CVE-2026-34755: CWE-770: Allocation of Resources Without Limits or Throttling in vllm-project vllm
vLLM is an inference and serving engine for large language models (LLMs). From 0.7.0 to before 0.19.0, the VideoMediaIO.load_base64() method at vllm/multimodal/media/video.py splits video/jpeg data URLs by comma to extract individual JPEG frames, but does not enforce a frame count limit. The num_frames parameter (default: 32), which is enforced by the load_bytes() code path, is completely bypassed in the video/jpeg base64 path. An attacker can send a single API request containing thousands of comma-separated base64-encoded JPEG frames, causing the server to decode all frames into memory and crash with OOM. This vulnerability is fixed in 0.19.0.
AI Analysis
Technical Summary
In vllm versions >=0.7.0 and <0.19.0, the VideoMediaIO.load_base64() method improperly handles video/jpeg base64 data URLs by splitting them on commas to extract JPEG frames without enforcing the num_frames limit parameter. This bypass allows an attacker to supply a single API request with thousands of base64-encoded JPEG frames, causing the server to decode all frames into memory, leading to an out-of-memory crash. The vulnerability is classified under CWE-770 (Allocation of Resources Without Limits or Throttling). It has a CVSS 3.1 base score of 6.5 (medium severity) with network attack vector, low attack complexity, low privileges required, no user interaction, and impacts availability only. The vulnerability is fixed in vllm version 0.19.0. Red Hat references this CVE in their advisories but does not explicitly state a patch for vllm itself; users should upgrade to vllm 0.19.0 or later to remediate.
Potential Impact
An attacker with the ability to send API requests to the vulnerable vllm server can cause a denial of service by exhausting server memory through a specially crafted request containing thousands of base64-encoded JPEG frames. This results in an out-of-memory crash, impacting availability. There is no impact on confidentiality or integrity according to the CVSS vector and description.
Mitigation Recommendations
A fix is available by upgrading to vllm version 0.19.0 or later, where the frame count limit is properly enforced in the load_base64() method. Since the vendor advisory does not indicate any temporary fixes or workarounds, users should apply this upgrade to remediate the vulnerability. Patch status is confirmed by the vendor advisory and CVE description.
CVE-2026-34755: CWE-770: Allocation of Resources Without Limits or Throttling in vllm-project vllm
Description
vLLM is an inference and serving engine for large language models (LLMs). From 0.7.0 to before 0.19.0, the VideoMediaIO.load_base64() method at vllm/multimodal/media/video.py splits video/jpeg data URLs by comma to extract individual JPEG frames, but does not enforce a frame count limit. The num_frames parameter (default: 32), which is enforced by the load_bytes() code path, is completely bypassed in the video/jpeg base64 path. An attacker can send a single API request containing thousands of comma-separated base64-encoded JPEG frames, causing the server to decode all frames into memory and crash with OOM. This vulnerability is fixed in 0.19.0.
CVSS v3.1
Score 6.5medium
Affected software
Run on your own infrastructure? Check whether these packages are installed with threat-finder — our free open-source scanner.
Weaknesses
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
In vllm versions >=0.7.0 and <0.19.0, the VideoMediaIO.load_base64() method improperly handles video/jpeg base64 data URLs by splitting them on commas to extract JPEG frames without enforcing the num_frames limit parameter. This bypass allows an attacker to supply a single API request with thousands of base64-encoded JPEG frames, causing the server to decode all frames into memory, leading to an out-of-memory crash. The vulnerability is classified under CWE-770 (Allocation of Resources Without Limits or Throttling). It has a CVSS 3.1 base score of 6.5 (medium severity) with network attack vector, low attack complexity, low privileges required, no user interaction, and impacts availability only. The vulnerability is fixed in vllm version 0.19.0. Red Hat references this CVE in their advisories but does not explicitly state a patch for vllm itself; users should upgrade to vllm 0.19.0 or later to remediate.
Potential Impact
An attacker with the ability to send API requests to the vulnerable vllm server can cause a denial of service by exhausting server memory through a specially crafted request containing thousands of base64-encoded JPEG frames. This results in an out-of-memory crash, impacting availability. There is no impact on confidentiality or integrity according to the CVSS vector and description.
Mitigation Recommendations
A fix is available by upgrading to vllm version 0.19.0 or later, where the frame count limit is properly enforced in the load_base64() method. Since the vendor advisory does not indicate any temporary fixes or workarounds, users should apply this upgrade to remediate the vulnerability. Patch status is confirmed by the vendor advisory and CVE description.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- GitHub_M
- Date Reserved
- 2026-03-30T19:17:10.225Z
- Cvss Version
- 3.1
- State
- PUBLISHED
- Remediation Level
- null
- Vendor Advisory Urls
- [{"url":"https://access.redhat.com/security/cve/CVE-2026-34755","vendor":"Red Hat"}]
Threat ID: 69d402cf0a160ebd92d2b84e
Added to database: 04/06/2026, 19:00:31 UTC
Last enriched: 07/15/2026, 13:20:14 UTC
Last updated: 07/27/2026, 02:47:46 UTC
Views: 131
Community Reviews
0 reviewsCrowdsource mitigation strategies, share intel context, and vote on the most helpful responses. Sign in to add your voice and help keep defenders ahead.
Want to contribute mitigation steps or threat intel context? Sign in or create an account to join the community discussion.
Actions
Updates to AI analysis require Pro Console access. Upgrade inside Console → Billing.
Need more coverage?
Upgrade to Pro Console for AI refresh and higher limits.
For incident response and remediation, OffSeq services can help resolve threats faster.
Latest Threats
Check if your credentials are on the dark web
Instant breach scanning across billions of leaked records. Free tier available.