- Lab
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Libraries: If you want this lab, consider one of these libraries.
- Security
Validate User Input for Python
In this lab, you will act as a secure Python developer at Globomantics, and your goal is to identify and patch severe vulnerabilities in a Python data processing service. You will explore how to protect Python applications from common memory-level risks, insecure deserialization, and untrusted data payloads by adopting secure development practices.
Lab Info
Table of Contents
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Challenge
Vaidate and mitigate buffer overflow within Python applications
You will explore memory safety risks in Python applications by triggering a buffer overflow in a legacy C-API extension and refactoring the code to use safe native types.
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Challenge
Prevent insecure deserialization vulnerabilities when handling untrusted data
You will run a data ingestion with both benign and malicious serialized payloads to demonstrate how untrusted data can execute arbitrary code, identify the unsafe deserialization functions in the codebase, and replace them with secure alternatives.
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Challenge
Implement robust validation for untrusted data structures
You will test the error handling of a vulnerable local Python API service by executing provided payloads and implement Pydantic for strong data validation to prevent sensitive information disclosure.
About the author
Real skill practice before real-world application
Hands-on Labs are real environments created by industry experts to help you learn. These environments help you gain knowledge and experience, practice without compromising your system, test without risk, destroy without fear, and let you learn from your mistakes. Hands-on Labs: practice your skills before delivering in the real world.
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Engage hands-on with the tools and technologies you’re learning. You pick the skill, we provide the credentials and environment.
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On average, you retain 75% more of your learning if you take time to practice. Hands-on labs set you up for success to make those skills stick.