EUVD-2024-41714

Malicious code in bioql PyPI...

EUVD-2024-41271

Malicious code in bioql PyPI...

EUVD-2023-26954

Malicious code in bioql PyPI...

Forensic journey: hunting evil within AmCache

Introduction When it comes to digital forensics, AmCache plays a vital role in identifying malicious activities in Windows systems. This artifact allows the identification of the execution of both benign and malicious software on a machine. It is managed by the operating system, and at the time o...

POLAR: Automating Cyber Threat Prioritization through LLM-Powered Assessment

Large Language Models LLMs are intensively used to assist security analysts in counteracting the rapid exploitation of cyber threats, wherein LLMs offer cyber threat intelligence CTI to support vulnerability assessment and incident response. While recent work has shown that LLMs can support a wid...

Microsoft Flags AI Phishing Attack Hiding in SVG Files

Microsoft Threat Intelligence detected a new AI-powered phishing campaign using LLMs to hide malicious code inside SVG files disguised as business dashboards...

SecureBERT 2.0: Advanced Language Model for Cybersecurity Intelligence

Effective analysis of cybersecurity and threat intelligence data demands language models that can interpret specialized terminology, complex document structures, and the interdependence of natural language and source code. Encoder-only transformer architectures provide efficient and robust...

ThreatBook Launches Best-of-Breed Advanced Threat Intelligence Solution

Singapore, Singapore, 29th September 2025, CyberNewsWire...

Uncovering Vulnerabilities of LLM-Assisted Cyber Threat Intelligence

Large Language Models LLMs are intensively used to assist security analysts in counteracting the rapid exploitation of cyber threats, wherein LLMs offer cyber threat intelligence CTI to support vulnerability assessment and incident response. While recent work has shown that LLMs can support a wid...

A Global Analysis of Cyber Threats to the Energy Sector: "Currents of Conflict" from a Geopolitical Perspective

The escalating frequency and sophistication of cyber threats increased the need for their comprehensive understanding. This paper explores the intersection of geopolitical dynamics, cyber threat intelligence analysis, and advanced detection technologies, with a focus on the energy domain. We...

AI vs. AI: Detecting an AI-obfuscated phishing campaign

Microsoft Threat Intelligence recently detected and blocked a credential phishing campaign that likely used AI-generated code to obfuscate its payload and evade traditional defenses. Appearing to be aided by a large language model LLM, the activity obfuscated its behavior within an SVG file,...

CyberSOCEval: Benchmarking LLMs Capabilities for Malware Analysis and Threat Intelligence Reasoning

Today's cyber defenders are overwhelmed by a deluge of security alerts, threat intelligence signals, and shifting business context, creating an urgent need for AI systems to enhance operational security work. While Large Language Models LLMs have the potential to automate and scale Security...

Unmasking Hidden Threats: Spotting a DPRK IT-Worker Campaign

Unmasking Hidden Threats: Spotting a DPRK IT-Worker Campaign By Duy-Phuc Pham and John Fokker · September 23, 2025 In today's complex threat landscape, staying ahead of sophisticated adversaries is paramount. Organizations face constant pressure to identify threats that do not always involve...

Wordfence Bug Bounty Program Monthly Report – August 2025

Last month in August 2025, the Wordfence Bug Bounty Program received 438 vulnerability submissions from our growing community of security researchers working to improve the overall security posture of the WordPress ecosystem. These submissions are reviewed, triaged, and processed by the Wordfence...

CVE-2024-52846

creationtimestamp| type| source ---|---|--- 2025-09-16 23:16:38+00:00| seen| MISP/be792712-f638-4d7d-b62d-4f5032e86764 2025-09-18 16:44:33+00:00| seen| MISP/be792712-f638-4d7d-b62d-4f5032e86764...

CVE-2024-52844

creationtimestamp| type| source ---|---|--- 2025-09-16 23:16:37+00:00| seen| MISP/be792712-f638-4d7d-b62d-4f5032e86764 2025-09-18 16:44:31+00:00| seen| MISP/be792712-f638-4d7d-b62d-4f5032e86764...

Cyber Threat Hunting: Non-Parametric Mining of Attack Patterns from Cyber Threat Intelligence for Precise Threats Attribution

With the ever-changing landscape of cyber threats, identifying their origin has become paramount, surpassing the simple task of attack classification. Cyber threat attribution gives security analysts the insights they need to device effective threat mitigation strategies. Such strategies empower...

Large Language Models for Security Operations Centers: a Comprehensive Survey

Large Language Models LLMs have emerged as powerful tools capable of understanding and generating human-like text, offering transformative potential across diverse domains. The Security Operations Center SOC, responsible for safeguarding digital infrastructure, represents one of these domains. SO...

A Cyber-Twin Based Honeypot for Gathering Threat Intelligence

Critical Infrastructure CI is prone to cyberattacks. Several techniques have been developed to protect CI against such attacks. In this work, we describe a honeypot based on a cyber twin for a water treatment plant. The honeypot is intended to serve as a realistic replica of a water treatment pla...

Notes of cyber inspector: three clusters of threat in cyberspace

Hacktivism and geopolitically motivated APT groups have become a significant threat to many regions of the world in recent years, damaging infrastructure and important functions of government, business, and society. In late 2022 we predicted that the involvement of hacktivist groups in all major...