331 - Network and Web Security - 2025

• Overview. This week we cover some general security topics which are relevant to the rest of the course. In order to secure a system, we want to be able to discover, fix and, even better, prevent security vulnerabilities. Attackers attempt to install malware on their victims, and use malware itself to implement further attacks. Although malware is not the focus of this course, we need to have some familiarity with it, in order to understand the objectives and techniques used to attack networks and web applications. Threat modelling is a conceptual tool that we will use in the rest of the course to assess the security of applications and systems. Note that this week is a gentle introduction to the course, the pace and difficulty will increase as we get into technical topics.
• Topics
  • 1 Vulnerabilities
    • Read Chapter 2 of Professional Penetration Testing
  • 2 Malware
    • Optional reading
      • Analysis of a Botnet Takeover
      • End-to-End Analysis of the Spam Value Chain
      • Understanding the Mirai Botnet
      • Browse the Evolution of Exploit Kits working paper
  • 3 Threat Modelling
    • Read Chapters 1-4 of Threat modelling – Designing for security
• Activities
  • Lab on Monday
    • Guide: Install VirtualBox and Kali
  • In class session on Thursday
    • Overview, Q&A, demos
    • Tutorial 1: Threat Modelling

Sergio Maffeis. Sergio is a senior lecturer in Computer Security at Imperial, where he leads the Security and Machine Learning Lab. He received his PhD from Imperial and his MSc from University of Pisa, Italy. Maffeis' research interests include security, machine learning, formal methods, and programming languages. You can find out more from his home page.

Antoine Vianey-Liaud. Antoine manages a team of threat hunters at Crowdstrike, uncovering sophisticated adversaries within the networks of a large customer base. He received his MSc from Imperial College London in 2016, delivering an ISO and thesis under the supervision of Dr Maffeis. His interests include intrusion detection (using security domain knowledge, statistical and data science methods), capture the flag competitions, and security in all its forms.

Charlie Hothersall-Thomas. Charlie is a Director of Engineering at Netcraft, where he leads the DevOps division. Prior to this he worked as a developer on a variety of Netcraft's anti-cybercrime products. His technical expertise includes web security, TLS and PKI, networking, Linux system administration and Tor. He graduated in 2014 with a BEng in Computing from Imperial College London, where he started BrowserAudit as his final year project.

Ibrahim ElSayed. Ibrahim is a Senior Staff Security Engineer at Lacework. He obtained his BSc in Computer Engineering from The American University in Cairo and his MSc in Information Security from Royal Holloway, University of London. Ibrahim focuses on using program analysis to scale security vulnerability detection and prevention. He is currently leading the code security team at Lacework, creating tools to enable developers and security teams to detect and prevent impactful vulnerabilities. Previously, he spent 8 years at Meta, building various static analysis tools such as Zoncolan, Pysa, and Mariana-Trench to analyze hundreds of millions of lines of Meta's codebase, including PHP, Python, and Java.

Joseph Katsioloudes. Joseph works for the GitHub Security Lab, and was previously a Security Consultant at IBM. He obtained an MSc in Cyber Security Engineering from the University of Warwick and an MEng in Computing from Imperial College London. His experience in security stems from summer internships and own initiatives to problem-solve. Highlights include the disclosure of a zero-day vulnerability for a top ten cryptocurrency during his final year at Imperial College, the GCHQ security accreditation, software contributions to open-source tools and advanced attack simulations.

Adbdullah Adlaihan. Abdullah is a PhD student at Imperial College London under the supervision of Dr. Maffeis. He received his MSc in computer science from Georgia Institute of Technology, and his BSc in computer science from King Saud University. Abdullah's focus is on utilizing Large Language Models (LLMs) for systems security.

Adam Jones. Adam is a PhD student at Imperial under the supervision of Dr. Maffeis and Dr. Zizzo. He received his MEng from Imperial in Computer Science. Adam's research is focused on the security of foundation models that generate code, in particular researching attacks and defenses in the domains of model poisoning and prompt injection.

Eman Maali. Eman is a PhD student at Imperial College London under the supervision of Prof. McCann. Eman's Ph.D. focus is IoT Security, in which she is developing an anomaly detector for IoT networks. In 2017, Eman completed her MSc in Electromagnetic Sensor Networks at the University of Birmingham. The focus of the Master's was on electromagnetic, antennas, propagation, computer communications networks, and RF and microwave engineering. Moreover, Eman completed her BA in Computer Systems Engineering from Birzeit University in Palestine.

Fahad Alotaibi. Fahad is a PhD student at Imperial College London under the supervision of Dr. Maffeis. He received his MSc from The University of York (UK) in Cyber Security, and his BCs from Shaqra University (KSA) in Computer Science. Fahad’ research is focused on robusting deep learning-based security applications againsts evasion attacks and concept drift. Fahad is also interested in other areas such as digital forensics and ransomware prevention.

Myles Foley. Myles is a PhD student at Imperial College London under the supervision of Dr. Maffeis. He received his MEng from University College London in Electronic Engineering with Computer Science, earning the ‘Outstanding MEng Graduating Student’ prize. Myles’ research is focused at novel - and exciting - ways of applying reinforcement learning to problems in cyber security.

Xin Fan Guo. Xin Fan is a PhD student in the Safe and Trusted AI CDT, a joint program between King’s College London and Imperial College London, supervised by Dr. Pierazzi and Dr. Maffeis. She holds a BSc in Computer Science from King’s College London. Her research focuses on applying symbolic AI to enhance network security.