fully-homomorphic-encryption

Google的FHE团队与多位合作者一起， 致力于 为Google和世界解锁全同态加密。 让它变得简单 让它变得快速 且可规模化 最初是一个C++转译器，现已演变为两个新库： HEIR 是一个新的开发平台和 编译器工具链，用于将现有模型转换为其FHE版本， 支持多种FHE方案 和后端。 Jaxite 是一个全同态加密 后端，针对TPU和GPU， 用JAX编写。 注意：寻找最初的"Google Transpiler"项目？请参见归档代码库...

CVE-2026-78684 vLLM before 0.27.0 Denial of Service via DeepStream Backend

vLLM before 0.27.0 fails to properly classify DeepStream as a GPU backend and omits pixel-limit enforcement in its decode path. Unauthenticated attackers can activate DeepStream at request time to initialize the process-wide GPU decode pool and submit video that bypasses resource controls, causin...

CVE-2026-68255

A flaw was found in the kernel. A malicious virtio-gpu backend can exploit an out-of-bounds read vulnerability in the drm/virtio component of the Linux kernel. By manipulating the Extended Display Identification Data EDID block index and advertising a large size, the backend can read beyond the...

Linux Distros Unpatched Vulnerability : CVE-2022-2832

The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - A flaw was found in Blender 3.3.0. A null pointer dereference exists in source/blender/gpu/opengl/glbackend.cc that may lead to loss of confidentiality and...

FIDESlib: a Fully-Fledged Open-Source FHE Library for Efficient CKKS on GPUs

Word-wise Fully Homomorphic Encryption FHE schemes, such as CKKS, are gaining significant traction due to their ability to provide post-quantum-resistant, privacy-preserving approximate computing; an especially desirable feature in Machine-Learning-as-a-Service MLaaS cloud-computing paradigms...

[SECURITY] Fedora 42 Update: llama-cpp-b4094-11.fc42

The main goal of llama.cpp is to run the LLaMA model using 4-bit integer quantization on a MacBook Plain C/C++ implementation without dependencies Apple silicon first-class citizen - optimized via ARM NEON, Accelerate and Metal frameworks AVX, AVX2 and AVX512 support for x86 architectures Mixed F...

[SECURITY] Fedora 40 Update: llama-cpp-b3561-1.fc40

The main goal of llama.cpp is to run the LLaMA model using 4-bit integer quantization on a MacBook Plain C/C++ implementation without dependencies Apple silicon first-class citizen - optimized via ARM NEON, Accelerate and Metal frameworks AVX, AVX2 and AVX512 support for x86 architectures Mixed F...