BeDKD: Backdoor Defense Based on Dynamic Knowledge Distillation and Directional Mapping Modulator

Although existing backdoor defenses have gained success in mitigating backdoor attacks, they still face substantial challenges. In particular, most of them rely on large amounts of clean data to weaken the backdoor mapping but generally struggle with residual trigger effects, resulting in...

SUSE CVE-2025-38418

In the Linux kernel, the following vulnerability has been resolved: remoteproc: core: Release rproc-cleantable after rprocattach fails When rproc-state = RPROCDETACHED is attached to remote processor through rprocattach, if rprochandleresources returns failure, then the clean table should be...

UBUNTU-CVE-2025-38418

In the Linux kernel, the following vulnerability has been resolved: remoteproc: core: Release rproc-cleantable after rprocattach fails When rproc-state = RPROCDETACHED is attached to remote processor through rprocattach, if rprochandleresources returns failure, then the clean table should be...

CVE-2025-38418 remoteproc: core: Release rproc->clean_table after rproc_attach() fails

In the Linux kernel, the following vulnerability has been resolved: remoteproc: core: Release rproc-cleantable after rprocattach fails When rproc-state = RPROCDETACHED is attached to remote processor through rprocattach, if rprochandleresources returns failure, then the clean table should be...

CVE-2025-27056

Memory corruption during sub-system restart while processing clean-up to free up resources...

CVE-2025-27056

CVE-2025-27056 describes a memory corruption issue that occurs during subsystem restart cleanup in a Qualcomm component (kernel-related). The available records indicate a local attacker could trigger memory corruption during the restart/cleanup phase, with potential impact on confidentiality, int...

CVE-2025-27056 Use After Free in DSP Service

Memory corruption during sub-system restart while processing clean-up to free up resources...

PT-2025-27076 · WordPress · Samex - Clean

Name of the Vulnerable Software and Affected Versions: Samex - Clean, Minimal Shop WooCommerce WordPress Theme versions n/a through 2.6 Description: The issue affects the Samex - Clean, Minimal Shop WooCommerce WordPress Theme, allowing for PHP Local File Inclusion due to improper control of...

WordPress plugin Samex - Clean, Minimal Shop WooCommerce 安全漏洞

WordPress and WordPress plugin are both products of the WordPress Foundation.WordPress is a blogging platform developed using the PHP language. The platform supports setting up personal blog sites on servers with PHP and MySQL.WordPress plugin is an application plugin. A security vulnerability...

Blameless Users in a Clean Room: Defining Copyright Protection for Generative Models

Are there any conditions under which a generative model's outputs are guaranteed not to infringe the copyrights of its training data? This is the question of "provable copyright protection" first posed by Vyas, Kakade, and Barak ICML 2023. They define near access-freeness NAF and propose it as...

The vulnerability of the bch2_sb_clean_validate_late() function in the fs/bcachefs/sb-clean.c module of the bcachefs file system support in the Linux operating system allows a attacker to compromise the confidentiality, integrity, and accessibility of the protected information.

The vulnerability of the bch2sbcleanvalidatelate function in the fs/bcachefs/sb-clean.c module of the bcachefs file system support module in the Linux operating system is related to an uncontrolled resource consumption. Exploiting this vulnerability could allow an attacker to compromise the...

MEraser: an Effective Fingerprint Erasure Approach for Large Language Models

Large Language Models LLMs have become increasingly prevalent across various sectors, raising critical concerns about model ownership and intellectual property protection. Although backdoor-based fingerprinting has emerged as a promising solution for model authentication, effective attacks for...

InverTune: Removing Backdoors from Multimodal Contrastive Learning Models Via Trigger Inversion and Activation Tuning

Multimodal contrastive learning models like CLIP have demonstrated remarkable vision-language alignment capabilities, yet their vulnerability to backdoor attacks poses critical security risks. Attackers can implant latent triggers that persist through downstream tasks, enabling malicious control ...

When Forgetting Triggers Backdoors: a Clean Unlearning Attack

Machine unlearning has emerged as a key component in ensuring Right to be Forgotten, enabling the removal of specific data points from trained models. However, even when the unlearning is performed without poisoning the forget-set clean unlearning, it can be exploited for stealthy attacks that...

Screen Hijack: Visual Poisoning of VLM Agents in Mobile Environments

With the growing integration of vision-language models VLMs, mobile agents are now widely used for tasks like UI automation and camera-based user assistance. These agents are often fine-tuned on limited user-generated datasets, leaving them vulnerable to covert threats during the training process...

[SECURITY] Fedora 42 Update: python-django5-5.2.2-1.fc42

Django is a high-level Python Web framework that encourages rapid development and a clean, pragmatic design. It focuses on automating as much as possible and adhering to the DRY Don't Repeat Yourself principle...

[SECURITY] Fedora 41 Update: python-django4.2-4.2.22-1.fc41

Django is a high-level Python Web framework that encourages rapid development and a clean, pragmatic design. It focuses on automating as much as possible and adhering to the DRY Don't Repeat Yourself principle...

VulnCheck KEV: CVE-2025-20188

A vulnerability in the Out-of-Band Access Point AP Image Download, the Clean Air Spectral Recording, and the client debug bundles features of Cisco IOS XE Software for Wireless LAN Controllers WLCs could allow an unauthenticated, remote attacker to upload arbitrary files to an affected...

BadReward: Clean-Label Poisoning of Reward Models in Text-To-Image RLHF

Reinforcement Learning from Human Feedback RLHF is crucial for aligning text-to-image T2I models with human preferences. However, RLHF's feedback mechanism also opens new pathways for adversaries. This paper demonstrates the feasibility of hijacking T2I models by poisoning a small fraction of...

Hijacking Large Language Models Via Adversarial In-Context Learning

In-context learning ICL has emerged as a powerful paradigm leveraging LLMs for specific downstream tasks by utilizing labeled examples as demonstrations demos in the preconditioned prompts. Despite its promising performance, crafted adversarial attacks pose a notable threat to the robustness of...