The course has seven (7) lectures, six (6) laboratory exercises, and 6 Moodle exams. The course does not contain final coursework; instead see the course Computer Security Project 521253S for project work .

Lectures are handling topics from a high perspective and they are not going technically deep. Moodle exams are based on the lectures.

Laboratory exercises are thought of as independent packages: containing theory and exercises, and going technologically very deep.

Lab materials are located in their corresponding folders:

1. Fuzzing lab

2. Network lab

3. Botnets and malware lab

4. Shellcoding lab

5. ChipWhisperer lab

6. Digital forensics lab

See the section about virtual machines to set up a laboratory environment in the University classes or at home.

To pass this course with grade 1, you have to pass the Moodle exams.

To get a better grade, you have to do some laboratory exercises. You can somewhat decide what grade you will earn on this course because you can (hopefully!) see from the beginning how much work is required for each grade. All laboratory tasks are optional and total points from those will determine your grade. The grading section is presented here.

Labs are divided into levels (which is the corresponding grade/points on that lab), level may contain one or several tasks. The amount of tasks which are required for each level/grade is defined in the grading section of the corresponding lab. Tasks are designed to become somewhat harder and time-consuming on every level. Getting 2-3 points from each lab is doable for the average student with a reasonable amount of work, 4-5 points require a lot more time and skill.

See deadlines section for information about deadlines of lab works.

• Enroll in the course

• Find course's Moodle page from University's Moodle

• Find a link where you can receive and create a private repository containing all the return template folders. You are expected to answer for given templates and store your actual work in this repository.

• Create a GitHub account, if you don't have one already, and create this private repository from the link.

• You can see deadlines below. They are the same in Moodle. There might be exceptions for ChipWhisperer.

• Complete as many tasks as you wish and update your repository accordingly. Check the grading table found in each labs instructions on what you have to complete to earn the grade of your choosing

• Push your changes to your repository before the deadline, and return the link to your repository to the corresponding return box of the lab in Moodle.

Check cheat sheet if you need a refresher on how to use Git. Some basic commands below

git add </path/filename>
git commit -m "<message>"
git push

As described earlier, you have to pass Moodle exams to pass the course. You can have higher grades by doing lab works.

You can get up to 5 points in each lab (A total of 30 points). The grade is determined based on those points.

Each week has a deadline for the corresponding lab exercise.

Laboratory assignments utilize a set of various tools and also handle potentially malicious files in Lab 3. Thus it is recommended to handle files in an isolated environment, or at least the execution of tools happens in an isolated environment at some level.

A straightforward solution for this is pre-configured virtual machines - if you have enough disk space and performance on your computer to use them. For Windows users - this is the most convenient way.

If you are already using Linux/macOS-based operating system, the other option is to use a specific tool called cincan-command. It is a wrapper for Docker to run a different kinds of tools in isolated matter. It makes the installation of a wide variety of tools easier while providing some level of isolation as well. Most of the tools used in exercises are usable with it. It requires that Python 3.6+ and Docker are functioning in your system. Installation steps can be found from the documentation.

If you want, you can install packages in a normal way, or just use the provided virtual machine on the Linux host as well.

Note If you are using the following virtual machines on your own PC, they are pre-configured with 4GB of RAM for VMware player. So if you have less than 8 GB of RAM in your PC, you might want to reduce this pre-configured RAM.

Each lab utilizes one of the virtual machines below:

• Kali Linux - for shellcoding, fuzzing, web security, and malware lab

  • User: kali
  • Password: kali

• ChipWhisperer Jupyter virtual machine

  • Both VMWare and VirtualBox versions available, more accurate information about setup on lab 5 page

Direct download links for these machines are provided on the Moodle page!

They are 7zip compressed. Run machine from .vmx file with VMware Player/VMware Workstation.

These virtual machines are located on the University network drive, in case the download speed on direct URLs is slow.

Check here

If you are on the University premises and can access to laboratory computer which has VMware installed.

This is the recommended method, if your computer does not have enough free space on Windows drive. Kali Linux requires around 30GB at the moment and ChipWhisperer around 7GB. You can launch the virtual machine with following PowerShell commands.

1. Mount network drive (If the domain 'kaappi' is not found, you can use "\\cifs.isi.oulu.fi\Virtuaalikoneet$")

New-PSDrive -Persist -Name "Z" -PSProvider "FileSystem" -Root "\\kaappi\Virtuaalikoneet$"

2. Create temprary directory (Correct path is important!)

New-Item -Path "C:\Temp" -Name "Kali" -ItemType "directory"

3. Copy VMware configuration file from the network drive

Copy-Item "Z:\VMware\CompSec\Kali_x64_2021\Kali-Linux_nonpersistent.vmx" -Destination "C:\Temp\Kali"

4. Launch the virtual machine

Start-Process -FilePath "C:\Temp\Kali\Kali-Linux_nonpersistent.vmx"

If you have enough space on your lab computer, and you are not too hesitant to start, the recommended way is to copy the virtual machine from the network drive, and then start it locally. This way changes are not lost in the shutdown.

You can mount the network drive as above.

There should be now new Z: drive, named Virtuaalikoneet$

And virtual machines are located in:

Virtuaalikoneet$ -> VMware -> CompSec

Copy selected virtual machine to C:\Temp folder.

Run machine from .vmx file, which does not say 'nonpersistent'.

When the virtual machine asks if you have copied or moved the machine, press "I copied it".

You can mount network drive into your own PC, if it has been connected to Eduroam .

After you have successfully connected to the network, you can mount the network drive as follows. If any credentials are asked, the username is [email protected]

Open Windows cmd:

net use z: "\\kaappi\Virtuaalikoneet$"

The drive should be mounted after giving correct credentials.

If the domain kaappi is not found, try to use the following instead:

net use z: "\\cifs.isi.oulu.fi\Virtuaalikoneet$" 

If you have mnt folder in root directory, and package cifs-utils is installed, you can:

sudo mount -t cifs //kaappi/Virtuaalikoneet$ /mnt/ -o [email protected]

Depending on your versions, you might need to play with 'sec' -variable, for example Ubuntu 16.04 might require:

sudo mount -t cifs //kaappi/Virtuaalikoneet$ /mnt/ -o [email protected],sec=ntlm

Passwords should be prompted.

Virtual machines are located in:

Virtuaalikoneet$ -> VMware -> CompSec

If you are using QEMU/KVM, you cannot directly load the .vmdk file to run the virtual machines as-is due to a lack of support for split .vmdk files.

In order to combine the .vmdk disk parts into a format QEMU can load you need to convert them into a .qcow2 disk file using qemu-img:

qemu-img convert Kali.vmdk Kali.qcow2

If direct download URLs are not functioning for any reason and if you are not able to get into University to copy virtual machines from a network drive by using Lab computer, you can do it remotely as well. This requires setting up VPN - connection to the University network. This can be acquired by following the guidelines presented here. OpenVPN software is being used.

After you have successfully connected to the network, instructions are the same as here.