n-days-poc-benchmark-and-dataset

ICS N-Day Vulnerability PoC Benchmark Suite A structured coll...

From transparency to action: What the latest Microsoft email security benchmark reveals

In our last benchmarking post, Clarity in complexity: New insights for transparent email security ,1 we shared why transparency matters more than ever in email security and how clear, consistent benchmarking helps security teams cut through noise and make confident decisions. Today, we’re...

PQC-LEO: An Evaluation Framework for Post-Quantum Cryptographic Algorithms

Advances in quantum computing threaten digital communication security by undermining the foundations of current public-key cryptography through Shor's quantum algorithm. This has driven the development of Post-Quantum Cryptography PQC, a new set of algorithms resistant to quantum attacks. While...

Quantifying Frontier LLM Capabilities for Container Sandbox Escape

Large language models LLMs increasingly act as autonomous agents, using tools to execute code, read and write files, and access networks, creating novel security risks. To mitigate these risks, agents are commonly deployed and evaluated in isolated "sandbox" environments, often implemented using...

Why Intelligent Contract Solutions Are Replacing Traditional CLM Systems

Intelligent contract solutions replace traditional CLM by adding AI analysis, benchmarking, and risk insights that speed reviews, reduce delays, and improve decisions...

Introducing AI Cyber Model Arena: A Real-World Benchmark for AI Agents in Cybersecurity

Wiz Research’s AI Cyber Model Arena benchmarks offensive AI security on 257 real-world challenges zero-days, CVEs, API/web, and cloud across AWS/Azure/GCP/K8s demonstrating what AI models and agents can really do...

Next-Generation Cyberattack Detection with Large Language Models: Anomaly Analysis across Heterogeneous Logs

This project explores large language models LLMs for anomaly detection across heterogeneous log sources. Traditional intrusion detection systems suffer from high false positive rates, semantic blindness, and data scarcity, as logs are inherently sensitive, making clean datasets rare. We address...

AI-Driven Cybersecurity Threats: A Survey of Emerging Risks and Defensive Strategies

Artificial Intelligence's dual-use nature is revolutionizing the cybersecurity landscape, introducing new threats across four main categories: deepfakes and synthetic media, adversarial AI attacks, automated malware, and AI-powered social engineering. This paper aims to analyze emerging risks,...

AutoDFBench 1.0: A Benchmarking Framework for Digital Forensic Tool Testing and Generated Code Evaluation

The National Institute of Standards and Technology NIST Computer Forensic Tool Testing CFTT programme has become the de facto standard for providing digital forensic tool testing and validation. However to date, no comprehensive framework exists to automate benchmarking across the diverse forensi...

Clarity in complexity: New insights for transparent email security

As email threats grow more sophisticated and layered security architectures become more common, organizations need clear, data-driven insights to evaluate how their security solutions perform together. Benchmarking plays a critical role in helping security leaders understand not just individual...

Clarity in complexity: New insights for transparent email security

As email threats grow more sophisticated and layered security architectures become more common, organizations need clear, data-driven insights to evaluate how their security solutions perform together. Benchmarking plays a critical role in helping security leaders understand not just individual...

Constructing and Benchmarking: A Labeled Email Dataset for Text-Based Phishing and Spam Detection Framework

Phishing and spam emails remain a major cybersecurity threat, with attackers increasingly leveraging Large Language Models LLMs to craft highly deceptive content. This study presents a comprehensive email dataset containing phishing, spam, and legitimate messages, explicitly distinguishing betwee...

StealthCup: Realistic, Multi-Stage, Evasion-Focused CTF for Benchmarking IDS

Intrusion Detection Systems IDS are critical to defending enterprise and industrial control environments, yet evaluating their effectiveness under realistic conditions remains an open challenge. Existing benchmarks rely on synthetic datasets e.g., NSL-KDD, CICIDS2017 or scripted replay frameworks...

Benchmarking NVIDIA RTX Pro 6000 Blackwell on Akamai Cloud

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ThreatIntel-Andro: Expert-Verified Benchmarking for Robust Android Malware Research

The rapidly evolving Android malware ecosystem demands high-quality, real-time datasets as a foundation for effective detection and defense. With the widespread adoption of mobile devices across industrial systems, they have become a critical yet often overlooked attack surface in industrial...

Microsoft raises the bar: A smarter way to measure AI for cybersecurity

ExCyTIn-Bench is Microsoft’s newest open-source benchmarking tool designed to evaluate how well AI systems perform real-world cybersecurity investigations.1 It helps business leaders assess language models by simulating realistic cyberthreat scenarios and providing clear, actionable insights into...

EUVD-2009-0324

Malware in sbrugna...

Enhancing Automotive Security with a Hybrid Approach Towards Universal Intrusion Detection System

Security measures are essential in the automotive industry to detect intrusions in-vehicle networks. However, developing a one-size-fits-all Intrusion Detection System IDS is challenging because each vehicle has unique data profiles. This is due to the complex and dynamic nature of the data...

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...

End-To-End Co-Simulation Testbed for Cybersecurity Research and Development in Intelligent Transportation Systems

Intelligent Transportation Systems ITS have been widely deployed across major metropolitan regions worldwide to improve roadway safety, optimize traffic flow, and reduce environmental impacts. These systems integrate advanced sensors, communication networks, and data analytics to enable real-time...