CVE-2026-22778: CWE-532: Insertion of Sensitive Information into Log File in vllm-project vllm
vLLM is an inference and serving engine for large language models (LLMs). From 0.8.3 to before 0.14.1, when an invalid image is sent to vLLM's multimodal endpoint, PIL throws an error. vLLM returns this error to the client, leaking a heap address. With this leak, we reduce ASLR from 4 billion guesses to ~8 guesses. This vulnerability can be chained a heap overflow with JPEG2000 decoder in OpenCV/FFmpeg to achieve remote code execution. This vulnerability is fixed in 0.14.1.
AI Analysis
Technical Summary
The vulnerability in vLLM (CVE-2026-22778) affects versions from 0.8.3 to before 0.14.1. When an invalid image is sent to the multimodal endpoint, the Python Imaging Library (PIL) throws an error that vLLM returns to the client, leaking a heap address. This information leak reduces the address space layout randomization (ASLR) entropy from approximately 4 billion guesses to about 8 guesses. This leak can be chained with a heap overflow vulnerability in the JPEG2000 decoder used by OpenCV/FFmpeg, enabling remote code execution. The vulnerability is classified under CWE-532 and CWE-209. Red Hat advisories confirm the vulnerability and note that it is fixed in vLLM version 0.14.1.
Potential Impact
The vulnerability allows an attacker to obtain a heap address leak from error messages returned by the vLLM multimodal endpoint. This significantly reduces the effectiveness of ASLR, facilitating exploitation of a separate heap overflow vulnerability in the JPEG2000 decoder of OpenCV/FFmpeg. Successful exploitation can lead to remote code execution with high impact on confidentiality, integrity, and availability. The CVSS v3.1 score is 9.8 (critical), reflecting network attack vector, no privileges required, no user interaction, and high impact on confidentiality, integrity, and availability.
Mitigation Recommendations
A fixed version of vLLM is available: version 0.14.1. Users should upgrade to vLLM 0.14.1 or later to remediate this vulnerability. No additional mitigations are indicated by the vendor advisories. Patch status is confirmed by Red Hat advisories linked in the vendor advisory content.
CVE-2026-22778: CWE-532: Insertion of Sensitive Information into Log File in vllm-project vllm
Description
vLLM is an inference and serving engine for large language models (LLMs). From 0.8.3 to before 0.14.1, when an invalid image is sent to vLLM's multimodal endpoint, PIL throws an error. vLLM returns this error to the client, leaking a heap address. With this leak, we reduce ASLR from 4 billion guesses to ~8 guesses. This vulnerability can be chained a heap overflow with JPEG2000 decoder in OpenCV/FFmpeg to achieve remote code execution. This vulnerability is fixed in 0.14.1.
CVSS v3.1
Score 9.8critical
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The vulnerability in vLLM (CVE-2026-22778) affects versions from 0.8.3 to before 0.14.1. When an invalid image is sent to the multimodal endpoint, the Python Imaging Library (PIL) throws an error that vLLM returns to the client, leaking a heap address. This information leak reduces the address space layout randomization (ASLR) entropy from approximately 4 billion guesses to about 8 guesses. This leak can be chained with a heap overflow vulnerability in the JPEG2000 decoder used by OpenCV/FFmpeg, enabling remote code execution. The vulnerability is classified under CWE-532 and CWE-209. Red Hat advisories confirm the vulnerability and note that it is fixed in vLLM version 0.14.1.
Potential Impact
The vulnerability allows an attacker to obtain a heap address leak from error messages returned by the vLLM multimodal endpoint. This significantly reduces the effectiveness of ASLR, facilitating exploitation of a separate heap overflow vulnerability in the JPEG2000 decoder of OpenCV/FFmpeg. Successful exploitation can lead to remote code execution with high impact on confidentiality, integrity, and availability. The CVSS v3.1 score is 9.8 (critical), reflecting network attack vector, no privileges required, no user interaction, and high impact on confidentiality, integrity, and availability.
Mitigation Recommendations
A fixed version of vLLM is available: version 0.14.1. Users should upgrade to vLLM 0.14.1 or later to remediate this vulnerability. No additional mitigations are indicated by the vendor advisories. Patch status is confirmed by Red Hat advisories linked in the vendor advisory content.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- GitHub_M
- Date Reserved
- 2026-01-09T18:27:19.388Z
- Cvss Version
- 3.1
- State
- PUBLISHED
- Vendor Advisory Urls
- [{"url":"https://access.redhat.com/security/cve/CVE-2026-22778","vendor":"Red Hat"},{"url":"https://access.redhat.com/errata/RHSA-2026:3461","vendor":"Red Hat"},{"url":"https://access.redhat.com/errata/RHSA-2026:3462","vendor":"Red Hat"},{"url":"https://access.redhat.com/errata/RHSA-2026:3782","vendor":"Red Hat"},{"url":"https://access.redhat.com/errata/RHSA-2026:19712","vendor":"Red Hat"},{"url":"https://access.redhat.com/errata/RHSA-2026:3713","vendor":"Red Hat"}]
Threat ID: 69813004f9fa50a62f63a39d
Added to database: 02/02/2026, 23:15:16 UTC
Last enriched: 07/21/2026, 19:12:01 UTC
Last updated: 09/10/2026, 19:36:52 UTC
Views: 1196
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