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title: a guide to python code security scanning with bandit
python is a versatile and powerful programming language, but like any software, it's crucial to ensure the security of your code. one way to enhance code security is by using tools like bandit, a python code security scanner. bandit helps identify potential security issues in your python codebase by analyzing its structure and identifying common vulnerabilities.
in this tutorial, we'll explore how to use bandit to scan python code for security issues and discuss ways to address the findings.
first, let's install bandit using pip:
now that bandit is installed, you can run a basic scan on your python code. navigate to the root directory of your project in the terminal and run the following command:
this command recursively scans all python files in the current directory and its subdirectories. bandit will generate a report highlighting any identified security issues.
bandit's output is categorized by severity levels: low, medium, high, and undefined. each finding is associated with a unique code, and bandit provides a brief description of the issue.
for example:
here, bandit found a potential security issue in main.py at line 8, where a hardcoded password string is present.
bandit can be configured using a .bandit configuration file. create a .bandit file in your project's root directory and customize it based on your requirements. this allows you to ignore specific checks, set confidence levels, and more.
example .bandit file:
this configuration tells bandit to exclude the 'tests' and 'docs' directories, scan the 'src' directory recursively, and apply checks to all python files.
after running bandit, it's essential to address the identified security issues. here are some common strategies:
avoid hardcoded secrets: replace hardcoded secrets with environment variables or use a secure storage solution.
input validation: ensure proper input validation to prevent vulnerabilities like sql injection or command inje ...

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