Security chaos engineering is the practice of intentionally introducing security incidents into a system in order to test and improve its resilience and response to unexpected events. This can help organizations to identify and fix vulnerabilities before they are exploited by attackers.

Creating a security chaos engineering experiment in Python involves the following steps:

1. Define the scope of the experiment: Identify the specific security incident that you want to simulate, and the components of your system that will be affected by the experiment.
2. Plan the experiment: Determine the steps that you will need to take to simulate the security incident, and the methods that you will use to verify that the experiment has had the intended effect.
3. Set up the necessary tools and resources: Install the necessary software and libraries, and ensure that you have access to the resources that you will need to run the experiment.
4. Write the Python code to implement the experiment: Use the AWS SDK for Python (Boto3) or the kubernetes Python module to interact with the relevant AWS services or Kubernetes components.
5. Run the experiment: Execute the Python code to simulate the security incident and observe the results.
6. Analyze the results: Analyze the data collected during the experiment to identify any vulnerabilities or weaknesses in your system, and determine what steps can be taken to improve its resilience.
7. Document the experiment: Document the results of the experiment and any lessons learned, to help inform future security chaos engineering efforts.

It is important to note that security chaos engineering experiments should be carefully planned and executed, as they can have unintended consequences if not handled correctly. It is recommended to perform these experiments in a controlled environment, such as a staging or development environment, rather than in production.