Which versions of Python are affected by CVE-2025-9906?

CVE-2025-9906 presents significant security risk, a insecure deserialization vulnerability rated CVSS 8.6.. A patch is available.

How to fix or mitigate CVE-2025-9906?

Within 30 days: Identify all affected systems and apply vendor patches as part of regular patch cycle. Restrict deserialization to trusted data sources and implement integrity checks.

Python CVE-2025-9906

Q: What is the CVSS score of CVE-2025-9906?

CVE-2025-9906 has a CVSS 4.0 base score of 8.6 (High). CVSS vector: CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:P/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:Y/R:A/V:X/RE:X/U:X. EPSS exploitation probability: 0.1%.

HIGH

Deserialization of Untrusted Data (CWE-502)

2025-09-19 cve-coordination@google.com

GHSA-36fq-jgmw-4r9c

Python RCE Deserialization Keras Red Hat

8.6

CVSS 4.0 · NVD

Severity by source

NVD PRIMARY

8.6 HIGH

CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:P/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:Y/R:A/V:X/RE:X/U:X

Red Hat

8.2 HIGH

qualitative

Primary rating from NVD.

CVSS VectorNVD

CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:P/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:Y/R:A/V:X/RE:X/U:X

Attack Vector

Local

Attack Complexity

Low

Privileges Required

Low

User Interaction

Scope

Lifecycle Timeline

Patch released

Mar 31, 2026 - 21:13 nvd

Patch available

Analysis Generated

Mar 28, 2026 - 19:13 vuln.today

CVE Published

Sep 19, 2025 - 09:15 nvd

HIGH 8.6

DescriptionCVE.org

The Keras Model.load_model method can be exploited to achieve arbitrary code execution, even with safe_mode=True.

One can create a specially crafted .keras model archive that, when loaded via Model.load_model, will trigger arbitrary code to be executed. This is achieved by crafting a special config.json (a file within the .keras archive) that will invoke keras.config.enable_unsafe_deserialization() to disable safe mode. Once safe mode is disable, one can use the Lambda layer feature of keras, which allows arbitrary Python code in the form of pickled code. Both can appear in the same archive. Simply the keras.config.enable_unsafe_deserialization() needs to appear first in the archive and the Lambda with arbitrary code needs to be second.

AnalysisAI

The Keras Model.load_model method can be exploited to achieve arbitrary code execution, even with safe_mode=True. Rated high severity (CVSS 8.6), this vulnerability is low attack complexity. No vendor patch available.

Technical ContextAI

This vulnerability is classified as Deserialization of Untrusted Data (CWE-502), which allows attackers to execute arbitrary code through malicious serialized objects. The Keras Model.load_model method can be exploited to achieve arbitrary code execution, even with safe_mode=True. One can create a specially crafted .keras model archive that, when loaded via Model.load_model, will trigger arbitrary code to be executed. This is achieved by crafting a special config.json (a file within the .keras archive) that will invoke keras.config.enable_unsafe_deserialization() to disable safe mode. Once safe mode is disable, one can use the Lambda layer feature of keras, which allows arbitrary Python code in the form of pickled code. Both can appear in the same archive. Simply the keras.config.enable_unsafe_deserialization() needs to appear first in the archive and the Lambda with arbitrary code needs to be second. Affected products include: Keras.

RemediationAI

No vendor patch is available at time of analysis. Monitor vendor advisories for updates. Avoid deserializing untrusted data. Use safe serialization formats (JSON). Implement integrity checks and type allowlists.