Improper Input ValidationWeakness · CWE-20

CVE-2025-4701

MEDIUM · 5.3 CVSS v3.1 Published 2025-05-15
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
55/100
Remediation priority · Elevated
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
A vulnerability, which was classified as problematic, has been found in VITA-MLLM Freeze-Omni up to 20250421. This issue affects the function torch.load of the file models/utils.py. The manipulation of the argument path leads to deserialization. It is possible to launch the attack on the local host.

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

A deserialization vulnerability exists in VITA-MLLM Freeze-Omni's models/utils.py where the torch.load function processes a manipulable path argument. This allows an attacker with local access to load malicious serialized PyTorch model files, potentially executing arbitrary code through unsafe pickle deserialization.

MitigationReplace unsafe torch.load calls with torch.load(weights_only=True) where feasible, implement path allowlisting, and add cryptographic signature verification for model files before loading.

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
Local
Complexity
Low
Privileges
Low
User interaction
None
Scope
Unchanged
Confidentiality
Low
Integrity
Low
Availability
Low

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

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. Locate VITA-MLLM or Freeze-Omni installation
    Search for the project directory: find / -type d -name 'Freeze-Omni' 2>/dev/null or find / -type d -name 'VITA-MLLM' 2>/dev/null. Also check pip list for installed packages containing these names.
    Affected if The project is installed or present on the system
  2. Find the vulnerable models/utils.py file
    Within the VITA-MLLM or Freeze-Omni directory, locate models/utils.py. Use: find <project_path> -name 'utils.py' -path '*/models/*'
    Affected if The file models/utils.py exists in the project
  3. Inspect torch.load calls for unsafe deserialization
    Open models/utils.py and search for torch.load calls. Check if they use torch.load(path) without the weights_only=True parameter. Example vulnerable pattern: torch.load(model_path)
    Affected if torch.load is called without weights_only=True parameter, enabling arbitrary code execution via pickle
  4. Check if model paths are user-controllable
    Review the code around torch.load calls to determine if the path argument comes from external input, configuration files, or user-supplied values rather than hardcoded trusted paths.
    Affected if The path argument to torch.load can be influenced by an attacker (e.g., from config, CLI args, or external input)
  5. Verify file permissions on model directories
    Check who can write to directories containing model files: ls -la <project_path>/models/ and ls -la <project_path>/checkpoints/ or similar model storage directories.
    Affected if Model directories are writable by untrusted users, allowing injection of malicious model files

A user is affected if VITA-MLLM or Freeze-Omni is installed and models/utils.py contains torch.load calls without weights_only=True where the model path can be controlled by an attacker.

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 unsafe torch.load calls with torch.load(weights_only=True) where feasible, implement path allowlisting, and add cryptographic signature verification for model files before loading.

Have this fixed Scoped from the published advisory
  • Consultation4.0 h
  • Implementation8.0 h
  • Testing6.0 h
  • Review / QA4.0 h
22.0 hours of engineering $3,860
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Scan for this in your stack

Free · runs locally
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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-2025-4701 in production — separate from our analysis above.

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What this is

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