Keras
CVE-2025-9906
HIGH
GHSA-36fq-jgmw-4r9c
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A08:2025 - Software or Data Integrity Failures
ASVS 5.0
V1 - Encoding and Sanitization Safe deserialization, type allowlists
MITRE ATT&CK
2 techniques across 2 tactics: Execution, Initial Access The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Impact | CVSS score of 8.6 (HIGH). Attack characteristics: local attack vector, low complexity, low privileges required, user interaction required. EPSS exploitation probability: 0.08%. |
| Exploit ScenarioDerived | A local attacker with access to the system could execute arbitrary code through malicious serialized objects. |
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Alert meAnalysisAIv1 – Mar 28, 2026
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.
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.
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in pypi
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
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.
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- Exploit and PoC references, threat intelligence from 22 sources
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Severity by source
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/AU:Y/R:A
Primary rating from Vendor (google).
CVSS VectorVendor: google
Lifecycle Timeline
2DescriptionCVE.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.
Executive ViewAI
CVE-2025-9906 presents significant security risk, a insecure deserialization vulnerability rated CVSS 8.6. Insecure deserialization could allow attackers to execute arbitrary code by providing crafted serialized data. Organizations should apply vendor updates when available and consider compensating controls in the interim.
Apply vendor patch. If immediate patching is not feasible: (1) Restrict deserialization endpoints; (2) Implement integrity checks on serialized data; (3) Use type-safe alternatives.
Threat Intelligence Overview
NVD
CVE.org
EPSS
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Insecure deserialization occurs when an application converts serialized data (a stream of bytes representing an object's state) back into a living object without proper validation.
Remote Code Execution represents the critical moment when an attacker successfully runs arbitrary code on a target system without physical access.
Affected Products (CPE)CVE.org
The Keras Model.load_model method can be exploited to achieve arbitrary code execution, even with safe_mode=True. Rated
Deserialization of untrusted data in Keras 3.11.0 through 3.11.2 allows remote code execution when a victim loads a mali
A arbitrary code injection vulnerability in TensorFlow's Keras framework (<2.13) allows attackers to execute arbitrary c
Directory traversal in Keras through 3.11.3 allows an attacker who supplies a crafted tar archive to keras.utils.get_fil
Path traversal in Keras archive extraction utilities prior to version 3.14.0 allows remote attackers to write files outs
Memory-exhaustion denial of service in Google Keras 3.0.0 through 3.13.0 lets a remote attacker crash the Python interpr
Arbitrary local file disclosure in Keras 3.0.0 through 3.13.1 allows a remote attacker to read sensitive files from a vi
Keras Model.load_model fails to enforce safe_mode=True for the StringLookup layer's vocabulary path handling, so a malic
A safe mode bypass vulnerability in the `Model.load_model` method in Keras versions 3.0.0 through 3.10.0 allows an attac
An issue in keras 3.7.0 allows attackers to write arbitrary files to the user's machine via downloading a crafted tar fi
Exploit-DB