ai-security-battle

🤖 AI Security Battle System Red Team vs Blue Team: Adversarial ML Combat Simulation A comprehensive adversarial machine learning security simulation where Red Team attackers battle against Blue Team defenders in a 30-minute AI/ML security warfare scenario. 🎯 Project Overview This system simulates...

0xsp-Mongoose

Support the project for continuous development ETH 0xf340c15c5e669a4ababab856e9f2bccd659d6e42 0xsp Mongoose RED for Windows Current Release 2.2.0 0xsp mongoose red version is provided to assist your needs during cyber security simulation, by using this version you will be able to audit a targeted...

siras

SIRAS v3.0 is a modern Security Incident Response Automated Simulation framework designed to manage red teaming exercises as code. You can execute controlled security simulations that test your Incident Response plan in realistic scenarios. The main goal of SIRAS is to provide red teaming exercis...

Beyond Centralized Policy Decision Points: Decentralized Sticky Policy Authorization through Evidence Quorums

Sticky policies remain attached to protected data so that access restrictions can persist across systems, yet request-time authorization often still depends on a centralized Trusted Authority or Policy Decision Point PDP. This paper presents SPEAR-Q, a decentralized framework in which independent...

Fingerprint-Driven Automation: Coupling Reconnaissance with POC Verification

In the field of network security confrontation, reconnaissance is the first and most critical step. Accurate, efficient, and comprehensive reconnaissance can help network security workers more fully understand the target's current state, identify potential weaknesses, and formulate a targeted...