Improper Input ValidationWeakness · CWE-20

CVE-2025-3165

MEDIUM · 5.3 CVSS v3.1 Published 2025-04-03
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 classified as critical has been found in thu-pacman chitu 0.1.0. This affects the function torch.load of the file chitu/chitu/backend.py. The manipulation of the argument ckpt_path/quant_ckpt_dir leads to deserialization. An attack has to be approached locally.

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 chitu library uses torch.load with user-controllable paths (ckpt_path, quant_ckpt_dir) in chitu/chitu/backend.py, allowing loading of untrusted PyTorch checkpoint files. Since torch.load deserializes pickle objects by default, a malicious checkpoint can execute arbitrary code on the local system.

MitigationReplace torch.load calls with safer alternatives: use weights_only=True parameter (requires PyTorch 1.8+) to prevent arbitrary object deserialization, or migrate to SafeTensors format which does not use pickle and is designed for secure 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. Verify chitu library is installed
    Run 'pip show chitu' or 'pip list | grep -i chitu' to confirm the library is present in your Python environment
    Affected if The chitu library is installed and being used in your project
  2. Locate the vulnerable backend.py file
    Find the chitu/chitu/backend.py file in your Python environment or project directory (use 'python -c "import chitu; print(chitu.__file__)"' to locate the package)
    Affected if The file exists in your environment, indicating the vulnerable code is present
  3. Inspect torch.load calls in backend.py
    Open chitu/chitu/backend.py and search for 'torch.load' calls, specifically those using 'ckpt_path' or 'quant_ckpt_dir' as parameters
    Affected if torch.load is called with user-controllable paths (ckpt_path or quant_ckpt_dir) in the code
  4. Check for weights_only parameter
    In backend.py, examine each torch.load call to see if it includes 'weights_only=True' as a parameter
    Affected if torch.load is called without weights_only=True, allowing arbitrary pickle deserialization
  5. Determine if your application uses vulnerable checkpoint loading
    Search your own code for imports from chitu and calls to functions that pass checkpoint paths (ckpt_path or quant_ckpt_dir) to the chitu backend
    Affected if Your code passes user-controllable or untrusted paths to chitu's checkpoint loading functions

You are affected if the chitu library is installed and your environment loads checkpoint files via torch.load without the weights_only=True parameter, enabling arbitrary code execution through malicious pickle objects.

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 torch.load calls with safer alternatives: use weights_only=True parameter (requires PyTorch 1.8+) to prevent arbitrary object deserialization, or migrate to SafeTensors format which does not use pickle and is designed for secure loading.

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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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-2025-3165 in production — separate from our analysis above.

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What this is

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