The labs
Train hands-on
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Introduction to Python Bandit
Python bandit is one of the most commonly used Python linters and static analysis tools. This lab introduces the use of bandit for analysis of Python code.
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Introduction to Python Control Flow Analysis
Control flow analysis is useful for identifying mistakes or unexpected flows in a program. This lab demonstrates the use of staticfg for control flow analysis in Python.
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Command Injection in Python
A command injection vulnerability enables an attacker to run malicious code on the system where an application is running. This lab demonstrates how to identify, exploit and mitigate these vulnerabilities in Python.
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XPath Injection in Python
XPath is a programming language for extracting data from XML files; however, it is vulnerable to injection attacks. This lab demonstrates vulnerable code and how to exploit and remediate it.
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XML Attacks in Python
XML is a useful method for storing structured data, but code parsing it can be vulnerable to a number of attacks. This lab demonstrates some of the ways that different XML parsing functions can be exploited in Python.
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Race Conditions in Python
Race condition vulnerabilities exist when the proper operation of a program depends upon operations being run sequentially back-to-back. This lab demonstrates how to identify, exploit and remediate these vulnerabilities.
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Cross-Site Scripting in Python
Cross-site-scripting (XSS) is one of the most common web application vulnerabilities in existence. This lab demonstrates how to identify, exploit and remediate XSS vulnerabilities in Flask web applications.
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Cross-Site Request Forgery in Python
Cross-site request forgery (CSRF) vulnerabilities allow an attacker to force unauthorized actions to be taken on an authenticated user’s account. This lab demonstrates how to identify, exploit and remediate these vulnerabilities in Python code.
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Supply Chain Vulnerabilities in Python
Very few applications are designed to be completely standalone, and a program’s dependencies can introduce vulnerabilities. This lab demonstrates the use of tools for identifying potential supply chain vulnerabilities in Python programs.
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Unsafe Deserialization in Python
Serialization is helpful for making Python objects and data writable to files and transferrable over the network. This lab demonstrates how some serialization options can be vulnerable to exploitation in Python and how to securely serialize data.
You're in good company
We use Infosec Skills to provide continuous training to our technicians and to prepare them for various certifications. Infosec Skills allows us to create personalized training programs that focus on each of our technicians’ particular roles and see their progress as they take courses. We also, recommend it to clients to make their IT support teams better.
Caleb Yankus
This has been utilized to bridge the skills gap across our cyber team and to aid them as they prepare for their various certifications. It also has provided a nice learning foundation for our various cyber team members to utilize as we continue to find ways for cross-utilization with operations while minimizing the downtime needed to ensure everyone’s knowledge is the same.
Daniel Simpson
We use Infosec Skills to provide base level knowledge for employees. We also use the services to provide in depth learning for employees as they encounter new technologies. If an employee is is assigned to a new project, we can rely on Infosec Skills to provide a rapid concentrated learning environment. This rapid concentrated learning positions our employees for success.
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