Uncontrolled Resource ConsumptionWeakness · CWE-400

CVE-2026-47479

HIGH · 7.5 CVSS v3.1 Published 2026-07-14
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
84/100
Remediation priority · High
Remotely reachable No privileges Zero-click 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 Triton Inference Server for Linux contains a vulnerability where an attacker can 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 for Linux contains a vulnerability allowing an attacker to cause uncontrolled resource consumption, potentially leading to denial of service. The specific attack vector and affected code paths are not detailed in available documentation.

MitigationImplement network-level access controls to limit exposure of the Triton Inference Server, apply rate limiting on inference endpoints, and monitor for abnormal resource usage patterns. Await NVIDIA's official patch and apply it when available.

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

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 if Triton Inference Server is installed
    Run command: which tritonserver OR docker ps | grep triton OR ps aux | grep triton to find running instances
    Affected if Triton Inference Server is found running on the system
  2. Determine installed Triton version
    Run: tritonserver --version OR check docker image tag OR inspect /opt/triton/bin/tritonserver --version output
    Affected if Installed version matches or falls within an affected version range (compare to CVE published vulnerable versions)
  3. Verify network exposure of Triton service
    Check if port 8000 (default gRPC), 8001 (HTTP), or 8002 (metrics) is listening on non-loopback interfaces using: netstat -tlnp | grep -E '800[0-9]' OR ss -tlnp | grep -E '800[0-9]'
    Affected if Triton ports are bound to 0.0.0.0 or exposed externally without network access controls
  4. Monitor for abnormal resource consumption
    Observe CPU, memory, and network I/O for Triton processes using: top -p $(pgrep tritonserver) OR docker stats <container_id> while under inference load
    Affected if Resource usage spikes abnormally high or fails to scale down after requests complete
  5. Check for rate limiting on inference endpoints
    Review Triton configuration files and proxy/load balancer settings for rate-limit rules on inference endpoints (port 8000/8001)
    Affected if No rate limiting is configured and service is network-accessible

User is affected if Triton Inference Server is running with a vulnerable version exposed to network without rate limiting or access controls, and exhibiting abnormal resource consumption patterns.

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.

From vendor data
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Implement network-level access controls to limit exposure of the Triton Inference Server, apply rate limiting on inference endpoints, and monitor for abnormal resource usage patterns. Await NVIDIA's official patch and apply it when available.

Have this fixed Scoped from the published advisory
  • Consultation3.0 h
  • Implementation6.0 h
  • Testing3.0 h
  • Review / QA2.0 h
14.0 hours of engineering $2,490
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Scan for this in your stack

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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-2026-47479 in production — separate from our analysis above.

No notes yet

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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
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