MemoPhishAgent: Memory-Augmented Multi-Modal LLM Agent for Phishing URL Detection

Traditional phishing website detection relies on static heuristics or reference lists, which lag behind rapidly evolving attacks. While recent systems incorporate large language models LLMs, they are still prompt-based, deterministic pipelines that underutilize reasoning capability. We present...

LoRA-Based Parameter-Efficient LLMs for Continuous Learning in Edge-Based Malware Detection

The proliferation of edge devices has created an urgent need for security solutions capable of detecting malware in real time while operating under strict computational and memory constraints. Recently, Large Language Models LLMs have demonstrated remarkable capabilities in recognizing complex...

RedSage: A Cybersecurity Generalist LLM

Cybersecurity operations demand assistant LLMs that support diverse workflows without exposing sensitive data. Existing solutions either rely on proprietary APIs with privacy risks or on open models lacking domain adaptation. To bridge this gap, we curate 11.8B tokens of cybersecurity-focused...

LogPurge: Log Data Purification for Anomaly Detection Via Rule-Enhanced Filtering

Log anomaly detection, which is critical for identifying system failures and preempting security breaches, detects irregular patterns within large volumes of log data, and impacts domains such as service reliability, performance optimization, and database log analysis. Modern log anomaly detectio...

An Evaluation Framework for Network IDS/IPS Datasets: Leveraging MITRE ATT&CK and Industry Relevance Metrics

The performance of Machine Learning ML and Deep Learning DL-based Intrusion Detection and Prevention Systems IDS/IPS is critically dependent on the relevance and quality of the datasets used for training and evaluation. However, current AI model evaluation practices for developing IDS/IPS focus...

Mind the Gap: Missing Cyber Threat Coverage in NIDS Datasets for the Energy Sector

Network Intrusion Detection Systems NIDS developed using publicly available datasets predominantly focus on enterprise environments, raising concerns about their effectiveness for converged Information Technology IT and Operational Technology OT in energy infrastructures. This study evaluates the...

Permissioned LLMs: Enforcing Access Control in Large Language Models

In enterprise settings, organizational data is segregated, siloed and carefully protected by elaborate access control frameworks. These access control structures can completely break down if an LLM fine-tuned on the siloed data serves requests, for downstream tasks, from individuals with disparat...

CVE-2024-42351

Galaxy is a free, open-source system for analyzing data, authoring workflows, training and education, publishing tools, managing infrastructure, and more. An attacker can potentially replace the contents of public datasets resulting in data loss or tampering. All supported branches of Galaxy and...

A Collaborative Intrusion Detection System Using Snort IDS Nodes

Intrusion Detection Systems IDSs are integral to safeguarding networks by detecting and responding to threats from malicious traffic or compromised devices. However, standalone IDS deployments often fall short when addressing the increasing complexity and scale of modern cyberattacks. This paper...

CVE-2024-42351 Possible Data Tampering & Loss of Public Datasets in Galaxy

Galaxy is a free, open-source system for analyzing data, authoring workflows, training and education, publishing tools, managing infrastructure, and more. An attacker can potentially replace the contents of public datasets resulting in data loss or tampering. All supported branches of Galaxy and...

CVE-2024-42351

CVE-2024-42351 affects the Galaxy open‑source data analysis platform, where an attacker can potentially replace contents of public datasets, causing data loss or tampering. Affected versions are Galaxy releases prior to 21.05; patches have been applied in all supported branches back to release_21...

CVE-2024-42351 Possible Data Tampering & Loss of Public Datasets in Galaxy

Galaxy is a free, open-source system for analyzing data, authoring workflows, training and education, publishing tools, managing infrastructure, and more. An attacker can potentially replace the contents of public datasets resulting in data loss or tampering. All supported branches of Galaxy and...

CVE-2024-42351 Possible Data Tampering & Loss of Public Datasets in Galaxy

Galaxy is a free, open-source system for analyzing data, authoring workflows, training and education, publishing tools, managing infrastructure, and more. An attacker can potentially replace the contents of public datasets resulting in data loss or tampering. All supported branches of Galaxy and...

PT-2024-29888 · Galaxy · Galaxy

Name of the Vulnerable Software and Affected Versions: Galaxy versions prior to release 21.05 Description: Galaxy is a free, open-source system for analyzing data, authoring workflows, training and education, publishing tools, managing infrastructure, and more. An attacker can potentially replace...