Lenny Zeltser

OCTOBER 13, 2020

To guide you through the process of examining malware, REMnux documentation lists the installed tools by category. In addition to providing numerous tools as part of the REMnux distro, the project also offers several malware analysis tools as Docker images.

Malware 145

Malware Engineering Software Information Security 145

Lenny Zeltser

JANUARY 6, 2021

Malware analysis sits at the intersection of incident response, forensics, system and network administration, security monitoring, and software engineering. As someone who’s helped thousands of security professionals learn how to analyze malware at SANS Institute , I have a few tips for how you can get started.

Malware 145

Malware Software Engineering Information Security 145

Lenny Zeltser

MARCH 2, 2019

You’ll want snapshots when examining malware, so you can revert the VM’s state to start a new investigation or backtrack an analysis step. Step 3: Update the VM and Install Malware Analysis Tools. You can use this connection to update the OS to the latest patch level and install malware analysis tools.

Malware 112

Malware Software Engineering Antivirus 112

Security Affairs

APRIL 4, 2019

You can download the GHIDRA source code and its component from the following links: Github — source code Download GHIDRA 9.0 — software package, slides, and exercises Installation Guide — basic usage documentation Cheat Sheet — keyboard shortcuts Issue Tracker — report bugs.

Engineering 97

Engineering Malware Hacking Software 97

Lenny Zeltser

SEPTEMBER 7, 2017

This cheat sheet outlines tips for reversing malicious Windows executables via static and dynamic code analysis with the help of a debugger and a disassembler. Overview of the Code Analysis Process. Perform automated and manual behavioral analysis to gather additional details. Additional Code Analysis Tips.

Engineering 111

Engineering Malware Software Information Security 111

Security Boulevard

APRIL 5, 2022

Microsoft has a great cheat sheet that highlights common approaches:??. Principal Component Analysis. Principal component analysis (PCA) is commonly used for dimensionality reduction , which involves projecting a data set to a lower-dimensional space while attempting to explain most of the variance of the original data.

Architecture 69

Architecture InfoSec Risk Technology 69