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Python | System hardening and compliance reports using Lynis
  • Last Updated : 16 May, 2019

Lynis is a battle-tested security tool for systems running Linux, macOS, or Unix-based operating system. It performs an extensive health scan of your systems to support system hardening and compliance testing. The project is open source software with the GPL license and available since 2007.

Since Lynis is flexible, it is used for several different purposes. Typical use cases for Lynis include:

  • Security auditing
  • Compliance testing (e.g. PCI, HIPAA, SOx)
  • Penetration testing
  • Vulnerability detection
  • System Hardening

System hardening refers to securing your system from potential Threats and Vulnerabilities. Lynis can be used to generate a detailed report on various Threats and Vulnerabilities in your system. The user or System Administrator can then take the necessary actions to secure the system.

Lynis reports are hard to read and usually have a lot of information. Therefore, we use Bash and Python scripts to parse through the report, extract relevant information from the report such as warnings, suggestions and store them in an excel file as a report.

Prerequisites for Lynis –

    You must run a Linux/Unix based OS such as Ubuntu, Mac Os or any other Linux distribution.

  • Install Lynis on your system by cloning the github repository:
  • Install the pandas library using the command sudo pip3 install pandas .
  • Once you have installed Lynis on your system, navigate to the Lynis directory where you will find a bunch of files along with an executable file called Lynis.
  • Use the bash script (code is given below) to extract relevant information such as warning and suggestions given in the lynis report. create a file called and copy paste the bash code into that file and type: sudo ./ to run the bash script.
  • Run the Python script (code is given below) to clean and parse the extracted data and output the relevant information as an excel file.

Below are the Bash and Python scripts –

Bash Script:

# script to scrape/parse the report file and
# extract the relevant details and run the 
# python script to display the details in a server.
echo "running......"
echo ""
sudo ./lynis audit system --quick
# execute warnings. sudo ./
echo "Generating warnings"
echo ""
echo "warnings are: "
echo ""
sudo cat /var/log/lynis-report.dat | grep warning | sed -e "s/warning\[\]\=//g"
sudo cat /var/log/lynis-report.dat | grep warning | sed -e "s/warning\[\]\=//g" | cat > warnings.txt
echo ""
echo "warnings generated"
echo "output file: warnings.txt"
sudo chmod 755 warnings.txt
#execute suggestions.  sudo ./
echo "Generating suggestions"
echo ""
echo "suggestions are: "
echo ""
sudo cat /var/log/lynis-report.dat | grep suggestion | sed -e "s/suggestion\[\]\=//g"
sudo cat /var/log/lynis-report.dat | grep suggestion | sed -e "s/suggestion\[\]\=//g" | cat > suggestions.txt
echo ""
echo "suggestions generated"
echo "output file: suggestions.txt"
sudo chmod 755 suggestions.txt
# execute packages. sudo ./
echo "Generating packages"
echo ""
echo "packages are: "
echo ""
sudo cat /var/log/lynis-report.dat | grep installed_package | sed -e "s/installed_package\[\]\=//g"
sudo cat /var/log/lynis-report.dat | grep installed_package | sed -e "s/installed_package\[\]\=//g" | cat > packages.txt
echo ""
echo "packages generated"
sudo chmod 755 packages.txt
# execute shells.  sudo ./
echo "Generating avaliable shells"
echo ""
echo "shells are: "
echo ""
sudo cat /var/log/lynis-report.dat | grep available_shell | sed -e "s/available_shell\[\]\=//g"
sudo cat /var/log/lynis-report.dat | grep available_shell | sed -e "s/available_shell\[\]\=//g" | cat > shells.txt
echo ""
echo "shells generated"
echo "output file: shells.txt"
sudo chmod 755 shells.txt

Python script:

# importing libraries
import pandas as pd
from pandas import ExcelWriter
import os
# function to get the data.
def get_data():
    warnings = open('warnings.txt', 'r')
    suggestions = open('suggestions.txt', 'r')
    packages = open('packages.txt', 'r')
    shells = open('shells.txt', 'r')
    warn_data = warnings.readlines()
    sugg_data = suggestions.readlines()
    pack_data =
    shell_data = shells.readlines()
    return warn_data, sugg_data, pack_data, shell_data
def clean_data():
    warn, sugg, pack, shell = get_data()
    warn_clean = []
    for line in warn:
    for i in range(len(warn_clean)):
        warn_clean[i] = warn_clean[i][:2]
        # print(warn_clean[i])
    sugg_clean = []    
    for line in sugg:
    for i in range(len(sugg_clean)):
        sugg_clean[i] = sugg_clean[i][:2]
        # print(sugg_clean[i])
    pack_clean = []
    pack = pack.split('|')
    pack_clean = pack
    del pack_clean[0]
    shell_clean = []
    for i in range(len(shell)):
        # print(shell_clean[i])
    return warn_clean, sugg_clean, pack_clean, shell_clean
def convert_to_excel():
    warnings, suggestions, packages, shells = clean_data()
    warn_packages = []
    warn_text = []
    for i in range(len(warnings)):
    for i in range(len(warnings)):
    print(warn_packages, warn_text)
    warn = pd.DataFrame()
    warn['Packages'] = warn_packages
    warn['warnings'] = warn_text
    # warn.to_excel('warnings.xlsx', index = False)
    writer = ExcelWriter('warnings.xlsx')
    warn.to_excel(writer, 'report1', index = False)
    workbook =
    worksheet = writer.sheets['report1']
    # Account info columns
    worksheet.set_column('A:A', 15)
    # State column
    worksheet.set_column('B:B', 45)
    # Post code
    # worksheet.set_column('F:F', 10)
    sugg_packages = []
    sugg_text = []
    for i in range(len(suggestions)):
    for i in range(len(suggestions)):
    # print(sugg_packages, sugg_text)
    sugg = pd.DataFrame()
    sugg['Packages'] = sugg_packages
    sugg['suggestions'] = sugg_text
    writer1 = ExcelWriter('suggestions.xlsx')
    sugg.to_excel(writer1, 'report2', index = False)
    workbook =
    worksheet = writer1.sheets['report2']
    # Account info columns
    worksheet.set_column('A:A', 25)
    # State column
    worksheet.set_column('B:B', 120)
    # Post code
    # worksheet.set_column('F:F', 10)
    pack_data = pd.DataFrame()
    pack_data['Packages'] = packages
    writer1 = ExcelWriter('packages.xlsx')
    pack_data.to_excel(writer1, 'report3', index = False)
    workbook =
    worksheet = writer1.sheets['report3']
    # Account info columns
    worksheet.set_column('A:A', 75)
    # State column
    # Post code
    # worksheet.set_column('F:F', 10)
if __name__ == '__main__':
    warnings, suggestions, packages, shells = clean_data()

Once you run the above scripts, you will find a folder called outputs in the current directory. navigate to the outputs folder where you will find excel sheets that contain warnings, suggestions and installed packages.

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