CVE-2024-0095
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 · uneditedNVIDIA Triton Inference Server for Linux and Windows contains a vulnerability where a user can inject forged logs and executable commands by injecting arbitrary data as a new log entry. A successful exploit of this vulnerability might lead to code execution, denial of service, escalation of privileges, information disclosure, and data tampering.
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 confidenceNVIDIA Triton Inference Server contains a log injection vulnerability where user-supplied input is not properly sanitized before being written to logs. An attacker can inject arbitrary data as new log entries, potentially including executable commands that could be interpreted when logs are viewed or processed by other systems. This can lead to code execution, denial of service, privilege escalation, information disclosure, or data tampering.
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>= 20.10, < 24.05CVSS 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
- High
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- High
- Integrity
- High
- Availability
- High
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/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 checksWork through these to decide whether this CVE applies to you.
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Identify Triton Inference Server installationRun 'tritonserver --version' or check the container image tag if running via Docker. If installed via pip, run 'pip show tritoninferenceserver' or check the installed package version.Affected if The installed version is >= 20.10 and < 24.05
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Verify the version is within affected rangeCompare the identified version number against the vulnerable range: 20.10 through 24.04 (inclusive). Versions 24.05 and later are patched.Affected if The version falls within >= 20.10 and < 24.05
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Confirm the service is accessible to untrusted usersCheck if Triton Inference Server HTTP/REST or gRPC endpoints are exposed to network or untrusted users. Review service binding configuration ('--http-port', '--grpc-port', '--metrics-port' flags or config).Affected if The service accepts user requests from untrusted sources, providing attack surface for log injection
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Review custom model repository pathsIf using custom model repositories, verify whether user-controlled model names or metadata could be passed to the server, as model names may appear in logs.Affected if User-supplied model names or data can reach the server and be logged without sanitization
You are affected if Triton Inference Server version is 20.10 or higher but lower than 24.05 and accepts user input that gets logged.
Generated from the published advisory. Verify against your own configuration.
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 · scoped24.05
Implement strict input validation and sanitization for all user-supplied data before logging. Use parameterized logging APIs or escape special characters to prevent log injection and command execution via log entries.
Triton Inference Server >= 24.05
- 1. Back up your current Triton Inference Server configuration and model repository
- 2. Stop the Triton Inference Server service
- 3. Upgrade Triton Inference Server to version 24.05 or later
- 4. Verify the upgrade by checking the server version: `tritonserver --version`
- 5. Test that models load correctly and inference works as expected
- 6. Monitor logs to confirm log injection vulnerability is resolved
Generated from the published advisory — verify against the referenced sources before acting.
- Consultation4.0 h
- Implementation8.0 h
- Testing6.0 h
- Review / QA4.0 h
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Scan for this in your stack
Free · runs locallyCheck whether your project pulls in CVE-2024-0095 — or any other known-vulnerable package — straight from your lock files. Free and open source; it runs locally and uploads nothing.
References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.
Primary sourcesPractitioner notes
ContributedPeer-ranked notes from engineers who’ve handled CVE-2024-0095 in production — separate from our analysis above.
The advisory tells you what broke. It rarely tells you what actually worked. If you’ve dealt with this one, that detail is what the next engineer is searching for.
- The version that genuinely resolved it — not the one the vendor claimed
- A config change or rule that shut the vector down
- A gotcha in the upgrade path that cost you an afternoon
No notes yet
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- 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
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