Operation-Molasses

🍯 OPERATION MOLASSES PEKMEZ Zencefil Efendi's Cyber Dow...

DeepStage: Learning Autonomous Defense Policies against Multi-Stage APT Campaigns

This paper presents DeepStage, a deep reinforcement learning DRL framework for adaptive, stage-aware defense against Advanced Persistent Threats APTs. The enterprise environment is modeled as a partially observable Markov decision process POMDP, where host provenance and network telemetry are fus...

Turning threat reports into detection insights with AI

Security teams routinely need to transform unstructured threat knowledge, such as incident narratives, red team breach-path writeups, threat actor profiles, and public reports into concrete defensive action. The early stages of that work are often the slowest. These include extracting tactics,...

Turning threat reports into detection insights with AI

Security teams routinely need to transform unstructured threat knowledge, such as incident narratives, red team breach-path writeups, threat actor profiles, and public reports into concrete defensive action. The early stages of that work are often the slowest. These include extracting tactics,...

Endpoint Security Agent: A Comprehensive Approach to Real-Time System Monitoring and Threat Detection

As cyber threats continue to evolve in complexity and frequency, robust endpoint protection is essential for organizational security. This paper presents "Endpoint Security Agent: A Comprehensive Approach to Real-time System Monitoring and Threat Detection" a modular, real-time security solution...

offensive-toolkit

Offensive Security Toolkit A comprehensive, modular Python fr...

Code Agent Can Be an End-To-End System Hacker: Benchmarking Real-World Threats of Computer-Use Agent

Computer-use agent CUA frameworks, powered by large language models LLMs or multimodal LLMs MLLMs, are rapidly maturing as assistants that can perceive context, reason, and act directly within software environments. Among their most critical applications is operating system OS control. As CUAs in...

Towards Effective Identification of Attack Techniques in Cyber Threat Intelligence Reports Using Large Language Models

This work evaluates the performance of Cyber Threat Intelligence CTI extraction methods in identifying attack techniques from threat reports available on the web using the MITRE ATT&CK framework. We analyse four configurations utilising state-of-the-art tools, including the Threat Report ATT&CK...