dbcve.org
TensorrtApplication · Nvidia

CVE-2026-24268

HIGH · 7.8 CVSS v3.1 Published 2026-07-14
Fix available
A fix is available. Upgrade to 11.0 or later.
See remediation →
81/100
Remediation priority · High
No privileges 5 weeks old

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
NVIDIA TensorRT contains a vulnerability where an attacker might cause a heap-based buffer overflow. A successful exploit of this vulnerability might lead to code execution.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · moderate confidence

NVIDIA TensorRT contains a heap-based buffer overflow vulnerability that could allow an attacker to achieve code execution through specially crafted inputs to the deep learning inference engine.

MitigationApply NVIDIA's security updates for TensorRT when available; until then, restrict TensorRT model processing to trusted inputs and minimize attack surface by running in isolated environments.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.

NVD · CPE data
TensorrtApplication
Affected:< 11.0

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Local
Complexity
Low
Privileges
None
User interaction
Required
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Detect if TensorRT is installed
    Check for TensorRT libraries or Python package. On Linux: 'dpkg -l | grep tensorrt' or 'pip show tensorrt'. On Windows: check NVIDIA TensorRT installation directory or 'pip show tensorrt'. Also check for libnvinfer*.so libraries in /usr/lib/x86_64-linux-gnu/ or /usr/local/cuda/lib64/.
    Affected if TensorRT package or libraries are found on the system
  2. Identify installed TensorRT version
    Run 'python -c "import tensorrt; print(tensorrt.__version__)"' or check via 'nvcc --version' and look for TensorRT version in nvidia-smi output. Also check package manager: 'dpkg -l | grep tensorrt' or 'rpm -qa | grep tensorrt'.
    Affected if Version returned is lower than 11.0 (e.g., 10.x, 9.x, 8.x, etc.)
  3. Verify TensorRT runtime is accessible
    Check that TensorRT shared libraries exist and are loadable: 'ldconfig -p | grep nvinfer' or attempt 'python -c "import tensorrt"' without error. Confirm CUDA runtime is available as TensorRT depends on it.
    Affected if TensorRT libraries load successfully and inference engine is functional
  4. Confirm model processing capability is active
    Check for any TensorRT engine files (.plan files) on the system or applications that use TensorRT for inference. Look for processes using TensorRT: 'ps aux | grep -i tensorrt' or check application logs mentioning TensorRT inference.
    Affected if TensorRT is actively used or configured for model inference with any inputs

User is affected if TensorRT is installed with a version lower than 11.0 and the inference engine processes inputs, since the heap-based buffer overflow can trigger during model processing with specially crafted inputs.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

dbcve · scoped
Upgrade available Upgrade to 11.0 or later
Fixed in 11.0
Interim mitigation

Apply NVIDIA's security updates for TensorRT when available; until then, restrict TensorRT model processing to trusted inputs and minimize attack surface by running in isolated environments.

Recommended fix Moderate confidence

TensorRT 11.0

  1. 1. Back up any existing TensorRT installations and configurations
  2. 2. Navigate to NVIDIA TensorRT downloads page (https://developer.nvidia.com/tensorrt)
  3. 3. Download TensorRT version 11.0 or later for your platform
  4. 4. Uninstall the current TensorRT version
  5. 5. Install the downloaded TensorRT 11.0+ package using the official installation guide
  6. 6. Update any PATH or environment variables to point to the new installation
  7. 7. Verify the installation by checking the TensorRT version with `trtexec --version` or importing tensorrt in Python

Generated from the published advisory — verify against the referenced sources before acting.

Fix this in Tensorrt Scoped from the published advisory
  • Consultation4.0 h
  • Implementation12.0 h
  • Testing6.0 h
  • Review / QA4.0 h
26.0 hours of engineering $4,580
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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2026-24268 in production — separate from our analysis above.

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What this is

A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.

What belongs here
  • Verified mitigations, workarounds, and config changes
  • Version or environment caveats, and links to real fixes
  • No weaponised exploit code, or anything meant to cause harm
  • No spam, self-promotion, credentials, or personal data