Demystifying Feature Engineering in Malware Analysis of API Call Sequences

Machine learning ML has been widely used to analyze API call sequences in malware analysis, which typically requires the expertise of domain specialists to extract relevant features from raw data. The extracted features play a critical role in malware analysis. Traditional feature extraction is...

Improving the Identification of Real-World Malware's DNS Covert Channels Using Locality Sensitive Hashing

Nowadays, malware increasingly uses DNS-based covert channels in order to evade detection and maintain stealthy communication with its command-and-control servers. While prior work has focused on detecting such activity, identifying specific malware families and their behaviors from captured...

HyMAD: A Hybrid Multi-Activity Detection Approach for Border Surveillance and Monitoring

Seismic sensing has emerged as a promising solution for border surveillance and monitoring; the seismic sensors that are often buried underground are small and cannot be noticed easily, making them difficult for intruders to detect, avoid, or vandalize. This significantly enhances their...

Adaptive Dual-Layer Web Application Firewall (ADL-WAF) Leveraging Machine Learning for Enhanced Anomaly and Threat Detection

Web Application Firewalls are crucial for protecting web applications against a wide range of cyber threats. Traditional Web Application Firewalls often struggle to effectively distinguish between malicious and legitimate traffic, leading to limited efficacy in threat detection. To overcome these...

AFLGopher: Accelerating Directed Fuzzing Via Feasibility-Aware Guidance

Directed fuzzing is a useful testing technique that aims to efficiently reach target code sites in a program. The core of directed fuzzing is the guiding mechanism that directs the fuzzing to the specified target. A general guiding mechanism adopted in existing directed fuzzers is to calculate th...

Binary and Multiclass Cyberattack Classification on GeNIS Dataset

The integration of Artificial Intelligence AI in Network Intrusion Detection Systems NIDS is a promising approach to tackle the increasing sophistication of cyberattacks. However, since Machine Learning ML and Deep Learning DL models rely heavily on the quality of their training data, the lack of...

Whisper Leak: A Side-Channel Attack on Large Language Models

Large Language Models LLMs are increasingly deployed in sensitive domains including healthcare, legal services, and confidential communications, where privacy is paramount. This paper introduces Whisper Leak, a side-channel attack that infers user prompt topics from encrypted LLM traffic by...

Towards Ultra-Low Latency: Binarized Neural Network Architectures for In-Vehicle Network Intrusion Detection

The Control Area Network CAN protocol is essential for in-vehicle communication, facilitating high-speed data exchange among Electronic Control Units ECUs. However, its inherent design lacks robust security features, rendering vehicles susceptible to cyberattacks. While recent research has...

CVE-2025-54479

When a classification profile is configured on a virtual server without an HTTP or HTTP/2 profile, undisclosed requests can cause the Traffic Management Microkernel TMM to terminate. Note: Software versions which have reached End of Technical Support EoTS are not evaluated...

EUVD-2025-34638

When a classification profile is configured on a virtual server without an HTTP or HTTP/2 profile, undisclosed requests can cause the Traffic Management Microkernel TMM to terminate. Note: Software versions which have reached End of Technical Support EoTS are not evaluated...

bluescan

BlueScan - Bluetooth Security Scanner A comprehensive Bluetoo...

CVE-2025-54479

When a classification profile is configured on a virtual server without an HTTP or HTTP/2 profile, undisclosed requests can cause the Traffic Management Microkernel TMM to terminate. Note: Software versions which have reached End of Technical Support EoTS are not evaluated...

CVE-2025-54479

CVE-2025-54479 affects F5 BIG-IP BIG-IP PEM/Traffic Management Microkernel (TMM) when a classification profile is configured on a virtual server without an HTTP or HTTP/2 profile, causing TMM termination and potential DoS. Multiple sources corroborate the issue and list affected products/branches...

CVE-2025-54479 BIG-IP PEM vulnerability

When a classification profile is configured on a virtual server without an HTTP or HTTP/2 profile, undisclosed requests can cause the Traffic Management Microkernel TMM to terminate. Note: Software versions which have reached End of Technical Support EoTS are not evaluated...

CVE-2025-54479 BIG-IP PEM vulnerability

When a classification profile is configured on a virtual server without an HTTP or HTTP/2 profile, undisclosed requests can cause the Traffic Management Microkernel TMM to terminate. Note: Software versions which have reached End of Technical Support EoTS are not evaluated...

Lightweight CNN-Based Wi-Fi Intrusion Detection Using 2D Traffic Representations

Wi-Fi networks are ubiquitous in both home and enterprise environments, serving as a primary medium for Internet access and forming the backbone of modern IoT ecosystems. However, their inherent vulnerabilities, combined with widespread adoption, create opportunities for malicious actors to gain...

EUVD-2021-1504

Malware in sbrugna...

EUVD-2020-24515

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EUVD-2019-16169

Malware in sbrugna...

EUVD-2006-4647

Malware in sbrugna...