Secure your Python Code with Bandit

Secure your Python Code with Bandit

Python is a popular programming language for building web applications, scientific computing, data analysis, and more. However, like any other programming language, it is vulnerable to security issues. To address these vulnerabilities, Python developers can use various tools and techniques to identify and fix security issues in their code. One such tool is Bandit, a security linter for Python code that can identify common security issues.

What is Bandit?

Bandit is a security linter for Python code that can help identify security issues in your code. It is an open-source tool that is designed to be easy to use and integrate into your development workflow. Bandit can be used as a command-line tool or integrated into your development environment.

How does Bandit work?

Bandit works by analyzing the abstract syntax tree (AST) of your Python code. The AST is a tree-like structure that represents the syntactic structure of your code. Bandit uses a set of built-in plugins to analyze the AST and identify potential security issues.

Bandit can detect a wide range of security issues, including:

  1. SQL injection vulnerabilities

  2. Cross-site scripting (XSS) vulnerabilities

  3. Command injection vulnerabilities

  4. Hardcoded passwords and secret keys

  5. Use of unsafe cryptographic functions

  6. Use of known vulnerable libraries and modules

  7. Improper use of dangerous functions like eval() and exec()

Using Bandit to find security issues in Python code

To use Bandit, you first need to install it. You can install Bandit using pip, the Python package manager:

pip install bandit

Once installed, you can run Bandit on your Python code using the bandit command. For example, to scan a Python file named, you would run:


This will run the default set of Bandit plugins on your code and generate a report of any security issues found.

You can also customize Bandit's behavior by specifying options and plugins. For example, to run only the SQL injection plugin and generate an XML report, you would run:

bandit -r example_directory -x example_directory/venv -p sql -f xml

In this command, -r specifies the directory to scan, -x specifies directories to exclude, -p specifies the plugin to use, and -f specifies the output format.

Hands-On Example

Here's a coding example to demonstrate how Bandit can be used to identify a security vulnerability in Python code:

Consider the following Python code:

import subprocess

user_input = input("Enter your name: ")["echo", user_input])

This code takes input from the user and passes it to the echo command using This is potentially dangerous, as it allows the user to execute arbitrary commands on the system. An attacker could use this to run malicious code or gain unauthorized access to the system.

To identify this vulnerability, we can use Bandit by running the following command:


This will generate a report that includes the following warning:

>> Issue: [B602:subprocess_popen_with_shell_equals_true] Possible injection vector through shell metacharacters.
   Severity: High   Confidence: Medium
   More Info:
4["echo", user_input])

This warning indicates that the function is potentially vulnerable to command injection through shell metacharacters. To fix this vulnerability, we can modify the code to use with shell=False, like so:

import subprocess

user_input = input("Enter your name: ")["echo", user_input], shell=False)

By using shell=False, we prevent the user from executing arbitrary commands and mitigate the risk of a potential security vulnerability.

In this way, Bandit can help identify potential security vulnerabilities in your Python code and provide guidance on how to fix them.


Bandit is a powerful tool for identifying common security issues in Python code. By integrating Bandit into your development workflow, you can catch potential security issues early and ensure that your code is secure. However, it is important to note that Bandit is not a silver bullet, and it is not a substitute for good coding practices and thorough security testing. You should always follow best practices for secure coding, such as using secure cryptographic functions, avoiding hardcoded passwords and secret keys, and sanitizing input to prevent SQL injection and XSS vulnerabilities.

To Know more goto Bandit Documentation:

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