GO-2025-3822 Authentik has insufficient check for account active status when authenticating with OAuth/SAML Sources in goauthentik.io

Authentik has insufficient check for account active status when authenticating with OAuth/SAML Sources in goauthentik.io. NOTE: The source advisory for this report contains additional versions that could not be automatically mapped to standard Go module versions. If this is causing false-positive...

CVE-2025-54888

Fedify is a TypeScript library for building federated server apps powered by ActivityPub. In versions below 1.3.20, 1.4.0-dev.585 through 1.4.12, 1.5.0-dev.636 through 1.5.4, 1.6.0-dev.754 through 1.6.7, 1.7.0-pr.251.885 through 1.7.8 and 1.8.0-dev.909 through 1.8.4, an authentication bypass...

CVE-2025-54888 @fedify/fedify: Improper Authentication and Incorrect Authorization

Fedify is a TypeScript library for building federated server apps powered by ActivityPub. In versions below 1.3.20, 1.4.0-dev.585 through 1.4.12, 1.5.0-dev.636 through 1.5.4, 1.6.0-dev.754 through 1.6.7, 1.7.0-pr.251.885 through 1.7.8 and 1.8.0-dev.909 through 1.8.4, an authentication bypass...

Linux Distros Unpatched Vulnerability : CVE-2022-21270

The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - Vulnerability in the MySQL Server product of Oracle MySQL component: Server: Federated. Supported versions that are affected are 5.7.36 and prior and 8.0.27 and...

Label Inference Attacks against Federated Unlearning

Federated Unlearning FU has emerged as a promising solution to respond to the right to be forgotten of clients, by allowing clients to erase their data from global models without compromising model performance. Unfortunately, researchers find that the parameter variations of models induced by FU...

Linux Distros Unpatched Vulnerability : CVE-2022-21547

The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - Vulnerability in the MySQL Server product of Oracle MySQL component: Server: Federated. Supported versions that are affected are 8.0.29 and prior. Easily...

SelectiveShield: Lightweight Hybrid Defense against Gradient Leakage in Federated Learning

Federated Learning FL enables collaborative model training on decentralized data but remains vulnerable to gradient leakage attacks that can reconstruct sensitive user information. Existing defense mechanisms, such as differential privacy DP and homomorphic encryption HE, often introduce a...

SenseCrypt: Sensitivity-Guided Selective Homomorphic Encryption for Joint Federated Learning in Cross-Device Scenarios

Homomorphic Encryption HE prevails in securing Federated Learning FL, but suffers from high overhead and adaptation cost. Selective HE methods, which partially encrypt model parameters by a global mask, are expected to protect privacy with reduced overhead and easy adaptation. However, in...

Per-Element Secure Aggregation against Data Reconstruction Attacks in Federated Learning

Federated learning FL enables collaborative model training without sharing raw data, but individual model updates may still leak sensitive information. Secure aggregation SecAgg mitigates this risk by allowing the server to access only the sum of client updates, thereby concealing individual...

Coward: toward Practical Proactive Federated Backdoor Defense Via Collision-Based Watermark

Backdoor detection is currently the mainstream defense against backdoor attacks in federated learning FL, where malicious clients upload poisoned updates that compromise the global model and undermine the reliability of FL deployments. Existing backdoor detection techniques fall into two...

Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy

This paper provides an integrated perspective on addressing key challenges in developing reliable and secure Quantum Neural Networks QNNs in the Noisy Intermediate-Scale Quantum NISQ era. In this paper, we present an integrated framework that leverages and combines existing approaches to enhance...

ModShift: Model Privacy Via Designed Shifts

In this paper, shifts are introduced to preserve model privacy against an eavesdropper in federated learning. Model learning is treated as a parameter estimation problem. This perspective allows us to derive the Fisher Information matrix of the model updates from the shifted updates and drive the...

FedBAP: Backdoor Defense Via Benign Adversarial Perturbation in Federated Learning

Federated Learning FL enables collaborative model training while preserving data privacy, but it is highly vulnerable to backdoor attacks. Most existing defense methods in FL have limited effectiveness due to their neglect of the model's over-reliance on backdoor triggers, particularly as the...

DP2Guard: a Lightweight and Byzantine-Robust Privacy-Preserving Federated Learning Scheme for Industrial IoT

Privacy-Preserving Federated Learning PPFL has emerged as a secure distributed Machine Learning ML paradigm that aggregates locally trained gradients without exposing raw data. To defend against model poisoning threats, several robustness-enhanced PPFL schemes have been proposed by integrating...

A Privacy-Centric Approach: Scalable and Secure Federated Learning Enabled by Hybrid Homomorphic Encryption

Federated Learning FL enables collaborative model training without sharing raw data, making it a promising approach for privacy-sensitive domains. Despite its potential, FL faces significant challenges, particularly in terms of communication overhead and data privacy. Privacy-preserving Technique...

CVE-2025-53941 Hollo renders posts received with form elements and allows submission

Hollo is a federated single-user microblogging software designed to be federated through ActivityPub. Versions prior to 0.6.5 allow HTML form elements to be submitted, making the software vulnerable to HTML injection. Version 0.6.5 fixes the issue...

CVE-2025-53941 Hollo renders posts received with form elements and allows submission

Hollo is a federated single-user microblogging software designed to be federated through ActivityPub. Versions prior to 0.6.5 allow HTML form elements to be submitted, making the software vulnerable to HTML injection. Version 0.6.5 fixes the issue...

CVE-2025-53941 Hollo renders posts received with form elements and allows submission

Hollo is a federated single-user microblogging software designed to be federated through ActivityPub. Versions prior to 0.6.5 allow HTML form elements to be submitted, making the software vulnerable to HTML injection. Version 0.6.5 fixes the issue...

PT-2025-29913 · Hollo · Hollo

Name of the Vulnerable Software and Affected Versions: Hollo versions prior to 0.6.5 Description: Hollo is a federated single-user microblogging software designed to be federated through ActivityPub. Versions prior to 0.6.5 allow HTML form elements to be submitted, leading to a potential HTML...

A Crowdsensing Intrusion Detection Dataset for Decentralized Federated Learning Models

This paper introduces a dataset and experimental study for decentralized federated learning DFL applied to IoT crowdsensing malware detection. The dataset comprises behavioral records from benign and eight malware families. A total of 21,582,484 original records were collected from system calls,...