James Fitts, Chris Fennel (Walmart)

Red Team campaigns simulate real adversaries and provide real value to the organization by exposing vulnerable infrastructure and processes that need to be improved. The challenge is that as organizations scale in size, time between campaign retesting increases. This can lead to gaps in ensuring coverage and finding emerging issues. Automation and simulation of adversarial attacks can be created to address the scale problem. Collecting libraries of Tactics, Techniques and Procedures (TTPs) and testing them via adversarial emulation software. Unfortunately, automation lacks feedback and cannot analyze the data in real time with each test.

To address this problem, we introduce RAMPART (Repeated And Measured Post Access Red Teaming). RAMPART campaigns are very quick campaigns (1 day) meant to bridge the gap between the automation of Red Team simulations and full blown Red Team campaigns. The speed of these campaigns comes from pre-built playbooks backed by Cyber Threat Intelligence (CTI) research. This approach enables a level of freedom to make decisions based on the data the red team analyst sees from their tooling and allows testing further in the attack chain to test detections that could be missed otherwise.

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SigmaDiff: Semantics-Aware Deep Graph Matching for Pseudocode Diffing

Lian Gao (University of California Riverside), Yu Qu (University of California Riverside), Sheng Yu (University of California, Riverside & Deepbits Technology Inc.), Yue Duan (Singapore Management University), Heng Yin (University of California, Riverside & Deepbits Technology Inc.)

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ActiveDaemon: Unconscious DNN Dormancy and Waking Up via User-specific...

Ge Ren (Shanghai Jiao Tong University), Gaolei Li (Shanghai Jiao Tong University), Shenghong Li (Shanghai Jiao Tong University), Libo Chen (Shanghai Jiao Tong University), Kui Ren (Zhejiang University)

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Before the Vicious Cycle Starts: Preventing Burnout Across SOC...

Kashyap Thimmaraju (Technische Universitat Berlin), Duc Anh Hoang (Technische Universitat Berlin), Souradip Nath (Arizona State University), Jaron Mink (Arizona State University), Gail-Joon Ahn (Arizona State University)

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