CVE-2024-8009

The Sensei LMS WordPress plugin (versions prior to 4.20.0 ) contains a vulnerability that discloses information about all blog users, including their email addresses , to users with teacher roles on the students page. To resolve this issue, it is recommended to update the plugin to version 4.20.0...

Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy

Large Language Models LLMs have gained significant popularity due to their remarkable capabilities in text understanding and generation. However, despite their widespread deployment in inference services such as ChatGPT, concerns about the potential leakage of sensitive user data have arisen...

PT-2025-21585 · Zulip · Zulip

Name of the Vulnerable Software and Affected Versions: Zulip versions 10.0 through 10.2 Description: The issue concerns the "Who can create public channels" access control mechanism in Zulip, which can be circumvented by creating a private or web-public channel and then changing the channel priva...

Private Transformer Inference in MLaaS: a Survey

Transformer models have revolutionized AI, powering applications like content generation and sentiment analysis. However, their deployment in Machine Learning as a Service MLaaS raises significant privacy concerns, primarily due to the centralized processing of sensitive user data. Private...

CVE-2025-24142

A privacy issue was addressed with improved private data redaction for log entries. This issue is fixed in macOS Sequoia 15.5, macOS Sonoma 14.7.6, macOS Ventura 13.7.6. An app may be able to access sensitive user data...

CVE-2025-31224

A logic issue was addressed with improved checks. This issue is fixed in macOS Sequoia 15.5, macOS Sonoma 14.7.6, macOS Ventura 13.7.6. An app may be able to bypass certain Privacy preferences...

CVE-2025-31242

A privacy issue was addressed with improved private data redaction for log entries. This issue is fixed in iOS 18.5 and iPadOS 18.5, iPadOS 17.7.7, macOS Sequoia 15.5, macOS Sonoma 14.7.3, macOS Sonoma 14.7.6, macOS Ventura 13.7.3, macOS Ventura 13.7.6, tvOS 18.5, visionOS 2.5, watchOS 11.5. An a...

CVE-2025-31220

A privacy issue was addressed by removing sensitive data. This issue is fixed in iPadOS 17.7.7, macOS Sequoia 15.5, macOS Sonoma 14.7.6, macOS Ventura 13.7.6. A malicious app may be able to read sensitive location information...

CVE-2025-31225

A privacy issue was addressed by removing sensitive data. This issue is fixed in iOS 18.5 and iPadOS 18.5. Call history from deleted apps may still appear in spotlight search results...

CVE-2025-31250

An information disclosure issue was addressed with improved privacy controls. This issue is fixed in macOS Sequoia 15.5. An app may be able to access sensitive user data...

CVE-2025-31236

An information disclosure issue was addressed with improved privacy controls. This issue is fixed in macOS Sequoia 15.5. An app may be able to access sensitive user data...

GHSA-9CWV-PXCR-HFJC LF Edge eKuiper Vulnerable to Stored XSS in Configuration Key Functionality

Summary Stored Cross-Site Scripting XSS vulnerability allows attackers to inject malicious scripts into web applications, which can then be executed in the context of other users' browsers. This can lead to unauthorized access to sensitive information, session hijacking, and spreading of malware,...

Google to pay $1.38 billion over privacy violations

The state of Texas reached a mammoth financial agreement with Google last week, securing $1.375 billion in payments to settle two three year-old lawsuits. The Office of Texas Attorney General Ken Paxton originally filed the first lawsuit against Google in January 2022, complaining that the tech...

Correlating Account on Ethereum Mixing Service Via Domain-Invariant Feature Learning

The untraceability of transactions facilitated by Ethereum mixing services like Tornado Cash poses significant challenges to blockchain security and financial regulation. Existing methods for correlating mixing accounts suffer from limited labeled data and vulnerability to noisy annotations, whic...

Privacy-Preserving Runtime Verification

Runtime verification offers scalable solutions to improve the safety and reliability of systems. However, systems that require verification or monitoring by a third party to ensure compliance with a specification might contain sensitive information, causing privacy concerns when usual runtime...

Alibaba Cloud Linux 3 : 0040: webkit2gtk3 (ALINUX3-SA-2025:0040)

The remote Alibaba Cloud Linux 3 host has packages installed that are affected by multiple vulnerabilities as referenced in the ALINUX3-SA-2025:0040 advisory. Package updates are available for Alibaba Cloud Linux 3 that fix the following vulnerabilities: CVE-2024-54543: The issue was addressed wi...

Robust Federated Learning with Confidence-Weighted Filtering and GAN-Based Completion under Noisy and Incomplete Data

Federated learning FL presents an effective solution for collaborative model training while maintaining data privacy across decentralized client datasets. However, data quality issues such as noisy labels, missing classes, and imbalanced distributions significantly challenge its effectiveness. Th...

DNS Query Forgery: a Client-Side Defense against Mobile App Traffic Profiling

Mobile applications continuously generate DNS queries that can reveal sensitive user behavioral patterns even when communications are encrypted. This paper presents a privacy enhancement framework based on query forgery to protect users against profiling attempts that leverage these background...

Inference Attacks for X-Vector Speaker Anonymization

We revisit the privacy-utility tradeoff of x-vector speaker anonymization. Existing approaches quantify privacy through training complex speaker verification or identification models that are later used as attacks. Instead, we propose a novel inference attack for de-anonymization. Our attack is...

Information Leakage in Data Linkage

The process of linking databases that contain sensitive information about individuals across organisations is an increasingly common requirement in the health and social science research domains, as well as with governments and businesses. To protect personal data, protocols have been developed t...