CSC 471 Modern Malware Analysis

2025-Spring Course Website

Instructor: Si Chen

Course Logo

About Malware and Malware Analysis

Malware, a term used to describe various types of malicious software, poses a significant threat to both personal privacy and computer security. ...

Course Description

This course aims to provide students with a comprehensive understanding of modern malware analysis techniques ...

Expected Background

No prerequisite for graduate students, although sufficient security background is expected. ...

  • Basic programming concepts
  • Knowledge with the C programming language, including pointers, arrays, loops, function calls, etc.
  • Familiar with Unix/Linux including the command-line shell and gdb
  • Familiar with Intel x86 assembly language and architecture
  • Familiar with web programming concepts (HTML, HTTP, TCP, network communications)

Textbook

No Textbook

Reference book:

  1. Monnappa K A, Learning Malware Analysis: Explore the concepts, tools, and techniques ... ISBN 978-1788392501
  2. Michael Sikorski, Andrew Honig, Practical Malware Analysis: The Hands-On Guide to Dissecting Malicious Software, ISBN 978-1593272906

Course Content

# Date Topic Slides Supporting Materials
Class 1 Jan 21, 2025 Introduction ch01.pdf
Class 2 Jan 23, 2025 Basic Concepts, DLL Injection (1) ch02.pdf
Class 3 Jan 28, 2025 IA32 Registers & Byte Ordering ch03.pdf
Class 4 Jan 30, 2025 X86 ASM ch04.pdf
Lab 1
(10 points)
Feb 04, 2025 Lab1: OllyDbg and DLL Injection
lab1.pdf
Class 5 Feb 06, 2025 Stack and Stack Frame (1) ch05.pdf
Class 6 Feb 11, 2025 Stack Frame (2) ch06.pdf
Lab 2
(10 points)
Feb 13, 2025 Lab2: Stack, Stack Frame & CrackMe
lab2.pdf
Class 7 Feb 13, 2025 Static Analysis & Dynamic Analysis (1) ch07.pdf
Class 8 Feb 18, 2025 Static Analysis & Dynamic Analysis (2): (De)Obfuscation ch08.pdf
Class 9 Feb 20, 2025 Windows Message Hooks ch09.pdf
Class 10 Feb 25, 2025 Windows API Hooks ch10.pdf
Class 11 Feb 27, 2025 PE Structure (1) ch11.pdf
Class 12 Mar 4, 2025 PE Structure (2) ch12.pdf
Lab 3
(10 points)
Mar 06, 2025 Lab3: Build a heuristic malware detection system
lab3.pdf
Class 13 Mar 06 & 18, 2025 Code Injection ch13.pdf
Class 14 Mar 25 & 27, 2025 Worms (1 - 2): CVE-2008-4250 (MS08-067) ch14.pdf
  • CVE-2008-4250.zippassword:infected
  • CVE-2008-4250 Static Analysis Report
  • conflicker.zip password:infected
  • ms08_067_SMB.pcapng.zip
  • Class 15 Apr 01, 2025 Anti-virus Software, Dynamic Heuristic Analysis ch15.pdf
  • [Video]
  • ransomware.zip (Experiment 1) password:infected
  • apivirus.zip (Experiment 2)
  • Lab 4
    (10 Points)
    Apr 01, 2025 Lab 4: Build a Dynamic Heuristic Analysis Tool for Detection of Unknown Malware
    lab4.pdf
  • ransomware.zip password:infected
  • Class 16 Apr 03, 2025 Worms (3): Conficker Worm ch16.pdf
  • CVE-2008-4250.zip
  • CVE-2008-4250 Static Analysis Report
  • conficker.zip password:infected
  • Class 17 Apr 08, 2025 Stealth process ch17.pdf
  • [Video]
  • StealthProcess1.zip password:infected
  • stealth.cpp
  • Class 18 Apr 10, 2025 Kernel Rootkit (1): Introduction ch18.pdf
  • [Video]
  • Class 19 Apr 15, 2025 Kernel Rootkit (2): SSDT Hooking ch19.pdf
  • [Video]
  • SSDTHook.zip password:infected
  • Lab 5
    (10 points)
    Apr 17, 2025 Lab5: SSDT Hooking
    lab5.pdf
  • lab5.zip
  • Class 20 Apr 17, 2025 Volatility, Stuxnet ch20.pdf
  • [Video]
  • stuxnet.vmem
  • Final Project
    (25 Points)
    Apr 22, 2025 Malware Analysis: Zeus
    FinalProject.pdf
  • zeus.vmem
  • zeus source code -- client side
  • Tutorials and Supporting Materials

    Presentation Rubric (total 15%)

    Category Percentage Criteria
    Content 8%
    • Accuracy: All content throughout the presentation is accurate, and there are no factual errors.
    • Relevance: The presentation covers the assigned topic comprehensively and relevantly.
    Presentation 5%
    • Organization: The presentation is well-structured, with a clear introduction, body, and conclusion.
    • Technical clarity: Technical terms are well-defined and explained in a clear and concise manner.
    • Depth: The presentation demonstrates substance and depth, going beyond superficial explanations.
    Q&A Session 1%
    • Knowledge: The student demonstrates full knowledge of the topic, answering questions confidently and accurately.
    Peer Engagement 1%
    • Preparation: The student has prepared questions for other groups and shows a proactive engagement in the learning process.