AT&T to pay compensation to data breach victims. Here’s how to check if you were affected

AT&T is set to pay $177 million to customers affected by two significant data breaches. These breaches exposed sensitive personal information of millions of current and former AT&T customers. For those that have missed the story so far: Back in 2021, an entity named Shiny Hunters a known hacking...

Researchers Warn Free VPNs Could Leak US Data to China

Tech Transparency Project warns Chinese-owned VPNs like Turbo VPN and X-VPN remain on Apple and Google app stores, raising national security concerns...

Many data brokers are failing to register with state consumer protection agencies

Hundreds of data brokers haven't registered with state consumer protection agencies, according to The Electronic Frontier Foundation EFF and Privacy Rights Clearinghouse PRC. There are different kinds of data brokers, but what they all have in common is that they gather personally identifiable...

Federated Learning-Based Data Collaboration Method for Enhancing Edge Cloud AI System Security Using Large Language Models

With the widespread application of edge computing and cloud systems in AI-driven applications, how to maintain efficient performance while ensuring data privacy has become an urgent security issue. This paper proposes a federated learning-based data collaboration method to improve the security of...

SoK: the Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation

Large language models LLMs are sophisticated artificial intelligence systems that enable machines to generate human-like text with remarkable precision. While LLMs offer significant technological progress, their development using vast amounts of user data scraped from the web and collected from...

Image Corruption-Inspired Membership Inference Attacks against Large Vision-Language Models

Large vision-language models LVLMs have demonstrated outstanding performance in many downstream tasks. However, LVLMs are trained on large-scale datasets, which can pose privacy risks if training images contain sensitive information. Therefore, it is important to detect whether an image is used t...

SoK: Privacy-Enhancing Technologies in Artificial Intelligence

As artificial intelligence AI continues to permeate various sectors, safeguarding personal and sensitive data has become increasingly crucial. To address these concerns, privacy-enhancing technologies PETs have emerged as a suite of digital tools that enable data collection and processing while...

Securing Generative AI Agentic Workflows: Risks, Mitigation, and a Proposed Firewall Architecture

Generative Artificial Intelligence GenAI presents significant advancements but also introduces novel security challenges, particularly within agentic workflows where AI agents operate autonomously. These risks escalate in multi-agent systems due to increased interaction complexity. This paper...

A week in security (June 1 – June 7)

Last week on Malwarebytes Labs: What does Facebook know about me? Lock and Code S06E11 Victims risk AsyncRAT infection after being redirected to fake Booking.com sites Juice jacking warnings are back, with a new twist The North Face warns customers about potentially stolen data Scammers are...

A Certified Unlearning Approach without Access to Source Data

With the growing adoption of data privacy regulations, the ability to erase private or copyrighted information from trained models has become a crucial requirement. Traditional unlearning methods often assume access to the complete training dataset, which is unrealistic in scenarios where the...

Privacy and Security Threat for OpenAI GPTs

Large language models LLMs demonstrate powerful information handling capabilities and are widely integrated into chatbot applications. OpenAI provides a platform for developers to construct custom GPTs, extending ChatGPT's functions and integrating external services. Since its release in November...

ROS-20250526-07

Google Chrome browser vulnerability involves post-release memory usage. Exploitation of the vulnerability could allow an attacker acting remotely to impact privacy, integrity and availability of data through the use of a specially crafted HTML page...

Understanding the Relationship between Personal Data Privacy Literacy and Data Privacy Information Sharing by University Students

With constant threats to the safety of personal data in the United States, privacy literacy has become an increasingly important competency among university students, one that ties intimately to the information sharing behavior of these students. This survey based study examines how university...

CVE-2024-25129

The CodeQL CLI repo holds binaries for the CodeQL command line interface CLI. Prior to version 2.16.3, an XML parser used by the CodeQL CLI to read various auxiliary files is vulnerable to an XML External Entity attack. If a vulnerable version of the CLI is used to process either a maliciously...

CVE-2024-23329

changedetection.io is an open source tool designed to monitor websites for content changes. In affected versions the API endpoint /api/v1/watch//history can be accessed by any unauthorized user. As a result any unauthorized user can check one's watch history. However, because unauthorized party...

CVE-2023-36827

Fides is an open-source privacy engineering platform for managing the fulfillment of data privacy requests in a runtime environment, and the enforcement of privacy regulations in code. A path traversal directory traversal vulnerability affects fides versions lower than version 2.15.1, allowing...

CVE-2023-27890

The Export User plugin through 2.0 for MyBB allows XSS during the process of an admin generating DSGVO data for a user, via the Custom User Title, Location, or Bio field. NOTE: This vulnerability only affects products that are no longer supported by the maintainer...

CVE-2021-29626

In FreeBSD 13.0-STABLE before n245117, 12.2-STABLE before r369551, 11.4-STABLE before r369559, 13.0-RC5 before p1, 12.2-RELEASE before p6, and 11.4-RELEASE before p9, copy-on-write logic failed to invalidate shared memory page mappings between multiple processes allowing an unprivileged process t...

Outsourced Privacy-Preserving Feature Selection Based on Fully Homomorphic Encryption

Feature selection is a technique that extracts a meaningful subset from a set of features in training data. When the training data is large-scale, appropriate feature selection enables the removal of redundant features, which can improve generalization performance, accelerate the training process...

Cross-Cloud Data Privacy Protection: Optimizing Collaborative Mechanisms of AI Systems by Integrating Federated Learning and LLMs

In the age of cloud computing, data privacy protection has become a major challenge, especially when sharing sensitive data across cloud environments. However, how to optimize collaboration across cloud environments remains an unresolved problem. In this paper, we combine federated learning with...