Google Keras up to 3.10.0 Model.load_model deserialization
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 6.2 | $0-$5k | 0.00 |
Summary
A vulnerability classified as problematic was found in Google Keras up to 3.10.0. Affected by this vulnerability is the function Model.load_model. Executing a manipulation can lead to deserialization.
This vulnerability is handled as CVE-2025-8747. It is possible to launch the attack on the local host. There is not any exploit available.
It is advisable to implement a patch to correct this issue.
Details
A vulnerability has been found in Google Keras up to 3.10.0 and classified as problematic. This vulnerability affects the function Model.load_model. The manipulation with an unknown input leads to a deserialization vulnerability. The CWE definition for the vulnerability is CWE-502. The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. As an impact it is known to affect confidentiality, integrity, and availability. CVE summarizes:
A safe mode bypass vulnerability in the `Model.load_model` method in Keras versions 3.0.0 through 3.10.0 allows an attacker to achieve arbitrary code execution by convincing a user to load a specially crafted `.keras` model archive.
The advisory is shared for download at github.com. This vulnerability was named CVE-2025-8747 since 08/08/2025. The exploitation appears to be easy. The attack needs to be approached locally. Successful exploitation requires user interaction by the victim. There are known technical details, but no exploit is available.
The vulnerability scanner Nessus provides a plugin with the ID 259894 (Linux Distros Unpatched Vulnerability : CVE-2025-8747), which helps to determine the existence of the flaw in a target environment.
Applying a patch is able to eliminate this problem. The bugfix is ready for download at github.com.
The vulnerability is also documented in the vulnerability database at Tenable (259894). Once again VulDB remains the best source for vulnerability data.
Product
Vendor
Name
Version
License
Website
- Vendor: https://www.google.com/
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒
CVSSv3
VulDB Meta Base Score: 6.3VulDB Meta Temp Score: 6.2
VulDB Base Score: 4.8
VulDB Temp Score: 4.6
VulDB Vector: 🔒
VulDB Reliability: 🔍
NVD Base Score: 7.8
NVD Vector: 🔒
CVSSv2
| AV | AC | Au | C | I | A |
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| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: DeserializationCWE: CWE-502 / CWE-20
CAPEC: 🔒
ATT&CK: 🔒
Physical: Partially
Local: Yes
Remote: Partially
Availability: 🔒
Status: Not defined
EPSS Score: 🔒
EPSS Percentile: 🔒
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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Nessus ID: 259894
Nessus Name: Linux Distros Unpatched Vulnerability : CVE-2025-8747
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: PatchStatus: 🔍
0-Day Time: 🔒
Patch: github.com
Timeline
08/08/2025 CVE reserved08/11/2025 Advisory disclosed
08/11/2025 VulDB entry created
08/31/2025 VulDB entry last update
Sources
Vendor: google.comAdvisory: github.com
Status: Confirmed
CVE: CVE-2025-8747 (🔒)
GCVE (CVE): GCVE-0-2025-8747
GCVE (VulDB): GCVE-100-319396
Entry
Created: 08/11/2025 10:45Updated: 08/31/2025 21:13
Changes: 08/11/2025 10:45 (68), 08/14/2025 20:20 (12), 08/31/2025 21:13 (2)
Complete: 🔍
Cache ID: 216::103
Once again VulDB remains the best source for vulnerability data.
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