Unsafe Deserialization in keras.layers.TorchModuleWrapper.from_config

Summary

CVECVE-2026-12484
StatePUBLISHED
Assigner@huntr_ai
Source PriorityCVE Program / NVD first with legacy fallback
Published2026-07-19 20:16:28 UTC
Updated2026-07-20 15:16:34 UTC
DescriptionA vulnerability in keras-team/keras version 3.15.0 allows unsafe deserialization of attacker-controlled PyTorch pickle data through the public `keras.layers.TorchModuleWrapper.from_config` method. This method invokes `torch.load(..., weights_only=False)` without requiring an explicit unsafe opt-in, such as a `safe_mode=False` parameter. When called outside a `SafeModeScope(True)` context, the absence of an ambient safe mode state permits unsafe deserialization by default. This issue can lead to arbitrary code execution if untrusted Keras layer configurations are processed using this method. The vulnerability arises because the method does not enforce safe deserialization practices unless explicitly guarded by Keras safe mode.

Risk And Classification

Primary CVSS: v3.0 7.8 HIGH from [email protected]

CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

EPSS: 0.002040000 probability, percentile 0.105320000 (date 2026-07-20)

Problem Types: CWE-502 | CWE-502 CWE-502 Deserialization of Untrusted Data


VersionSourceTypeScoreSeverityVector
3.0[email protected]Secondary7.8HIGHCVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
3.0CNADECLARED7.8HIGHCVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

CVSS v3.0 Breakdown

Attack Vector
Local
Attack Complexity
Low
Privileges Required
None
User Interaction
Required
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Vendor Declared Affected Products

SourceVendorProductVersionPlatforms
CNA Keras-team Keras-team/keras affected unspecified latest custom Not specified

References

ReferenceSourceLinkTags
huntr.com/bounties/ab14df49-13b5-4442-b754-3189430bfa28 134c704f-9b21-4f2e-91b3-4a467353bcc0 huntr.com
CVE Program record CVE.ORG www.cve.org canonical
NVD vulnerability detail NVD nvd.nist.gov canonical, analysis

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