CVE-2023-6656
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** UNSUPPORTED WHEN ASSIGNED ** A vulnerability was found in DeepFaceLab pretrained DF.wf.288res.384.92.72.22. It has been rated as critical. Affected by this issue is some unknown functionality of the file DFLIMG/DFLJPG.py. The manipulation leads to deserialization. The attack may be launched remotely. The complexity of an attack is rather high. The exploitation is known to be difficult. The identifier of this vulnerability is VDB-247364. NOTE: This vulnerability only affects products that are no longer supported by the maintainer.
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 confidenceA deserialization vulnerability exists in DeepFaceLab's DFLIMG/DFLJPG.py file used for processing pretrained model files (DF.wf.288res.384.92.72.22). The vulnerability allows manipulation of deserialized data through malicious or crafted model files, potentially leading to arbitrary code execution. The attack complexity is high and exploitation is known to be difficult.
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= df.wf.288res.384.92.72.22CVSS 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
- High
- Privileges
- None
- User interaction
- Required
- Scope
- Unchanged
- Confidentiality
- High
- Integrity
- High
- Availability
- High
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/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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Locate DeepFaceLab installationSearch for the DeepFaceLab installation directory, typically found in user home folders (e.g., ~/DeepFaceLab, C:\DeepFaceLab, or the folder where the tool was extracted)Affected if DeepFaceLab is not found on the system, then the environment is not affected
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Identify the vulnerable model fileLook for the pretrained model file named 'DF.wf.288res.384.92.72.22' in the models folder (commonly in /model/ or /workspace/ within the DeepFaceLab directory)Affected if The file DF.wf.288res.384.92.72.22 exists in the DeepFaceLab directory tree, indicating the affected component is present
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Check for DFLIMG/DFLJPG.pyLocate the DFLIMG or DFLJPG.py script file in the DeepFaceLab source code directory (typically in /core/ or /lib/ folder)Affected if The file DFLIMG/DFLJPG.py exists and is used for loading model files, confirming the vulnerable code path is present
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Verify active model processingCheck if the DeepFaceLab model training or conversion pipeline has been executed with the affected model file, which would trigger the deserialization of DF.wf.288res.384.92.72.22Affected if Logs, workspaces, or recent session data indicate the specific model was loaded or processed using the vulnerable deserialization routine
If DeepFaceLab with the DF.wf.288res.384.92.72.22 model file is present and has been used to process model data, the environment is likely affected by this deserialization vulnerability.
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.
From vendor dataSince DeepFaceLab is no longer supported, the recommended approach is to replace the affected component with actively maintained deepfake/face manipulation libraries that implement secure deserialization practices, or implement input validation and safe deserialization wrappers around the DFLJPG.py functionality if continued use is required.
- Consultation8.0 h
- Implementation16.0 h
- Testing8.0 h
- Review / QA4.0 h
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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 sourcesPractitioner notes
ContributedPeer-ranked notes from engineers who’ve handled CVE-2023-6656 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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- Version or environment caveats, and links to real fixes
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