Instructors: Silvio La Porta & Antonio Villani
Dates: June 24 to 27 2024
Capacity: 25
The course will present an in-depth description of the techniques implemented in modern malware to evade defenders and security products (such as AV, IPS, IDS, EDR), and how attackers design and operate their implants in order to ensure a prompt redeployment after a detection or a public disclosure by researchers or security vendors.
The course will also cover real-world scenarios that impair (effectively slow-down or dissuade) reverse engineering efforts and make the job of first responders tougher. The techniques will be demonstrated in two ways: first, by reversing real malware samples, and then by re-implementing an improved version of the malware code. The training is designed from an attacker's point of view, teaching red-teams how to make their implants stealthier, but it will also teach defenders how to deal with the anti-reversing and the OPSEC techniques demonstrated in class.
The course focuses primarily on Windows malware and on the analysis, tweaking and re-purposing of real malware samples. Participants will be provided with plenty of custom code to facilitate the understanding of complex malware techniques.
As part of the course, theory sessions will be followed by exercises where participants will reverse and re-implement specific parts of real malware in order to fully understand the hidden corners of all the techniques involved. 50% of the course will be dedicated to hands-on labs that will show how to translate the theory principles into practice.
Labs are designed to provide flexibility in terms of complexity and include bonus tracks to ensure that you always feel engaged and have something interesting to explore and learn.
Almost all labs are provided in dual versions (reverse and development). Students can choose which version to approach.
To develop and test the techniques described during the theory sessions, students will be provided with the source-code of our training agent and its corresponding C2.
Developers and Reverse engineers who want to understand the tradecraft from a different point of view, red-team members who want to go beyond using third-party implants, and researchers who want to develop anti-detection techniques of real malware/apt.
Dr. Silvio La Porta is CEO and Co-Founder at RETooling defining and developing Threat Actor emulation platform enabling red team to recreate a realist attack scenario. Previously he was a Senior Cyber Security Architect designing security products and researching advanced detection technology for complex malware/APT. Silvio previously was a lead research scientist with EMC Research Europe based in the Centre of Excellence in Cork, Ireland. His primary research focus areas were real-time network monitoring and data analysis in smart grids to detect malware activity in SCADA systems and corporate networks. He was also leading Security Service Level Agreement (Sec-SLA) and end user security/privacy protected data store projects for hybrid Cloud environment. He is a frequent speaker in professional and industry conferences. Before joining EMC, Silvio worked as a Malware Reverse Engineer in Symantec's Security Response team in Dublin, Ireland. Silvio holds a PhD in Computer Network Security from the University of Pisa, Italy.
Dr. Antonio Villani is the Co-Founder of RETooling. He is working full-time on the development of red-team and adversary emulation capabilities for his company. Previously he spent most of his time in the blueteam, reversing high level implants for top tier customers and providing detailed information to support cyber-defense and cyber threat intelligence teams. Now he analyzes complex implants to gain a deep understanding of the TTPs used by threat actors and to provide a high-quality reimplementation of them. As a researcher he published in top tier conferences and journals, and he participated in European research projects in the field of cyber resilience and data security. During his PhD he worked in the field of malware research and digital forensics.
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