Triton Inference ServerApplication · Nvidia

CVE-2026-24215

HIGH · 7.5 CVSS v3.1 Published 2026-05-20
Fix available
A fix is available. Upgrade to 26.03 or later.
See remediation →
84/100
Remediation priority · High
Remotely reachable No privileges Zero-click

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 Triton Inference Server contains a vulnerability in the DALI backend, where an attacker could cause uncontrolled resource consumption. A successful exploit of this vulnerability might lead to denial of service.

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 Triton Inference Server's DALI backend contains an uncontrolled resource consumption vulnerability where an attacker can trigger excessive resource usage, leading to denial of service. The flaw allows malicious or malformed input processed through the DALI data loading pipeline to exhaust server resources.

MitigationImplement resource limits and quotas for the DALI backend, including memory and CPU constraints on inference requests. Consider input validation and request rate limiting at the inference server level. Apply vendor patches when available.

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
Triton Inference ServerApplication
Affected:< 26.03

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
Network
Complexity
Low
Privileges
None
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/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. Identify Triton Inference Server version
    Run 'tritonserver --version' or check the Docker image tag/container metadata. On Linux systems, also check '/opt/tritonserver/bin/tritonserver --version' if installed via apt/docker.
    Affected if The installed version is lower than 26.03 (e.g., 26.02, 26.01, 25.x, etc.)
  2. Confirm DALI backend is in use
    Examine Triton model repository configuration files (config.pbtxt) for any model using the DALI backend. Check for 'backend: dali' or 'dali' in model configuration files located in the model repository directory.
    Affected if Any model in the repository is configured to use the DALI backend (backend: "dali");
  3. Check for existing resource exhaustion
    Monitor system resources during DALI processing: run 'top' or 'htop' to check CPU usage, use 'free -m' for memory usage, and check 'dmesg' for OOM killer messages. Also review Triton server logs for error messages related to DALI or resource failures.
    Affected if Server shows abnormally high CPU or memory usage tied to DALI model inference, or logs contain DALI-related resource error messages;
  4. Verify if resource controls exist
    Review Triton server launch parameters or configuration for resource-related flags such as --rate-limit, --timeout, or resource_pools settings. Also check if external rate limiting (e.g., nginx, reverse proxy) is configured before Triton.
    Affected if No rate limiting, timeout controls, or resource quotas are configured for the DALI backend or for Triton server generally.

The environment is affected if Triton Inference Server version is below 26.03 AND the DALI backend is actively used, with no resource consumption controls (rate limiting, timeouts, quotas) currently in place.

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 26.03 or later
Fixed in 26.03
Interim mitigation

Implement resource limits and quotas for the DALI backend, including memory and CPU constraints on inference requests. Consider input validation and request rate limiting at the inference server level. Apply vendor patches when available.

Recommended fix Moderate confidence

NVIDIA Triton Inference Server version 26.03 or later

  1. 1. Identify the current installed version of NVIDIA Triton Inference Server by checking the container image tag or running the server with --version flag
  2. 2. Back up any existing models, configurations, and persistent state data
  3. 3. Stop the currently running Triton Inference Server instance
  4. 4. Pull or update to Triton Inference Server version 26.03 or later from NVIDIA's container registry (e.g., nvcr.io/nvidia/tritonserver:<version>-py3 where version >= 26.03)
  5. 5. Validate that the DALI backend is properly configured in the model repository
  6. 6. Start the upgraded Triton Inference Server and verify successful initialization
  7. 7. Test inference workloads to confirm normal operation

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

Fix this in Triton Inference Server Scoped from the published advisory
  • Consultation4.0 h
  • Implementation8.0 h
  • Testing6.0 h
  • Review / QA2.0 h
20.0 hours of engineering $3,500
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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-2026-24215 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
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  • Version or environment caveats, and links to real fixes
  • No weaponised exploit code, or anything meant to cause harm
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