The Best Practices Cheat Sheet for Secure Coding in Python

Programming is at its peak at the moment with Python leading the pack with the! It is very popular because of its simple use and effectiveness in automation and DevOps. However, because of the nature of apps and services this programming language handles it is VERY important to have the code secured. You can achieve this by following the 11 best Python secure coding practices we developed in a cheat sheet for you and your teams.

Why Secure Coding is Important

The developers need to be vigilant and keep in mind:

  • Security and safety of code.
  • Optimization and efficiency of code.
  • Application architecture and design requirements.

The Risks Involved with not writing secure code

If your application is not secured to the fullest then it makes a gateway for the security thefts to come in. Like this, they have direct control of the particular device or provide access path to another device.

  • Results

This might result in the following:

  • Service loss.
  • Loss of life.
  • Compromised secrets.
  • System damage.
  • Denial of service to a single user.

Why Follow Secure Coding Standards

Why follow coding standard

Developers and programmers can easily weed out common vulnerabilities in their software, for this all they need to do is follow some great practices and guidelines known as secure coding standards.

They bring good in the 4 following ways:

  1. It removes all the commonly exploited vulnerabilities present in the software.
  2. Prevents cyberattacks.
  3. Sensitive information is not leaked out.
  4. Helps save up costs that may occur in case of an exploit.

2 Common Code Security vulnerabilities that are found

Python Security Vulnerabilities

Buffer Overflow:

Today through IoT embedded systems are becoming connected with the world outside. This creates new ways and more opportunities for malicious code attacks.

Buffer Flow, the security thief can put code or data in the system through this. If all happens correctly then that particular system is opened to further instructions.

Code Injection:

Now this is another one that exploits a bug that occurs by processing data that is not valid. This is a kind of injection attack that we can defend.

In this arbitrary code, Shell-lock can be executed there on the remote system to perform malicious activities.

11 Best Secure Coding Practices for Python Coding (A Cheat Sheet to Secure Python Code)

For the best coding you need to keep in mind regarding some things, we have compiled for you a list, follow through to know more:

Validate the inputs

For data sources you do not trust make sure to know them as there would be fewer chances of software vulnerabilities. Keep an eye on external data sources which include:

  • Network interfaces.
  • Environmental variables.
  • User-controlled files.

Authentication and Management of Passcode

Limiting access to users like this can prevent cyber-attacks and data breaches. You can use one of the following ways as well:

  1. For password, hashing uses a trusted system.
  2. Use of multi-factor authentication.
  3. Authentication credentials are strong.
  4. Make sure to have good password strength.
  5. Meet up with complexity requirements.

Use Python’s Recent Version

It is always best to keep your system and all the apps and software you use up to date. Its version 2.7 which came out in 2020 will lose its support therefore you need to move up the ladder and grab Python 3.

If you continue with the older version, it will become difficult to update it. You should also keep your IDE updated as a vulnerability can also appear in the tooling. We also advise using free and open-source IDEs as they are more secure and always updated by the community.

Access Control is a must

This goes hand in hand with authentication to be sure that any security theft cannot have easy access to the system.

Default Deny is safe

We suggest you adopt this, now if you are not aware of the term then don’t worry as it states that all those who can’t demonstrate authorization should not be given access.

Complexity can cause problems

Simple code ensures security. If the design is complex, there are chances that vulnerabilities will make their way in.

Cryptographic is the future

Values generated randomly need to be generated through an improved random number generator so they can’t be guessed.

Fast Error Handling

Code written down in the best way can also have errors. What needs to be done is we treat errors as soon as possible.

Protect from SQL Injection 

If you do not know, let us open your ears by telling you that SQL injections can also drop sensitive data from insecure devices. Make sure to take this one seriously as well and follow all the procedures to protect your database.

ALSO SEE: A guide to Install Python 3 Securely on Windows.

Data Protection is key

What security thefts aim is to get their hands on sensitive data and have access to it? Protect your data in the best possible way, we have also listed some ways for you:

  1. Have know-how of all the code elements.
  2. Make sure to regularly delete cached copies of sensitive data present on the server.
  3. Ensure you don’t have any stored passcodes and connection strings in clear text or another non-encrypted manner on the side of the client.

Model your threats

It is used to identify threads and then provides solutions. Make sure to do this on a regular basis. Make sure not to commit anything with a Password.

If we assume that developers using Github, then please make sure you have not left any password in any file, readme and description of the URL. If yes, remember that it shall be there in the data and accessed by anyone.

Get Bandit Installed

For every project, we recommend installing a bandit to scan the code for known vulnerabilities like issues with YAML.

Why you should consider Bandit:

  1. It ranks the risk of security from low to high.
  2. Informs users regarding which lines of code are causing the issues.
Paul@ninja-ide:~# Pip install bandit

Use Procedure

It scans all the Python files that have been selected and after that presents a report in the form of an abstract syntax tree.


  • Very quick.
  • Easy to use.

7 common coding mistakes done by developers you should avoid

Common Secure Coding Mistakes

  1. Having trust on third-party code.
  2. Hard-coding backdoor accounts.
  3. SQL injections not verified
  4. Remote file inclusions.
  5. Handing insecure data.
  6. Not able to encrypt data.
  7. Using a non-secure cryptographic system.


Secure coding is the way to go because you must start at the core of an application or software to be safe. Most data breaches happen and come to light years after because of 0-day vulnerabilities or bugs discovered in code that developers or companies don’t even know. This is why you need to start getting your development teams to implement secure coding standards throughout to start in a safe manner. You can also look at OWASP’s best practice guide for further tips.

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Paul Carruthers
Paul is an avid programmer who specializes in Python and Java with over 16 years of experience in the field. He loves automating complex tasks and creating useful scripts to streamline work and make life easier. He is also a massive fan of Linux and currently uses it as his main desktop OS. When he is not staring at code, he loves hiking and swimming in different parts of the world.


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