How severe is CVE-2025-9906?

No CVSS score has been assigned to CVE-2025-9906 yet. Review the advisory details and affected package list to assess your exposure.

Which packages are affected by CVE-2025-9906?

CVE-2025-9906 affects the following packages: keras (PyPI). Ecosystems affected: PyPI.

How do I fix CVE-2025-9906?

Update keras to 3.11.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2025-9906 is resolved across your whole dependency graph.

How do I detect CVE-2025-9906 in my PyPI dependencies?

Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for keras, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

How do I mitigate CVE-2025-9906 if there is no patch (or I can't update yet)?

Do not deserialise data from untrusted sources: where the format allows it, restrict deserialisation to an explicit allowlist of expected types, and prefer a data-only format (JSON, Protobuf) over one that can reconstruct arbitrary objects until you can upgrade.

Is CVE-2025-9906 actively exploited in the wild?

No public exploit code has been indexed for CVE-2025-9906 yet. This does not mean the vulnerability cannot be exploited — absence of public exploits does not imply safety. Apply the recommended fix and use O3 Security to monitor your exposure.

What is the EPSS score for CVE-2025-9906?

CVE-2025-9906 has an EPSS (Exploit Prediction Scoring System) score of 0.2%, placing it in the 10th percentile of all CVEs. EPSS is maintained by FIRST.org and estimates the probability that a vulnerability will be exploited in the wild within the next 30 days. This score indicates relatively lower exploitation probability, though the CVSS severity should still guide your patching priority.

What type of vulnerability is CVE-2025-9906?

CVE-2025-9906 is classified as Deserialization of Untrusted Data (CWE-502). This weakness type describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation. This is a high-impact weakness class that often enables remote code execution or data exposure.

When was CVE-2025-9906 published, and has it been updated?

CVE-2025-9906 was published on September 19, 2025 and was last updated on October 28, 2026. Advisory data evolves as severity scores, affected ranges, and exploit intelligence are revised — always check the latest version of the advisory before acting.

🐍 PyPI

Not in CISA KEV

CVE-2025-9906 — keras

Fix: keras-team/keras#21429

CVE-2025-9906 is a Deserialization of Untrusted Data vulnerability in keras. A fix is available for keras — see the affected versions and patch details below.

Arbitrary Code execution in Keras Safe Mode

Also known asGHSA-36fq-jgmw-4r9cPYSEC-2025-76

Published

Sep 19, 2025

Updated

Oct 28, 2026

Affected

1 pkg

Patched

1 / 1

Exploits

None indexed

Exploitation data as of Oct 30, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

A successful exploit gives an attacker total control of the affected component, not partial access.
CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for CVE-2025-9906.

EPSS Exploitation Probability

via FIRST.org ↗

0.2%probability of exploitation in next 30 days

Lower Risk+0.00%

Lower risk than most CVEs10th percentile — riskier than 10% of all scored CVEsHighest risk

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

Real-World Exposure

1 pkg affected

🐍keras

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Arbitrary Code Execution in Keras

Keras versions prior to 3.11.0 allow for arbitrary code execution when loading a crafted .keras model archive, even when safe_mode=True.

The issue arises because the archive’s config.json is parsed before layer deserialization. This can invoke keras.config.enable_unsafe_deserialization(), effectively disabling safe mode from within the loading process itself. An attacker can place this call first in the archive and then include a Lambda layer whose function is deserialized from a pickle, leading to the execution of attacker-controlled Python code as soon as a victim loads the model file.

Exploitation requires a user to open an untrusted model; no additional privileges are needed. The fix in version 3.11.0 enforces safe-mode semantics before reading any user-controlled configuration and prevents the toggling of unsafe deserialization via the config file.

Affected versions: < 3.11.0 Patched version: 3.11.0

It is recommended to upgrade to version 3.11.0 or later and to avoid opening untrusted model files.

Affected Packages

1 total 1 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`keras`	all versions	3.11.0`pip install --upgrade 'keras==3.11.0'`

Affected Products

1 product · 1 configurations

Application

keraskeras

≥ 3.0.0 && < 3.11.0

range

Detection & mitigation playbook

Open-source dependency

Detect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for keras, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update keras to 3.11.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2025-9906 is resolved across your whole dependency graph.
Workarounds
Do not deserialise data from untrusted sources: where the format allows it, restrict deserialisation to an explicit allowlist of expected types, and prefer a data-only format (JSON, Protobuf) over one that can reconstruct arbitrary objects until you can upgrade.

Fixing This On Your OS

If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.

Red HatImportant

Workaround published by Red Hat

Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.

Source: Red Hat security advisory for CVE-2025-9906 (CC BY 4.0)

Product	Fixed in	Advisory
Red Hat OpenShift AI 2.25	`rhoai/odh-modelmesh-runtime-adapter-rhel9:v2.25.1-1764825096`	RHSA-2025:23531

Frequently Asked Questions

### Arbitrary Code Execution in Keras Keras versions prior to 3.11.0 allow for arbitrary code execution when loading a crafted `.keras` model archive, even when `safe_mode=True`. The issue arises because the archive’s `config.json` is parsed before layer deserialization. This can invoke `keras.config.enable_unsafe_deserialization()`, effectively disabling safe mode from within the loading process itself. An attacker can place this call first in the archive and then include a `Lambda` layer whose function is deserialized from a pickle, leading to the execution of attacker-controlled Python co

O3 Security · Impact-Aware SCA

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