MalwarePT: A Binary-Level Foundation Model for Malware Analysis

Automated malware analysis increasingly relies on machine learning, yet most existing methods remain task-specific and depend on handcrafted features or narrowly scoped models. Recent developments in binary-level foundation models suggest a path toward reusable program representations, but their...

Backdoor Channels Hidden in Latent Space: Cryptographic Undetectability in Modern Neural Networks

Recent cryptographic results establish that neural networks can be backdoored such that no efficient algorithm can distinguish them from a clean model. These guarantees, however, have been confined to stylised architectures of limited practical relevance, leaving open whether comparable...

Intel NPU Driver May 2026 Security Update

Intel has informed HP of potential vulnerabilities identified in the Intel® NPU Drivers which might allow escalation of privilege or denial of service. Intel is releasing software updates to mitigate these potential vulnerabilities. Intel has released updates to mitigate the potential...

EUVD-2026-29525

Improper conditions check in some firmware for some IntelR NPU Drivers within Ring 1: Device Drivers may allow a denial of service. Unprivileged software adversary with an authenticated user combined with a low complexity attack may enable denial of service. This result may potentially occur via...

EUVD-2026-29521

Incorrect default permissions for some IntelR NPU Driver software installers before version 32.0.100.4511 within Ring 3: User Applications may allow an escalation of privilege. Unprivileged software adversary with an authenticated user combined with a high complexity attack may enable escalation ...

Intel NPU Driver Advisory - Lenovo Support US

No description provided...

CVE-2026-20754

Improper conditions check in some firmware for some IntelR NPU Drivers within Ring 1: Device Drivers may allow a denial of service. Unprivileged software adversary with an authenticated user combined with a low complexity attack may enable denial of service. This result may potentially occur via...

CVE-2026-20718

Incorrect default permissions for some IntelR NPU Driver software installers before version 32.0.100.4511 within Ring 3: User Applications may allow an escalation of privilege. Unprivileged software adversary with an authenticated user combined with a high complexity attack may enable escalation ...

CVE-2026-20718

CVE-2026-20718 concerns incorrect default permissions in Intel NPU Driver installers prior to 32.0.100.4511. The issue, exploitable by a local attacker with an authenticated user and high attack complexity, may enable privilege escalation in Ring 3 (User Applications) and could impact confidentia...

CVE-2026-31217

The loadmodel function in the neuralmagictraining.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f 2024-07-21 allows arbitrary code execution. When a user supplies a directory path via the --model command-line argument, the function reads a module.py file from...

Convolutional-Neural-Networks for Deanonymisation of I2P Traffic

This study investigates the potential for deanonymizing services within the Invisible Internet Project I2P network through passive traffic analysis and machine learning techniques. The primary objective is to identify distinctive patterns in I2P traffic despite the encryption of its payload. To...

CVE-2026-31218

The loadmodel function in the neuralmagictraining.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f 2024-07-21 is vulnerable to insecure deserialization CWE-502. When loading a model state dictionary from a statedict.pt file via torch.load, the function does not...

CVE-2026-31218

The loadmodel function in the neuralmagictraining.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f 2024-07-21 is vulnerable to insecure deserialization CWE-502. When loading a model state dictionary from a statedict.pt file via torch.load, the function does not...

Information Exposure

org.springframework.ai, spring-ai-autoconfigure-model-transformers is vulnerable to information exposure. The vulnerability is due to improper isolation in a shared environment, which allows an attacker to access and retrieve the ONNX model used by the application...

Security Bulletin: IBM Maximo Application Suite - Monitor Component uses onnx-1.20.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl which is vulnerable to CVE-2026-28500.

Summary IBM Maximo Application Suite - Monitor Component uses onnx-1.20.1-cp311-cp311-manylinux227x8664.manylinux228x8664.whl which is vulnerable to CVE-2026-28500. This bulletin contains information addressing the vulnerability. Vulnerability Details CVEID:CVE-2026-28500 DESCRIPTION: Open Neural...

CVE-2026-40979

In Spring AI, having access to a shared environment can expose the ONNX model used by the application. Affected versions: Spring AI: 1.0.0 - 1.0.5 fixed in 1.0.6, 1.1.0 - 1.1.4 fixed in 1.1.5...

CVE-2026-40979

In Spring AI, having access to a shared environment can expose the ONNX model used by the application. Affected versions: Spring AI: 1.0.0 - 1.0.5 fixed in 1.0.6, 1.1.0 - 1.1.4 fixed in 1.1.5...

EUVD-2026-26012

In Spring AI, having access to a shared environment can expose the ONNX model used by the application. Affected versions: Spring AI: 1.0.0 - 1.0.5 fixed in 1.0.6, 1.1.0 - 1.1.4 fixed in 1.1.5...

VMware Spring AI 安全漏洞

VMware Spring AI is a development framework by the American company VMware, which integrates artificial intelligence and large language model capabilities into the Spring ecosystem. Versions 1.0.0 to 1.0.5, as well as 1.1.0 to 1.1.4 of VMware Spring AI, have security vulnerabilities. These...

TL-RL-FusionNet: An Adaptive and Efficient Reinforcement Learning-Driven Transfer Learning Framework for Detecting Evolving Ransomware Threats

Modern ransomware exhibits polymorphic and evasive behaviors by frequently modifying execution patterns to evade detection. This dynamic nature disrupts feature spaces and limits the effectiveness of static or predefined models. To address this challenge, we propose TL-RL-FusionNet, a reinforceme...