By Jess Feldman
Last Updated October 28, 2021
You may think of Python as a data science programming language, but did you know that Cybersecurity Engineers heavily rely upon Python? From penetration testing to automating security processes, Python has become an in-demand skill for today’s cybersecurity professionals and Flatiron School Cybersecurity Instructor Aastha Sahni joined us to explain how Python is used on the job. Find out which Python libraries and frameworks are most popular amongst cybersecurity experts, and how to learn Python for cybersecurity at a bootcamp like Flatiron School!
Meet the Expert: Aastha Sahni
- Aastha Sahni is a Cyber Security Instructor at Flatiron School. She earned Bachelor’s and Master’s degrees in New Delhi, India, and now lives in New Jersey. At Flatiron School, Aastha supports the Flex programs by leading multiple cohorts, helping students in specific courses (including Python), and other courses like cryptography, application security, network security, system security, compliance, and more.
- Aastha has worked in various cybersecurity jobs before following her passion into teaching. She also leads and volunteers in cybersecurity communities.
What is Python?
Python is a free, open-source programming language that has a heavy focus on code readability and indentation. Python is accessible and modifiable, and can be used to design and customize web applications, for scientific computations, artificial intelligence, and data science. Python is an interpreted language, so when you run Python code, it is automatically converted into machine language. This is unlike other languages, like C++, which need to be first compiled and then interpreted.
Python is easy to learn, code, run, and read, making it a high-demand skill to possess. All of this makes Python the easiest, most used programming language in tech, including in cybersecurity!
How Python is Used by Cyber Security Analysts
In cybersecurity, Python is used to:
- Automate processes
- Write scripts
- Customize tools
- Automate and orchestrate security response operations
A cybersecurity analyst uses Python scripts to automate tasks, such as implementing penetration testing. A large number of cybersecurity applications and tools are based out of and heavily rely on Python, which means they can be customized according to individual needs and requirements.
Do cybersecurity professionals need to know Python?
As an entry-level cybersecurity professional, it’s not mandatory to know Python, and there are so many domains in cyber which do not include the usage of Python every day. However, it’s always helpful to know the basics of Python. The biggest benefit to knowing Python for cybersecurity is the ability to write scripts. Writing and developing scripts becomes very easy as it supports minimal code and extensive use of libraries.
Cybersecurity engineers are more involved with development, architecture, and customizing, which include understanding complex data structures, and may require a more intermediate-level understanding of Python. If you’re aspiring to be a security engineer, where you’re creating a custom tool or app, you are required to know an intermediate-level of Python.
Basic knowledge of Python opens many career doors to perform a variety of roles, not only in cybersecurity but in other areas, like data science. In addition to basics, having an intermediate-level understanding of Python will definitely help a cybersecurity professional in interviews, more responsibility, and future opportunities.
The Top 14 Python Libraries for Cybersecurity
Python is popular because it is free, simple, and requires minimal coding, thanks to the Python libraries’ functions and methods. And Python libraries are extensive! Python libraries are used for implementing a variety of functions and capabilities in the cybersecurity field. Here are some of the major libraries that are used for multiple operations by cybersecurity professionals on the job.
The Python libraries most widely used for natural language processing, data analysis, visualization, and more are NLTK, NumPy, and Pandas. These libraries are also used for malware analysis.
The Scikit library is widely used for implementing machine learning in cybersecurity operations. Machine learning algorithms are also supported by Scikit.
Network security-related libraries, like Nmap and Twisted, are widely used for scanning and implementing transport layer, application layer protocols.
Scapy is used for packet processing, decoding packets, forging packets, and analyzing the packet information on a network.
Beautiful Soup is widely used for scraping data from web pages in the form of HTML and XML.
Cryptography Library is used in order to implement cryptographic algorithms, specifically for the purpose of securing something, such as a file, communication, etc.
YARA is widely used for malware identification and classification.
Pymetasploit3 is a library where you can use the Metasploit framework for discovering hidden vulnerabilities.
Mechanize (which is similar to Beautiful Soup) is used for data acquisition and for interacting with and getting data from the web pages. Mechanize is also used for checking SQL injection and cross site scripting.
Example of Python Script for Automation in Cybersecurity
NMAP for Port Scanning
#nmap for port scanning
nm = nmap.PortScanner()
scan_range = nm.scan(hosts="127.0.0.1","21-443")
How is Python used in Pen Testing?
Penetration testing, also known as pen testing, is a wide area of implementation where cybersecurity professionals are trying to assess an organization’s security. That way, cybersecurity professionals can notify the company of any major loopholes in their security and then be better prepared for cyber attacks.
Someone performing a pen test is performing whatever an attacker would do. There are seven stages of penetration testing, and at every stage except for the first pre-engagement stage, there are a variety of Python libraries that can be used:
- Stage 1: Pre-Engagement – A cybersecurity team determines the objectives and logistics of the pen test.
- Stage 2: Information Gathering – Pen testers rely on the Python libraries: NMAP, Twisted, Beautiful Soup, Scapy, Socket, Mechanize, and Devploit script.
- Stage 3: Threat Modeling – Pen testers rely on the Python libraries: Pytm Framework and Threat-modeling 0.0.1.
- Stage 4: Vulnerability Scanning – Pen testers rely on the Python libraries: Vulners 1.5.13, Safety, and Scapy.
- Stage 5: Exploitation – Pen testers rely on the Python libraries: Pymetaploit3 (to implement Metasploit framework), Scapy, Socket, and BYOB.
- Stage 6: Post-Exploitation – Pen testers rely on the Python libraries: Pymetaploit3, BYOB, and RSPET.
- Stage 7: Reporting – Pen testers rely on the Python libraries: Sys, Plotly, Pandas, and NLTK.
How do cybersecurity analysts use Python during a cyber attack?
There are a few Python libraries and frameworks that cybersecurity experts rely on when under a cyber attack:
- pslist can be used to list processes and identify when certain processes start and how they end.
- pstree is used to analyze what processes are running, with the help of a tree architecture.
- psscan helps to uncover terminated processes, which have already stopped.
- psxview gives a comprehensive view of processes, their locations, where they are present and in what particular locations in your operating system.
- GRR (Google Rapid Response) is an incident response framework based out of Python.
Cybersecurity experts also rely on automating security tasks when under cyber attack. SOAR (Security Orchestration, Automation, and Response) helps in automating security tasks and is widely used at the time of incident response when we are analyzing various alerts.
- Example: A security alert has been generated. Python labels are used in SOAR so cybersecurity experts can perform an initial analysis to determine the nature of alert & type of incident and respond timely, with the help of APIs and libraries.
With the help of Python, cybersecurity experts can also create play books, which can automate analysis, from analyzing to creating the ticket for the incident response analyst.
How to Learn Python for Cybersecurity
Flatiron School teaches Python in the Cybersecurity Engineering Bootcamp. In the bootcamp, there are labs dedicated to Python, where students get hands-on experience while solving tasks. We use Python while developing various scripts and pull for cryptographic algorithms. Cybersecurity engineering bootcamp students also utilize Python in other courses, like cryptography. Not only do students learn Python at Flatiron School, they also learn how it is practically applied in cybersecurity.
Aastha’s 2 Favorite Python Resources
For total beginners, Flatiron School offers a free intro Python workshop. It’s a hands-on, short lesson where students learn different components using different Python skills and techniques.
For those looking to test their Python skills, Python’s website contains so many libraries and detailed exercises.