dbcve.org
KerasApplication

CVE-2026-12481

CRITICAL · 9.8 CVSS v3.1 Published 2026-07-03
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
Public exploit Remotely reachable No privileges Zero-click 7 weeks old

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 in keras-team/keras version 3.14.0 allows for arbitrary code execution due to improper handling of deserialization in the `Lambda` layer. Specifically, the `_raise_for_lambda_deserialization()` function fails to enforce the safe-mode guard when `safe_mode` is set to `None`, which is the default value when `from_config()` is called outside of a `SafeModeScope` context. This logic error conflates `None` (unset/default-deny) with `False` (explicitly disabled), bypassing the guard and allowing attacker-controlled `marshal` bytecode to be deserialized. Affected call sites include `keras.layers.deserialize(config)`, `keras.models.clone_model(model)`, and any direct invocation of `Lambda.from_config(config)` without an enclosing `SafeModeScope(True)`. This vulnerability can be exploited to achieve arbitrary OS-level code execution in the context of the server or user process.

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

A logic error in keras 3.14.0's Lambda layer deserialization allows arbitrary code execution. The `_raise_for_lambda_deserialization()` function incorrectly treats `safe_mode=None` (the default) as equivalent to `safe_mode=False` (explicitly disabled), bypassing the security guard and enabling attacker-controlled marshal bytecode to be deserialized when calling `keras.layers.deserialize()`, `keras.models.clone_model()`, or `Lambda.from_config()` outside a SafeModeScope.

MitigationUpgrade to a patched version of keras that properly distinguishes between `None` and `False` for safe_mode, or ensure all deserialization calls occur within a SafeModeScope(True) context when processing untrusted configurations.

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
KerasApplication
Affected:= 3.14.0

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. Verify Keras version is 3.14.0
    Run 'pip show keras' or 'import keras; print(keras.__version__)' to check the installed version
    Affected if The installed version is exactly 3.14.0 (this specific version is affected; other versions may not have this flaw)
  2. Identify Lambda layer usage in deserialization
    Search codebases and configuration files for calls to keras.layers.deserialize(), keras.models.clone_model(), or Lambda.from_config() that process external or untrusted model configurations
    Affected if Any of these functions are called to deserialize Lambda layers from untrusted configs without SafeModeScope protection
  3. Check for SafeModeScope wrapping
    Inspect the code around deserialization calls to determine if they are wrapped with SafeModeScope(True) context manager
    Affected if Deserialization of Lambda layers occurs outside a SafeModeScope(True) context, meaning the safe_mode is implicitly None (treated as False by the buggy code)
  4. Inspect Lambda layer configurations for marshal data
    Review any loaded model configs or serialized Lambda layers for the 'function' or 'q' parameters that may contain marshal bytecode
    Affected if Lambda layer configurations contain serialized function data from untrusted sources that could be executed during deserialization

You are affected if you use Keras 3.14.0 and deserialize Lambda layers from untrusted configurations outside of a SafeModeScope(True) context, which allows the buggy safe_mode=None handling to be exploited for arbitrary code execution.

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

Upgrade to a patched version of keras that properly distinguishes between `None` and `False` for safe_mode, or ensure all deserialization calls occur within a SafeModeScope(True) context when processing untrusted configurations.

Fix this in Keras Scoped from the published advisory
  • Consultation1.0 h
  • Implementation2.0 h
  • Testing2.0 h
  • Review / QA1.0 h
6.0 hours of engineering $1,040
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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-2026-12481 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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