Product label: Software Security

Generative AI is transforming the software industry, with tools like GitHub Copilot and Codeium enabling developers to achieve unprecedented levels of efficiency. While this is exciting progress, it also raises important concerns, encouraging stakeholders to approach these technologies with care. Current AI tools often lack the nuanced understanding necessary to address subtle, yet critical aspects of software development, particularly in the domain of security.

This course provides a comprehensive insight into the responsible use of generative AI in coding. Participants delve into topics in software development that are most likely to be impacted by careless use of generative AI, including authentication, authorization, and cryptography. The curriculum also includes an analysis of how AI tools like Copilot handle secure coding practices related to key vulnerabilities outlined in the OWASP Top Ten, such as path traversal, SQL injection, or cross-site scripting.

Through hands-on learning and experimenting, participants will get a solid understanding of both the strengths and limitations of AI-assisted development. In addition, case studies of real-world incidents showcase the consequences of insecure code and demonstrate the dual nature of generative AI as both a resource and a potential risk.

By the end of the course, developers will be equipped with the knowledge and skills to integrate AI tools into the software development lifecycle responsibly, enhancing efficiency without compromising security or product quality.

PRACTICAL INFO

• If on-site training is not feasible, we can discuss providing a live, interactive online (virtual) or hybrid training. The standard program with 3-day content can also be delivered in 5 half days (from Monday to Friday).
• Curious about how to quantify the return on investment (ROI) of secure coding trainings? Check out this article.

Generative AI is transforming the software industry, with tools like GitHub Copilot and Codeium enabling developers to achieve unprecedented levels of efficiency. While this is exciting progress, it also raises important concerns, encouraging stakeholders to approach these technologies with care. Current AI tools often lack the nuanced understanding necessary to address subtle, yet critical aspects of software development, particularly in the domain of security.

This course provides a comprehensive insight into the responsible use of generative AI in coding. Participants delve into topics in software development that are most likely to be impacted by careless use of generative AI, including authentication, authorization, and cryptography. The curriculum also includes an analysis of how AI tools like Copilot handle secure coding practices related to key vulnerabilities outlined in the OWASP Top Ten, such as path traversal, SQL injection, or cross-site scripting.

Through hands-on learning and experimenting, participants will get a solid understanding of both the strengths and limitations of AI-assisted development. In addition, case studies of real-world incidents showcase the consequences of insecure code and demonstrate the dual nature of generative AI as both a resource and a potential risk.

By the end of the course, developers will be equipped with the knowledge and skills to integrate AI tools into the software development lifecycle responsibly, enhancing efficiency without compromising security or product quality.

PRACTICAL INFO

• If on-site training is not feasible, we can discuss providing a live, interactive online (virtual) or hybrid training. The standard program with 3-day content can also be delivered in 5 half days (from Monday to Friday).
• Curious about how to quantify the return on investment (ROI) of secure coding trainings? Check out this article.

Generative AI is transforming the software industry, with tools like GitHub Copilot and Codeium enabling developers to achieve unprecedented levels of efficiency. While this is exciting progress, it also raises important concerns, encouraging stakeholders to approach these technologies with care. Current AI tools often lack the nuanced understanding necessary to address subtle, yet critical aspects of software development, particularly in the domain of security.

This course provides a comprehensive insight into the responsible use of generative AI in coding. Participants delve into topics in software development that are most likely to be impacted by careless use of generative AI, including authentication, authorization, and cryptography. The curriculum also includes an analysis of how AI tools like Copilot handle secure coding practices related to key vulnerabilities outlined in the OWASP Top Ten, such as path traversal, SQL injection, or cross-site scripting.

Through hands-on learning and experimenting, participants will get a solid understanding of both the strengths and limitations of AI-assisted development. In addition, case studies of real-world incidents showcase the consequences of insecure code and demonstrate the dual nature of generative AI as both a resource and a potential risk.

By the end of the course, developers will be equipped with the knowledge and skills to integrate AI tools into the software development lifecycle responsibly, enhancing efficiency without compromising security or product quality.

