNG tRNS Transparency Not Normalized, Causing Mismatch Between Model Input and Expectations

mediumCVSS 3.1 4.8GHSA-8jr5-v98p-w75m

Summary Issue 1: EXIF orientation not normalized → The image orientation processed by the model differs from how humans view it, introducing interpretation bias. Issue 2: PNG tRNS not explicitly flattened before converting to RGB → After conversion, transparent/semi-transparent pixels are rendered unexpectedly, making otherwise subtle overlay elements visible and distorting the input content.

Published Jun 17, 2026 · Updated Jul 17, 2026

Affected packages

vllm

Ecosystem
PyPI
Affected
>= 0.11.0, < 0.24.0
Fixed in
0.24.0
Check
pip show vllm

Advisory details

From the GitHub Advisory Database (CC BY 4.0).

Summary

Issue 1: EXIF orientation not normalized → The image orientation processed by the model differs from how humans view it, introducing interpretation bias.

Issue 2: PNG tRNS not explicitly flattened before converting to RGB → After conversion, transparent/semi-transparent pixels are rendered unexpectedly, making otherwise subtle overlay elements visible and distorting the input content. (This attack is similar to AlphaDog: RGBA handling is already correct in vLLM, but since tRNS permits RGB images, the correct processing path isn’t taken.)

Issue 3 : Pillow only loads the first frame when loading APNG or GIF files.

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Root Cause

  • Rotation: After opening an image, ImageOps.exif_transpose is not called to normalize EXIF orientation.
  • Transparency: Only RGBA→RGB is flattened with a background; PNGs carrying `tRNS` in `P`/`L`/`RGB + tRNS` and other non-RGBA modes take the image.convert("RGB") path, which implicitly discards/remaps transparency semantics.

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Affected Code

https://github.com/vllm-project/vllm/blob/16b37f3119918c1e5a39f303e0d0892c65c07a90/vllm/multimodal/image.py#L77-L84

https://github.com/vllm-project/vllm/blob/16b37f3119918c1e5a39f303e0d0892c65c07a90/vllm/multimodal/image.py#L37-L43

https://github.com/vllm-project/vllm/blob/16b37f3119918c1e5a39f303e0d0892c65c07a90/vllm/multimodal/image.py#L26-L34 > Current state: ImageOps.exif_transpose is not used. (Although the rescale_image_size function (https://github.com/vllm-project/vllm/blob/main/vllm/multimodal/image.py#L14) exists and includes a transpose parameter, I’ve found that it doesn’t seem to be called anywhere outside the test directory.)

Call order: _convert_image_mode runs first; if the conditions are met, convert_image_mode is called. > > Issue: Only the “RGBA → RGB” path is explicitly flattened. P, L, or RGB with tRNS all fall back to image.convert("RGB"). For PNGs that include tRNS, convert("RGB") directly produces 24-bit RGB, leading to: > > * `P` mode: The transparent index becomes an actual RGB color (often black, white, or an undefined background), so transparency is lost. > * `L/LA` and `RGB + tRNS`: convert("RGB") doesn’t composite against a chosen background first, so elements that relied on transparency to be hidden or softened become solid.

Impact & Scope

  • Impact: Pixels the model sees can diverge from operator expectations (due to orientation or transparency handling), potentially altering downstream reasoning.
  • Scope: The image I/O and mode-conversion paths in vllm/multimodal/image.py. The existing RGBA→RGB flattening is correct; the issues center on missing EXIF normalization and non-RGBA `tRNS` not being explicitly composited.

Case

EXIF: http://qiniu.funxingzuo.top/exif_orient_180.jpg tRNS: http://qiniu.funxingzuo.top/hello.png

Fix

A fix for this vulnerability was merged here: https://github.com/vllm-project/vllm/pull/44974

Credited to kexinoh, russellb, jperezdealgaba, DarkLight1337.

References

How this page is made: the data panel comes from the GitHub Advisory Database, CISA’s KEV catalog, the NVD and FIRST EPSS, and updates twice a day. No analysis has been written for this entry yet. Methodology

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