Information Gathering Using Python in Cybersecurity


In today’s world, where there is an abundance of data present everywhere, it is necessary to protect it from attackers. These attackers are always in search of information, and even a modicum of data, if gotten into their hands, can let them invade your whole database.

Python, being very comprehensible and relatively simple, helps a lot in the data gathering. So, in this article, we’ll discuss how Python is very useful for such information gathering and data collection.

But before getting into that, let us first understand what the term cybersecurity actually means.

What is Cybersecurity?

Cybersecurity is the practice of protecting critical data and sensitive information from digital attackers.

Cybersecurity attacks are usually for accessing, destroying, or modifying information using malware, ransomware, phishing, social engineering, spear phishing, insider threats, distributed denial of service, advanced persistent threats, and man-in-the-middle attacks.

Information Gathering Using Python in Cybersecurity

Types of Cybersecurity Attacks

The table given below shows the different types of cybersecurity attacks.

Type of AttackDescription
MalwareMalicious software like viruses, worms, and trojan horses infect your system with or
without your knowledge. They provide unauthorized access and can cause any damage to your
system.
RansomwareAs the name suggests, the attacker will threaten the victim to release or destroy the data unless provided with some ransom.
PhishingIt is an attack where the victims get deceitful emails and messages asking for their sensitive information like login credentials to any website account, credit and debit card numbers, etc.
Social EngineeringIt is a type of attack that uses human contact to deceive users into violating
security rules in order to obtain sensitive information that is normally protected.
Spear PhishingIt is a category of phishing attack which has a specified target, business, or organization.
Insider ThreatsThese are attacks that are directly done by the employees of the firm, or rather the people who already have access to the data and use it for the wrong purposes.
Distributed Denial of ServiceThe attack denies the availability of the data to the authorized users by crashing the server, increasing the traffic, or overloading the network.
Advanced Persistent ThreatsAPTs are long-term targeted attacks in which an attacker infiltrates a network and remains unnoticed for extended periods of time to steal data.
Man-in-the-middle AttackIt is an eavesdropping attack in which a cybercriminal intercepts and transmits messages between two parties to obtain data.
Table: Types of Cybersecurity Attacks

Steps in Hacking Into a System

Consider an attacker who needs to retrieve information from a big organization. Let’s see the steps as to how the attacker is going to achieve it.

The first and foremost thing that the attacker needs are the collection of data of the target like the IP address range, network, DNS records, etc. This is called the footprinting or reconnaissance phase. Python plays a significant role in this phase. We’ll see how it does in later sections.

Assuming the attacker has collected the required information about the target, the next step is to scan and find out the vulnerabilities he can exploit and get unauthorized access to the target system. This phase is called scanning.

The next phase is called gaining access, wherein the attacker will exploit the vulnerabilities found and hack into the targeted system. This can be done using any of the cybersecurity attacks mentioned above. 

After this, the attacker has to maintain access until his tasks are completed. This has to be done without the users’ knowledge and can be done using trojan horses, rootkits, etc.

Finally, as it’s always said, a thief never wants to get caught. So, the intelligent attacker will take an extra and important step of erasing all the tracks so that nobody can trace back to him. This phase is called clearing the tracks

How is Python Useful for Information Gathering and Collection of Data?

Now let’s see the use cases of Python in information gathering for cybersecurity.

1. Port Scanning

Port scanning is used to find all the access ports in the targeted network. It is used by hackers to target victims and security engineers to check for vulnerabilities.

Ports can either be open, closed, or filtered. Open ports are an attack path where the host responds that it is listening and gives an intimation to the attacker that it is open for queries.

A simple Python code can be written to find the open ports that are potentially vulnerable to exploitation.

2. Packet Sniffing

Packet sniffing is a technique for detecting and observing packet data traveling across a network. Packet sniffing tools are used by network administrators to monitor and validate network traffic, whereas hackers may use similar tools for malicious reasons.

Python has in-built modules like socket and struct that have the necessary functions to extract the MAC address of the source and destination of the frame.

3. DNS Exploration

DNS is an abbreviation for Domain Name System. It is a protocol that converts an IP address to a hostname. DNS lookup is of two types: searching a domain name to find its IP address (called forward DNS lookup) and identifying the domain name using the IP address (called the backward DNS lookup). 

A Major Python Package Used in Cybersecurity

Scapy is a critical tool for cybersecurity that helps in the first phase of attack called reconnaissance. It creates bespoke packets and sends them across the network, as well as sniffing, dissecting, and analyzing incoming data. 

Scapy is excellent for reconnaissance since it has all the building parts required to create a custom network or vulnerability scanners, such as Nmap or Nessus. A penetration tester can quickly and easily construct a network scan or a custom packet to test for a specific vulnerability via the network.

Final Thoughts

Information gathering and data collection are one of the most important to hacking into a system. Python, being a scripting language, is a powerful tool for these tasks.

Python can collect various data, not only visible ones but also latent ones. It automates the data collection process and helps the attacker to gather information quite easily.

Therefore, Python is an asset for cybersecurity, and you can use it for offense and defense. All the best for your future coding endeavors, and happy coding!

Ashwin Joy

I'm the face behind Pythonista Planet. I learned my first programming language back in 2015. Ever since then, I've been learning programming and immersing myself in technology. On this site, I share everything that I've learned about computer programming.

One thought on “Information Gathering Using Python in Cybersecurity

  1. Hi,

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    Cheers,
    Virginia Hamlin

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