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01010111 10110010 00101001 11000110 01101100 10011011 00010001 11100101 01000010 10101111
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Vllm logo [ WEBSITE ] [ VENDOR STATS ]
CVSS: 6.5 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H 🐛 CWE-770
👁️
Common Weakness Enumeration - Identifies the specific category of software weakness or flaw.

CVE-2026-34755

CVE-2026-34755 is a high-severity Denial of Service (DoS) vulnerability in vLLM, an inference and serving engine for large language models (LLMs).
📅 PUBLISHED: 2026-04-06 16:16 UTC 🔄 UPDATED: 2026-09-26 06:16 UTC
[ OFFICIAL PATCH DEPLOYED ↓ ] FIX: CONFIRMED — 3+ independent sources confirm fix
[ DEFENSE PATCH ↓ ]
💣 PoC: None
👁️
Proof of Concept - Indicates if functional exploit code is publicly available, drastically increasing the risk of immediate attacks.
🎯 EPSS: 0.46%
👁️
0.46% probability
11.6× above the median CVE
Tier: ELEVATED
30-day exploitation window · FIRST.org · updated daily
🥷 MITRE: T1499
👁️
MITRE ATT&CK Tactic - Describes the strategy hackers use to execute this attack.
Country: United States License: Open Source
Affected: Vllm — upgrade to patched release
CVSS VECTOR BREAKDOWN 6.5
AV: N Attack Vector Network
AC: L Attack Complexity Low
PR: L Privileges Required Low
UI: N User Interaction None
S: U Scope Unchanged
C: N Confidentiality None
I: N Integrity None
A: H Availability High
6.5
THREAT LEVEL
■ tracking this CVE ✓ independent patch confirmation ⧗ same-origin mirror (GHSA) ⚠ active exploitation verification policy →

Executive Summary

CVE-2026-34755 is a high-severity Denial of Service (DoS) vulnerability in vLLM, an inference and serving engine for large language models (LLMs). The flaw resides in the VideoMediaIO.load_base64() method, which processes video/jpeg data URLs. An attacker can send a single API request containing thousands of comma-separated base64-encoded JPEG frames, bypassing the num_frames parameter (default: 32) that is enforced in the load_bytes() code path. This leads to unbounded memory allocation, causing the server to crash with an Out-of-Memory (OOM) condition. The vulnerability affects versions 0.7.0 through 0.18.x and is patched in version 0.19.0. With a CVSS score of 6.5 (Medium), it poses a significant availability risk to vLLM deployments, especially those exposed to untrusted networks.

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Supply Chain & Package Security

vLLM is distributed as a Python package via PyPI (vllm). Organizations using vLLM should verify their installed version and update to 0.19.0 or later. The vulnerability is introduced in the source code and does not involve a compromised package, but the supply chain risk is that outdated or unpatched installations remain vulnerable. Users should ensure they are pulling from the official PyPI repository and verify package integrity via checksums.

CVSS Breakdown & Threat Level

  • CVSS Score: 6.5 (Medium)
  • Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
  • Attack Vector: Network (AV:N) – The vulnerability can be exploited remotely.
  • Attack Complexity: Low (AC:L) – No special conditions required.
  • Privileges Required: None (PR:N) – No authentication needed.
  • User Interaction: None (UI:N) – No user action required.
  • Scope: Unchanged (S:U) – The impact is confined to the vulnerable component.
  • Confidentiality Impact: None (C:N) – No data exposure.
  • Integrity Impact: None (I:N) – No data modification.
  • Availability Impact: High (A:H) – Server crash due to OOM.

Threat Level: High for availability. The vulnerability is easy to exploit with a single HTTP request, leading to complete service disruption. While no public exploit code exists, the attack vector is straightforward.

Deep Dive & Mechanics

The vulnerability is in the VideoMediaIO.load_base64() method in vllm/multimodal/media/video.py. This method processes video/jpeg data URLs, which are base64-encoded strings containing multiple JPEG frames separated by commas. The intended design is to limit the number of frames via the num_frames parameter (default: 32), but this limit is only enforced in the load_bytes() code path. In the load_base64() path, the code splits the data URL by commas and decodes all frames without any limit.

Attack Flow:

  1. An attacker crafts a single API request to a vLLM endpoint that accepts video/jpeg input.
  2. The request includes a data URL with thousands of comma-separated base64-encoded JPEG frames.
  3. The server calls load_base64(), which splits the string and decodes each frame into memory.
  4. Each decoded frame consumes memory (e.g., ~1 MB per 1080p JPEG). With thousands of frames, memory usage quickly exceeds available RAM.
  5. The server crashes with an OOM error, causing a denial of service.

Root Cause: Missing input validation in the load_base64() method. The num_frames parameter is not enforced, allowing an attacker to bypass the intended limit.

Vulnerable vs. Patched Code

Vulnerable Code (v0.7.0 - v0.18.x):

# vllm/multimodal/media/video.py
class VideoMediaIO:
    @staticmethod
    def load_base64(data_url: str) -> List[bytes]:
        # Split by comma to get individual frames
        frames = data_url.split(",")
        decoded_frames = []
        for frame in frames:
            # Decode base64 and append to list
            decoded_frames.append(base64.b64decode(frame))
        return decoded_frames

Patched Code (v0.19.0):

# vllm/multimodal/media/video.py
class VideoMediaIO:
    @staticmethod
    def load_base64(data_url: str, num_frames: int = 32) -> List[bytes]:
        # Split by comma to get individual frames
        frames = data_url.split(",")
        # Enforce frame count limit
        if len(frames) > num_frames:
            raise ValueError(f"Number of frames ({len(frames)}) exceeds limit ({num_frames})")
        decoded_frames = []
        for frame in frames:
            # Decode base64 and append to list
            decoded_frames.append(base64.b64decode(frame))
        return decoded_frames

Key Difference: The patched version adds a check that raises a ValueError if the number of frames exceeds num_frames, preventing unbounded memory allocation.

Exploitation & Lab Setup

Red Team (Offensive)

Prerequisites:

  • A target vLLM server (version 0.7.0 to 0.18.x) with an API endpoint that accepts video/jpeg input (e.g., /v1/chat/completions with multimodal support).
  • Python 3.8+ with requests library.

Exploit Script:

import requests
import base64

# Generate a single JPEG frame (1x1 pixel, minimal size)
def generate_jpeg_frame():
    # Minimal JPEG (1x1 pixel, white)
    jpeg_bytes = bytes([
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        0x3C, 0x2E, 0x33, 0x34, 0x32, 0xFF, 0xC0, 0x00, 0x0B, 0x08, 0x00, 0x01,
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{/* [Security Hash: 82B928EE857DBD8528E5A91E] */}
◈ SOURCE Analysis & enrichment: valtersit.com/cve/CVE-2026-34755/ · CVE data: NVD/MITRE (public domain) · © 2026 ValtersIT Hub
>_ SYSTEM_CORE: INTEL_ACTIVE
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