Security Vulnerabilities
- CVEs Published In January 2026
The application discloses all used components, versions and license information to unauthenticated actors, giving attackers the opportunity to target known security vulnerabilities of used components.
Certain error messages returned by the application expose internal system details that should not be visible to end users, providing attackers with valuable reconnaissance information (like file paths, database errors, or software versions) that can be used to map the application's internal structure and discover other, more critical vulnerabilities.
Allocation of Resources Without Limits or Throttling in the HDF5 weight loading component in Google Keras 3.0.0 through 3.13.0 on all platforms allows a remote attacker to cause a Denial of Service (DoS) through memory exhaustion and a crash of the Python interpreter via a crafted .keras archive containing a valid model.weights.h5 file whose dataset declares an extremely large shape.
The device's passwords have not been adequately salted, making them vulnerable to password extraction attacks.
Improper handling of a URL parameter may allow attackers to execute code in a user's browser after login. This can lead to the extraction of sensitive data.
An attacker with limited permissions may still be able to write files to specific locations on the device, potentially leading to system manipulation.
An attacker with low privileges may be able to read files from specific directories on the device, potentially exposing sensitive information.
An attacker with low privileges may be able to trigger critical system functions such as reboot or factory reset without proper restrictions, potentially leading to service disruption or loss of configuration.
Improper input handling in a system endpoint may allow attackers to overload resources, causing a denial of service.
An attacker may exploit missing protection against clickjacking by tricking users into performing unintended actions through maliciously crafted web pages, leading to the extraction of sensitive data.