35650 matches found
PhishSSL: Self-Supervised Contrastive Learning for Phishing Website Detection
Phishing websites remain a persistent cybersecurity threat by mimicking legitimate sites to steal sensitive user information. Existing machine learning-based detection methods often rely on supervised learning with labeled data, which not only incurs substantial annotation costs but also limits...
Intercom Chatbot Misconfiguration
Intercom is a solution to build & deploy AI customer experiences. If the identity verification is not enabled, an attacker can impersonate an other user and access to the previous conversations and data. This detection is included in the AI and LLM category. No source data...
Applying Graph Analysis for Unsupervised Fast Malware Fingerprinting
Malware proliferation is increasing at a tremendous rate, with hundreds of thousands of new samples identified daily. Manual investigation of such a vast amount of malware is an unrealistic, time-consuming, and overwhelming task. To cope with this volume, there is a clear need to develop...
Benchmarking Fake Voice Detection in the Fake Voice Generation Arms Race
As advances in synthetic voice generation accelerate, an increasing variety of fake voice generators have emerged, producing audio that is often indistinguishable from real human speech. This evolution poses new and serious threats across sectors where audio recordings serve as critical evidence...
Unity Linux 20.1070e Security Update: kernel (UTSA-2025-987018)
The Unity Linux 20 host has a package installed that is affected by a vulnerability as referenced in the UTSA-2025-987018 advisory. In the Linux kernel, the following vulnerability has been resolved: usb: chipidea: cihdrcimx: Also search for 'phys' phandle When passing 'phys' in the devicetree to...
Adversarial-Resilient RF Fingerprinting: A CNN-GAN Framework for Rogue Transmitter Detection
Radio Frequency Fingerprinting RFF has evolved as an effective solution for authenticating devices by leveraging the unique imperfections in hardware components involved in the signal generation process. In this work, we propose a Convolutional Neural Network CNN based framework for detecting rog...
Unity Linux 20.1070e Security Update: kernel (UTSA-2025-414559)
The Unity Linux 20 host has a package installed that is affected by a vulnerability as referenced in the UTSA-2025-414559 advisory. fs/nfs/nfs4client.c in the Linux kernel before 5.13.4 has incorrect connection-setup ordering, which allows operators of remote NFSv4 servers to cause a denial of...
kernel: security/keys: fix slab-out-of-bounds in key_task_permission
In the Linux kernel, the following vulnerability has been resolved: security/keys: fix slab-out-of-bounds in keytaskpermission KASAN reports an out of bounds read: BUG: KASAN: slab-out-of-bounds in kuidval include/linux/uidgid.h:36 BUG: KASAN: slab-out-of-bounds in uideq include/linux/uidgid.h:63...
How we trained an ML model to detect DLL hijacking
DLL hijacking is a common technique in which attackers replace a library called by a legitimate process with a malicious one. It is used by both creators of mass-impact malware, like stealers and banking Trojans, and by APT and cybercrime groups behind targeted attacks. In recent years, the numbe...
Forensic Timeliner 2.2
Forensic Timeliner is a high-speed forensic processing engine built for DFIR investigators. It quickly consolidates CSV output from top-tier triage tools into a unified mini timeline with built-in filtering, artifact detection, date filtering, keyword tagging, and deduplication...
Exploit for Improper Authentication in Oracle Concurrent_Processing
CVE-2025-61882 & CVE-2025-61884 EDIT: Oracle just disclose...
ZenML 安全漏洞
ZenML is an extensible open source MLOps framework from ZenML Open Source for creating portable, production-ready machine learning pipelines. An input validation error vulnerability exists in ZenML version 0.83.1, which stems from the failure of the PathMaterializer class to effectively detect...
MulVuln: Enhancing Pre-Trained LMs with Shared and Language-Specific Knowledge for Multilingual Vulnerability Detection
Software vulnerabilities SVs pose a critical threat to safety-critical systems, driving the adoption of AI-based approaches such as machine learning and deep learning for software vulnerability detection. Despite promising results, most existing methods are limited to a single programming languag...
OptiFLIDS: Optimized Federated Learning for Energy-Efficient Intrusion Detection in IoT
In critical IoT environments, such as smart homes and industrial systems, effective Intrusion Detection Systems IDS are essential for ensuring security. However, developing robust IDS solutions remains a significant challenge. Traditional machine learning-based IDS models typically require large...
Cyber Warfare during Operation Sindoor: Malware Campaign Analysis and Detection Framework
Rapid digitization of critical infrastructure has made cyberwarfare one of the important dimensions of modern conflicts. Attacking the critical infrastructure is an attractive pre-emptive proposition for adversaries as it can be done remotely without crossing borders. Such attacks disturb the...
Real-VulLLM: An LLM Based Assessment Framework in the Wild
Artificial Intelligence AI and more specifically Large Language Models LLMs have demonstrated exceptional progress in multiple areas including software engineering, however, their capability for vulnerability detection in the wild scenario and its corresponding reasoning remains underexplored...
CVE-2025-39940
CVE-2025-39940 concerns the Linux kernel’s dm-stripe component. A potential integer overflow can occur in stripe_io_hints when the chunk size is too large. The fix tests for an overflow and, if detected, avoids setting limits->io_min and limits->io_opt. This mitigates a local-privilege vect...
Security Analysis of Ponzi Schemes in Ethereum Smart Contracts
The rapid advancement of blockchain technology has precipitated the widespread adoption of Ethereum and smart contracts across a variety of sectors. However, this has also given rise to numerous fraudulent activities, with many speculators embedding Ponzi schemes within smart contracts, resulting...
Pilot Contamination Attacks Detection with Machine Learning for Multi-User Massive MIMO
Massive multiple-input multiple-output MMIMO is essential to modern wireless communication systems, like 5G and 6G, but it is vulnerable to active eavesdropping attacks. One type of such attack is the pilot contamination attack PCA, where a malicious user copies pilot signals from an authentic us...
