CVE-2026-22778 is a critical-severity (CVSS 9.8) CWE-532 vulnerability in vllm. EPSS puts its 30-day exploitation probability at 18.3% (97th percentile). A fix is available for vllm — see the affected versions and patch details below.
vLLM leaks a heap address when PIL throws an error
Exploitation Status
No confirmed exploitation observed yet
- CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
- A successful exploit gives an attacker total control of the affected component, not partial access.
- CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.
Exploitation and automatability from CISA’s SSVC triage for CVE-2026-22778.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
How urgent is this, really
Where this sits among everything scored
Real-World Exposure
vllmReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
Summary
A chain of vulnerabilities in vLLM allow Remote Code Execution (RCE):
- Info Leak - PIL error messages expose memory addresses, bypassing ASLR
- Heap Overflow - JPEG2000 decoder in OpenCV/FFmpeg has a heap overflow that lets us hijack code execution
Result: Send a malicious video URL to vLLM Completions or Invocations for a video model -> Execute arbitrary commands on the server
Completely default vLLM instance directly from pip, or docker, does not have authentication so "None" privileges are required, but even with non-default api-key enabled configuration this exploit is feasible through invocations route that allows payload to execute pre-auth.
Example heap target is provided, other heap targets can be exploited as well to achieve rce. Leak allows for simple ASLR bypass. Leak + heap overflow achieves RCE on versions prior to 0.14.1.
Deployments not serving a video model are not affected.
1. Vulnerability Overview
1.1 The Bug: JPEG2000 cdef Box Heap Overflow
The JPEG2000 decoder used by OpenCV (cv2) honors a cdef box that can remap color channels. When Y (luma) is mapped into the U (chroma) plane buffer, the decoder writes a large Y plane into the smaller U buffer, causing a heap overflow.
Root Cause
cdefallows channel remapping (e.g., Y→U, U→Y).- Y plane size:
W×H; U plane size:(W/2)×(H/2). - Overflow size =
W×H - (W/2×H/2)=0.75 × W × Hbytes.
Example (150×64)
- Y plane: 150×64 = 9,600 bytes
- U plane: 75×32 = 2,400 bytes
- Overflow: 7,200 bytes past the U buffer
1.2 Malicious cdef Box
Offset Size Field Value
0 4 Box Length 0x00000016 (22 bytes)
4 4 Box Type 'cdef'
8 2 N (channels) 0x0003
10 2 Channel 0 Cn 0x0000 (Y channel)
12 2 Channel 0 Typ 0x0000 (color)
14 2 Channel 0 Asoc 0x0002 (→ maps Y into U plane)
16 2 Channel 1 Cn 0x0001 (U channel)
18 2 Channel 1 Typ 0x0000 (color)
20 2 Channel 1 Asoc 0x0001 (→ maps U into Y plane)
22 2 Channel 2 Cn 0x0002 (V channel)
24 2 Channel 2 Typ 0x0000 (color)
26 2 Channel 2 Asoc 0x0003 (→ maps V plane)
Key control: Asoc=2 for channel 0 forces Y data into the U buffer, triggering the overflow.
Vulnerable Code Chain
1) Entry: vLLM accepts a remote video_url and downloads raw bytes
vLLM’s OpenAI-compatible API supports a video_url content part:
class VideoURL(TypedDict, total=False):
url: Required[str]
class ChatCompletionContentPartVideoParam(TypedDict, total=False):
video_url: Required[VideoURL]
type: Required[Literal["video_url"]]
Source: src/vllm/entrypoints/chat_utils.py.
When the URL is HTTP(S), vLLM downloads it as raw bytes and passes the bytes into the modality loader:
if url_spec.scheme.startswith("http"):
data = connection.get_bytes(url, timeout=fetch_timeout, allow_redirects=...)
return media_io.load_bytes(data)
Source: src/vllm/multimodal/utils.py (MediaConnector.load_from_url).
2) Decode: vLLM uses OpenCV (cv2) VideoCapture on an in-memory byte stream
The default video backend is OpenCV, and it constructs cv2.VideoCapture over a BytesIO buffer containing the downloaded bytes:
backend = cls().get_cv2_video_api()
cap = cv2.VideoCapture(BytesIO(data), backend, [])
if not cap.isOpened():
raise ValueError("Could not open video stream")
Source: src/vllm/multimodal/video.py (OpenCVVideoBackend.load_bytes).
The backend is selected from OpenCV’s stream-buffered backends registry:
import cv2.videoio_registry as vr
for backend in vr.getStreamBufferedBackends():
if vr.hasBackend(backend) and ...:
api_pref = backend
break
return api_pref
Source: src/vllm/multimodal/video.py (OpenCVVideoBackend.get_cv2_video_api).
Implication: vLLM is delegating container parsing + codec decode to OpenCV’s Video I/O stack (which, in typical builds, is backed by FFmpeg for MOV/MP4 and codecs like JPEG2000).
3) The actual overflow: Y (full-res) written into U (quarter-res)
When the decoder honors the remap and writes Y into the U-plane buffer, it writes too many bytes:
- Y plane bytes: (W \times H)
- U plane bytes: ((W/2) \times (H/2))
- Overflow bytes: (W \times H - (W/2 \times H/2) = 0.75 \times W \times H)
Concrete example tried (150×64):
- Y: (150 \times 64 = 9600) bytes
- U: (75 \times 32 = 2400) bytes
- Overflow: (9600 - 2400 = 7200) bytes past the end of the U allocation
This is a heap buffer overflow into whatever allocations follow the U-plane buffer in the decoder’s heap layout (structures, metadata, other buffers, etc.). The exact victims depend on build + runtime allocator layout.
