Code responsibly with generative AI in Java
Your Web application written in Java works as intended, so you are done, right? But did you consider feeding in incorrect values? 16Gbs of data? A null? An apostrophe? Negative numbers, or specifically -1 or -2^31? Because that's what the bad guys will do – and the list is far from complete.
Handling security needs a healthy level of paranoia, and this is what this course provides: a strong emotional engagement by lots of hands-on labs and stories from real life, all to substantially improve code hygiene. Mistakes, consequences, and best practices are our blood, sweat and tears.
The curriculum goes through the common Web application security issues following the OWASP Top Ten but goes far beyond it both in coverage and the details.All this is put in the context of Java, and extended by core programming issues, discussing security pitfalls of the Java language and the runtime environment.
So that you are prepared for the forces of the dark side.
So that nothing unexpected happens.
Nothing.
Audience & Prerequisits:
- Java developers working on Web applications.
- General Java and Web development
Standards and references:
- OWASP, SEI CERT, CWE and Fortify Taxonomy.
- 31 Labs and 16 Case studies.
What you will learn:
- Getting familiar with essential cyber security concepts
- Understanding how cryptography supports security
- Learning how to use cryptographic APIs correctly in Java
- Understanding Web application security issues
- Detailed analysis of the OWASP Top Ten elements
- Putting Web application security in the context of Java
- Going beyond the low hanging fruits
- Managing vulnerabilities in third party components
Note:
This variant of the course deals extensively with how certain security problems in code are handled by GitHub Copilot.
Through a number of hands-on labs participants will get first hand experience about how to use Copilot responsibly, and how to prompt it to generate the most secure code. In some cases it is trivial, but in most of the cases it is not; and in yet some other cases it is basically impossible.
At the same time, the labs provide general experience with using Copilot in everyday coding practice - what you can expect from it, and what are those areas where you shouldn't rely on it.
About The instructor Kiss Balazs
Balázs started in software security two decades ago as a researcher in various EU projects (FP6, FP7, H2020) while also taking part in over 25 commercial security evaluations: threat modeling, design review, manual testing, fuzzing. While breaking things was admittedly more fun, he's now on the other side, helping developers stop attacks at the (literal) source.
To date, he has held over 100 secure coding training courses all over the world about typical code vulnerabilities, protection techniques, and best practices.
His most recent passion is the (ab)use of AI systems, the security of machine learning, and the effect of generative AI on code security.
