Search

Use the Query Builder to create your own search query, or check out the documentation to learn the search syntax.

Search Examples

CVEs in KEV CVEs with EPSS >= 80% Crit. Microsoft High Apache SQL Injection (CWE-89) Linux Kernel High (CVSS 3.1) Apache Struts RCE (Remote Code Execution) XSS (CWE-79) Critical (CVSS 4.0) CVEs to check

Search Results (2 CVEs found)

Export CSV
CVE Vendors Products Updated CVSS v3.1
CVE-2026-12479 1 Keras-team 1 Keras 2026-06-23 N/A
A path traversal vulnerability exists in keras-team/keras version 3.14.0, specifically in the `DiskIOStore.make` method within the Keras 3 model saving and loading library. This vulnerability arises from the improper handling of user-provided layer names, which are used to construct directory paths without sanitizing for parent directory components (`..`). While forward slashes (`/`) are restricted in layer names, directory traversal sequences are not. This allows an attacker to craft a malicious Keras model that, when saved or loaded, can escape the intended temporary working directory and perform unauthorized file system operations, such as creating directories or writing files in arbitrary locations.
CVE-2026-11816 1 Keras-team 1 Keras 2026-06-12 8.1 High
Keras versions prior to 3.14.0 are vulnerable to a path traversal issue in the archive extraction utilities located in `keras/src/utils/file_utils.py`. The functions `filter_safe_tarinfos()` and `filter_safe_zipinfos()` validate archive member paths against the process current working directory (CWD) instead of the actual extraction destination. When the process runs with CWD set to `/`, which is common in Docker containers, CI/CD runners, and Jupyter environments, the validation boundary becomes the filesystem root, allowing traversal paths to bypass the security check. Additionally, the zip filter contains a bug that causes an `AttributeError` when a blocked entry is encountered, leading to incomplete extraction. Furthermore, Python 3.11 installations lack the `filter="data"` safety net, leaving them entirely reliant on the flawed CWD-based filter. Exploitation of this vulnerability can result in arbitrary file writes outside the intended extraction directory, enabling attackers to overwrite configuration files, inject malicious code, or corrupt machine learning datasets and pipelines.