1398 matches found
PenTiDef: Enhancing Privacy and Robustness in Decentralized Federated Intrusion Detection Systems against Poisoning Attacks
The increasing deployment of Federated Learning FL in Intrusion Detection Systems IDS introduces new challenges related to data privacy, centralized coordination, and susceptibility to poisoning attacks. While significant research has focused on protecting traditional FL-IDS with centralized...
Assessing Spear-Phishing Website Generation in Large Language Model Coding Agents
Large Language Models are expanding beyond being a tool humans use and into independent agents that can observe an environment, reason about solutions to problems, make changes that impact those environments, and understand how their actions impacted their environment. One of the most common...
GHSA-GFMX-QQQH-F38Q Duplicate Advisory: Keras vulnerable to arbitrary file read in the model loading mechanism (HDF5 integration)
Duplicate Advisory This advisory has been withdrawn because it is a duplicate of GHSA-3m4q-jmj6-r34q. This link is maintained to preserve external references. Original Description Arbitrary file read in the model loading mechanism HDF5 integration in Keras versions 3.0.0 through 3.13.1 on all...
Duplicate Advisory: Keras vulnerable to arbitrary file read in the model loading mechanism (HDF5 integration)
Duplicate Advisory This advisory has been withdrawn because it is a duplicate of GHSA-3m4q-jmj6-r34q. This link is maintained to preserve external references. Original Description Arbitrary file read in the model loading mechanism HDF5 integration in Keras versions 3.0.0 through 3.13.1 on all...
Lightweight Cluster-Based Federated Learning for Intrusion Detection in Heterogeneous IoT Networks
The rise of heterogeneous Internet of Things IoT devices has raised security concerns due to their vulnerability to cyberattacks. Intrusion Detection Systems IDS are crucial in addressing these threats. Federated Learning FL offers a privacy-preserving solution, but IoT heterogeneity and limited...
Linux Distros Unpatched Vulnerability : CVE-2026-1669
The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - Arbitrary file read in the model loading mechanism HDF5 integration in Keras versions 3.0.0 through 3.13.1 on all supported platforms allows a remote attacker t...
MalTool: Malicious Tool Attacks on LLM Agents
In a malicious tool attack, an attacker uploads a malicious tool to a distribution platform; once a user installs the tool and the LLM agent selects it during task execution, the tool can compromise the user's security and privacy. Prior work primarily focuses on manipulating tool names and...
AZL-77414 CVE-2026-1669 affecting package keras for versions less than 3.3.3-7
Arbitrary file read in the model loading mechanism HDF5 integration in Keras versions 3.0.0 through 3.13.1 on all supported platforms allows a remote attacker to read local files and disclose sensitive information via a crafted .keras model file utilizing HDF5 external dataset references...
DEBIAN-CVE-2026-1669
Arbitrary file read in the model loading mechanism HDF5 integration in Keras versions 3.0.0 through 3.13.1 on all supported platforms allows a remote attacker to read local files and disclose sensitive information via a crafted .keras model file utilizing HDF5 external dataset references...
CVE-2026-1669
Arbitrary file read in the model loading mechanism HDF5 integration in Keras versions 3.0.0 through 3.13.1 on all supported platforms allows a remote attacker to read local files and disclose sensitive information via a crafted .keras model file utilizing HDF5 external dataset references...
CVE-2026-1669 Arbitrary File Read in Keras via HDF5 External Datasets
Arbitrary file read in the model loading mechanism HDF5 integration in Keras versions 3.0.0 through 3.13.1 on all supported platforms allows a remote attacker to read local files and disclose sensitive information via a crafted .keras model file utilizing HDF5 external dataset references...
CVE-2026-1669
Arbitrary file read in the model loading mechanism HDF5 integration in Keras versions 3.0.0 through 3.13.1 on all supported platforms allows a remote attacker to read local files and disclose sensitive information via a crafted .keras model file utilizing HDF5 external dataset references...
CVE-2026-1669
Arbitrary file read in the model loading mechanism HDF5 integration in Keras versions 3.0.0 through 3.13.1 on all supported platforms allows a remote attacker to read local files and disclose sensitive information via a crafted .keras model file utilizing HDF5 external dataset references...
LLM-FS: Zero-Shot Feature Selection for Effective and Interpretable Malware Detection
Feature selection FS remains essential for building accurate and interpretable detection models, particularly in high-dimensional malware datasets. Conventional FS methods such as Extra Trees, Variance Threshold, Tree-based models, Chi-Squared tests, ANOVA, Random Selection, and Sequential...
CIC-Trap4Phish: A Unified Multi-Format Dataset for Phishing and Quishing Attachment Detection
Phishing attacks represents one of the primary attack methods which is used by cyber attackers. In many cases, attackers use deceptive emails along with malicious attachments to trick users into giving away sensitive information or installing malware while compromising entire systems. The...
CVE-2026-2107
A vulnerability was found in yeqifu warehouse up to aaf29962ba407d22d991781de28796ee7b4670e4. This affects the function loadAllLoginfo/deleteLoginfo/batchDeleteLoginfo of the file dataset\repos\warehouse\src\main\java\com\yeqifu\sys\controller\LoginfoController.java of the component Log Info...
Evasion of IoT Malware Detection Via Dummy Code Injection
The Internet of Things IoT has revolutionized connectivity by linking billions of devices worldwide. However, this rapid expansion has also introduced severe security vulnerabilities, making IoT devices attractive targets for malware such as the Mirai botnet. Power side-channel analysis has...
KRONE: Hierarchical and Modular Log Anomaly Detection
Log anomaly detection is crucial for uncovering system failures and security risks. Although logs originate from nested component executions with clear boundaries, this structure is lost when they are stored as flat sequences. As a result, state-of-the-art methods risk missing true dependencies...
Deep Learning for Contextualized NetFlow-Based Network Intrusion Detection: Methods, Data, Evaluation and Deployment
Network Intrusion Detection Systems NIDS have progressively shifted from signature-based techniques toward machine learning and, more recently, deep learning methods. Meanwhile, the widespread adoption of encryption has reduced payload visibility, weakening inspection pipelines that depend on...
Identifying Adversary Tactics and Techniques in Malware Binaries with an LLM Agent
Understanding TTPs Tactics, Techniques, and Procedures in malware binaries is essential for security analysis and threat intelligence, yet remains challenging in practice. Real-world malware binaries are typically stripped of symbols, contain large numbers of functions, and distribute malicious...