The Exploit Chain
Vuln 1: PIL BytesIO Address Leak (ASLR Bypass)
When you send an invalid image to vLLM's multimodal endpoint, PIL throws an error like:
cannot identify image file <_io.BytesIO object at 0x7a95e299e750>
^^^^^^^^^^^^^^^^
LEAKED ADDRESS!
vLLM returns this error to the client, leaking a heap address. This address is ~10.33 GB before libc in memory. With this leak, we reduce ASLR from 4 billion guesses to ~8 guesses.
Vuln 2: JPEG2000 cdef Heap Overflow (RCE)
vLLM uses OpenCV (cv2) to decode videos. OpenCV bundles FFmpeg 5.1.x which has a heap overflow in the JPEG2000 decoder. The OpenCV is used for video decoding so if we build a video from JPEG2000 frames it will reach the vuln:
vLLM API Request to Completions/Invocation
↓
OpenCV cv2.VideoCapture()
↓
FFmpeg 5.1 (bundled in OpenCV)
↓
JPEG2000 decoder (libopenjp2)
↓
HEAP OVERFLOW via malicious "cdef" box
↓
Overwrite function pointer → RCE!
How the overflow works:
- JPEG2000 has a
cdefbox that remaps color channels - We remap Y (luma) into the U (chroma) buffer
- Y plane = 9,600 bytes, U plane = 2,400 bytes
- On small geometry like 150x64 pixel image we get 7,200 bytes overflow past the U buffer. We can grow that exponentially by making bigger images.
- This overwrites an
AVBufferstructure containing afree()function pointer. This could be any function pointer or other targets. - We set
free = system()andopaque = "command string" - When the buffer is freed →
system("our command")executes
vLLM Attack Surface
Affected Endpoints
Both multimodal endpoints are vulnerable:
POST /v1/chat/completions (with video_url in content)
POST /v1/invocations (with video_url in content)
Request Flow
1. Attacker sends request with video_url pointing to malicious .mov file
2. vLLM fetches the video from the URL
3. vLLM passes video bytes to cv2.VideoCapture()
4. OpenCV's bundled FFmpeg decodes JPEG2000 frames
5. Malicious cdef box triggers heap overflow
6. AVBuffer.free pointer overwritten with system()
7. When buffer is released → system("attacker command") executes
Versions Affected
| Component | Version | Notes |
|---|---|---|
| vLLM | >= 0.8.3, < 0.14.1 | Default config vulnerable when serving a video model |
| OpenCV (cv2) | 4.x with FFmpeg bundle | Bundled FFmpeg is vulnerable |
| FFmpeg | 5.1.x (bundled) | JPEG2000 cdef overflow |
| libopenjp2 | 2.x | Honors malicious cdef box |
Fixes
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | vllm | ≥ 0.8.3&&< 0.14.1 | 0.14.1pip install --upgrade 'vllm==0.14.1' |
Affected Products
vllmvllmDetection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for vllm, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update vllm to 0.14.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-22778 is resolved across your whole dependency graph.
Workarounds
Stop feeding it untrusted input: reject or quarantine files and payloads from unverified sources until you can upgrade, restrict accepted formats to the ones you actually need, and run the parsing or decoding step in a least-privileged sandbox or short-lived worker so a crash or corrupted read cannot reach the rest of the process.
How to detect CVE-2026-22778
A community-maintained Nuclei template exists for this CVE. You can scan for it directly:
nuclei -id cve-2026-22778 -u https://target- Template
- vLLM 0.8.3 - 0.14.0 - Information Disclosure
- Severity
- critical
- Impact
- Remote attackers can leak heap addresses, significantly reducing ASLR effectiveness and enabling further exploitation like remote code execution.
- Remediation
- Upgrade to version 0.14.1 or later.
Template by ProjectDiscovery nuclei-templates (kenlacroix), MIT licensed. View the full template. Scan only systems you are authorised to test.
Fixing This On Your OS
If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.
This vulnerability is rated Critical rather than Important because it allows unauthenticated remote code execution without requiring user interaction, ultimately leading to full compromise of the affected system. An attacker can provide a malicious video URL to a vulnerable vLLM inference endpoint, which causes the…
Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base, or stability.Source: Red Hat security advisory for CVE-2026-22778 (CC BY 4.0)
| Product | Fixed in | Advisory |
|---|---|---|
| Red Hat AI Inference Server 3.2 | rhaiis/vllm-cuda-rhel9:1772160593 | RHSA-2026:3461 |
| Red Hat AI Inference Server 3.2 | rhaiis/vllm-rocm-rhel9:1772160625 | RHSA-2026:3462 |
| Red Hat AI Inference Server 3.3 | rhaiis/vllm-spyre-rhel9:1782352919 | RHSA-2026:30087 |
| Red Hat AI Inference Server 3.3 | rhaiis/vllm-rocm-rhel9:1782353093 | RHSA-2026:30088 |
| Red Hat AI Inference Server 3.3 | rhaiis/vllm-cuda-rhel9:1782352847 | RHSA-2026:30089 |
| Red Hat OpenShift AI 2.25 | rhoai/odh-vllm-cpu-rhel9:1772093436 | RHSA-2026:3782 |
| Red Hat OpenShift AI 3.3 | rhoai/odh-vllm-cpu-rhel9:1778264363 | RHSA-2026:19712 |
| Red Hat OpenShift AI 3.3 | rhoai/odh-vllm-gaudi-rhel9:1770956034 | RHSA-2026:3713 |
Frequently Asked Questions
Is CVE-2026-22778 in your dependencies?
Find it across PyPI, including transitive dependencies.