OptimateApplication · Nebuly

CVE-2026-31217

CRITICAL · 9.8 CVSS v3.1 Published 2026-05-12
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
100/100
Remediation priority · Urgent
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
The _load_model() function in the neural_magic_training.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f (2024-07-21) allows arbitrary code execution. When a user supplies a directory path via the --model command-line argument, the function reads a module.py file from that directory and executes its contents directly using Python's exec() function. This design does not validate or sanitize the file's content, allowing an attacker who controls the input directory to execute arbitrary Python code in the context of the process running the script.

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 · high confidence

The _load_model() function in neural_magic_training.py reads a module.py file from a user-supplied directory path (via --model argument) and executes its contents using Python's exec() function without any validation or sanitization. This allows an attacker who controls the input directory to achieve arbitrary code execution in the context of the running process.

MitigationReplace the unsafe exec() call with a secure alternative such as importlib.util.spec_from_file_location() with restricted execution, or validate that the module.py contains only allowed/whitelisted code patterns before execution.

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
OptimateApplication
Affected:= 2024-07-21

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
High
Integrity
High
Availability
High

CVSS:3.1/AV:N/AC:L/PR:N/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 checks

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

  1. Check Nebuly Optimate version
    Run 'pip show nebuly-optimate' or check the package installation directory for version 2024-07-21
    Affected if The installed version is exactly 2024-07-21
  2. Locate neural_magic_training.py
    Search for the file in the Nebuly Optimate installation directory using 'find /path/to/nebuly -name neural_magic_training.py'
    Affected if The file exists and contains the _load_model() function using exec()
  3. Verify the vulnerable exec() pattern
    Inspect the _load_model() function and confirm it uses exec() to execute module.py contents without validation
    Affected if The code reads module.py from user-supplied path and passes it directly to exec()
  4. Check if --model argument is exposed
    Run 'python -m nebuly_optimate --help' or check CLI argument definitions for --model
    Affected if The --model argument is available and accepts a directory path

You are affected if Nebuly Optamate version 2024-07-21 is installed AND the --model argument feature is enabled, allowing arbitrary directory paths to be provided for loading modules.

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

Replace the unsafe exec() call with a secure alternative such as importlib.util.spec_from_file_location() with restricted execution, or validate that the module.py contains only allowed/whitelisted code patterns before execution.

Fix this in Optimate Scoped from the published advisory
  • Consultation4.0 h
  • Implementation8.0 h
  • Testing4.0 h
  • Review / QA3.0 h
19.0 hours of engineering $3,380
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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-2026-31217 in production — separate from our analysis above.

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What this is

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What belongs here
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  • Version or environment caveats, and links to real fixes
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