Scientists Need a Positive Vision for AI

For many in the research community, it's gotten harder to be optimistic about the impacts of artificial intelligence. As authoritarianism is rising around the world, AI-generated "slop" is overwhelming legitimate media, while AI-generated deepfakes are spreading misinformation and parroting...

EUVD-2008-1780

Malware in sbrugna...

Unity Linux 20.1070e Security Update: kernel (UTSA-2025-986596)

The Unity Linux 20 host has a package installed that is affected by a vulnerability as referenced in the UTSA-2025-986596 advisory. In the Linux kernel, the following vulnerability has been resolved: smack: tcp: ipv4, fix incorrect labeling Currently, Smack mirrors the label of incoming tcp/ipv4...

EUVD-2025-14944

Malicious code in bioql PyPI...

EUVD-2025-4105

Malicious code in bioql PyPI...

EUVD-2021-30615

Malicious code in bioql PyPI...

Weakly Supervised Vulnerability Localization Via Multiple Instance Learning

Software vulnerability detection has emerged as a significant concern in the field of software security recently, capturing the attention of numerous researchers and developers. Most previous approaches focus on coarse-grained vulnerability detection, such as at the function or file level. Howeve...

Backdoor Attacks and Defenses in Computer Vision Domain: a Survey

Backdoor trojan attacks embed hidden, controllable behaviors into machine-learning models so that models behave normally on benign inputs but produce attacker-chosen outputs when a trigger is present. This survey reviews the rapidly growing literature on backdoor attacks and defenses in the...

Adaptive Anomaly Detection in Evolving Network Environments

Distribution shift, a change in the statistical properties of data over time, poses a critical challenge for deep learning anomaly detection systems. Existing anomaly detection systems often struggle to adapt to these shifts. Specifically, systems based on supervised learning require costly manua...

LMDG: Advancing Lateral Movement Detection through High-Fidelity Dataset Generation

Lateral Movement LM attacks continue to pose a significant threat to enterprise security, enabling adversaries to stealthily compromise critical assets. However, the development and evaluation of LM detection systems are impeded by the absence of realistic, well-labeled datasets. To address this...

NewStart CGSL MAIN 7.02 : kernel Multiple Vulnerabilities (NS-SA-2025-0118)

"The remote NewStart CGSL host, running version MAIN 7.02, has kernel packages installed that are affected by multiple vulnerabilities: - In the Linux kernel, the following vulnerability has been resolved: smack: tcp: ipv4, fix incorrect labeling Currently, Smack mirrors the label of incoming...

ADAPT: a Pseudo-Labeling Approach to Combat Concept Drift in Malware Detection

Whitepaper called ADAPT: A Pseudo-Labeling Approach To Combat Concept Drift In Malware Detection...

Taming Data Challenges in ML-Based Security Tasks: Lessons from Integrating Generative AI

Machine learning-based supervised classifiers are widely used for security tasks, and their improvement has been largely focused on algorithmic advancements. We argue that data challenges that negatively impact the performance of these classifiers have received limited attention. We address the...

FuncVul: an Effective Function Level Vulnerability Detection Model Using LLM and Code Chunk

Software supply chain vulnerabilities arise when attackers exploit weaknesses by injecting vulnerable code into widely used packages or libraries within software repositories. While most existing approaches focus on identifying vulnerable packages or libraries, they often overlook the specific...

Efficient Retail Video Annotation: a Robust Key Frame Generation Approach for Product and Customer Interaction Analysis

Accurate video annotation plays a vital role in modern retail applications, including customer behavior analysis, product interaction detection, and in-store activity recognition. However, conventional annotation methods heavily rely on time-consuming manual labeling by human annotators,...

Linux kernel 安全漏洞

Linux kernel is the kernel used by Linux, the open source operating system of the Linux Foundation in the United States. A security vulnerability exists in the Linux kernel that stems from a duplicate registration issue caused by the felix driver performing operations even when the labeling...

Mono: Is Your "Clean" Vulnerability Dataset Really Solvable? Exposing and Trapping Undecidable Patches and Beyond

The quantity and quality of vulnerability datasets are essential for developing deep learning solutions to vulnerability-related tasks. Due to the limited availability of vulnerabilities, a common approach to building such datasets is analyzing security patches in source code. However, existing...

Security Benefits and Side Effects of Labeling AI-Generated Images

Generative artificial intelligence is developing rapidly, impacting humans' interaction with information and digital media. It is increasingly used to create deceptively realistic misinformation, so lawmakers have imposed regulations requiring the disclosure of AI-generated content. However, only...

Laravel Starter 安全漏洞

Laravel Starter is a simple starter project based on Laravel 11.x by Nasir Khan Saikat Individual Developer. A security vulnerability exists in Laravel Starter version 11.11.0, which stems from insufficient handling of inputs in the name field in the labeling feature and could lead to a cross-sit...

UBUNTU-CVE-2025-26696

Certain crafted MIME email messages that claimed to contain an encrypted OpenPGP message, which instead contained an OpenPGP signed message, were wrongly shown as being encrypted. This vulnerability affects Thunderbird 136 and Thunderbird 128.8...