PRACTICAL INFO

• If on-site training is not feasible, we can discuss providing a live, interactive online (virtual) or hybrid training. The standard program with 3-day content can also be delivered in 5 half days (from Monday to Friday).
• Curious about how to quantify the return on investment (ROI) of secure coding trainings? Check out this article.

Generative AI is inevitably transforming the software industry. Tools like ChatGPT or Github Copilot enable developers to code more efficiently than ever before. While this sparks excitement, it also raises concerns, and so many stakeholders tend to balance this optimism with caution. Though these tools are advancing rapidly, to date they still lack the necessary sophistication to consider various subtle but important aspects of software products. This training course emphasizes the importance of understanding this evolution through the well-established principles of responsible AI.

After a short overview of AI and specifically responsible AI, participants delve into the complex world of machine learning (ML), focusing on how these solutions can be compromised. Threats and vulnerabilities such as model evasion, poisoning and inversion attacks are explained in a simple way, via real-world case studies and live demonstrations. Finally, we overview the security challenges of large language models (LLMs), exploring the practical defenses as well.

The course then highlights the capabilities and limitations of generative AI (GenAI) tools – like Github Copilot, Codeium or others –, offering insights into their role in code generation and beyond. Topics include smart prompt engineering, not only during the implementation phase but also during requirements capturing, design, testing and maintenance. Participants will learn best practices and pitfalls of using AI-generated code, with hands-on labs demonstrating potential security flaws such as dependency hallucination and path traversal. By the end, software engineers and managers will have a clear understanding of how to responsibly integrate GenAI tools into the various stages of the software development lifecycle.

Generative AI is transforming the software industry, with tools like GitHub Copilot and Codeium enabling developers to achieve unprecedented levels of efficiency. While this is exciting progress, it also raises important concerns, encouraging stakeholders to approach these technologies with care. Current AI tools often lack the nuanced understanding necessary to address subtle, yet critical aspects of software development, particularly in the domain of security.

This course provides a comprehensive insight into the responsible use of generative AI in coding. Participants delve into topics in software development that are most likely to be impacted by careless use of generative AI, including authentication, authorization, and cryptography. The curriculum also includes an analysis of how AI tools like Copilot handle secure coding practices related to key vulnerabilities outlined in the OWASP Top Ten, such as path traversal, SQL injection, or cross-site scripting.

Through hands-on learning and experimenting, participants will get a solid understanding of both the strengths and limitations of AI-assisted development. In addition, case studies of real-world incidents showcase the consequences of insecure code and demonstrate the dual nature of generative AI as both a resource and a potential risk.

By the end of the course, developers will be equipped with the knowledge and skills to integrate AI tools into the software development lifecycle responsibly, enhancing efficiency without compromising security or product quality.

PRACTICAL INFO

• If on-site training is not feasible, we can discuss providing a live, interactive online (virtual) or hybrid training. The standard program with 3-day content can also be delivered in 5 half days (from Monday to Friday).
• Curious about how to quantify the return on investment (ROI) of secure coding trainings? Check out this article.

Your machine learning application 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 -231? Because that’s what the bad guys will do. And the list is far from complete.

As a machine learning practitioner, you need to be paranoid just as any developer out there. Interest in attacking machine learning solutions is gaining momentum, and therefore protecting against adversarial machine learning is essential. This needs not only awareness, but also specific skills to protect your ML applications. The course helps you gain these skills by introducing cutting edge attacks and protection techniques from the ML domain.

Machine learning is software after all. That’s why in this course we also teach common secure coding skills and discuss security pitfalls of the Python programming language. Both adversarial machine learning and core secure coding topics come with lots of hands on labs and stories from real life, all to provide a strong emotional engagement to security and to substantially improve code hygiene.

To make sure that you are prepared for the forces of the dark side.

To make sure that nothing unexpected happens.

Nothing.

PRACTICAL INFO

• If on-site training is not feasible, we can discuss providing a live, interactive online (virtual) or hybrid training. The standard program with 3-day content can also be delivered in 5 half days (from Monday to Friday).
• Curious about how to quantify the return on investment (ROI) of secure coding trainings? Check out this article.

Your 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 -2^32? 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 hand on labs and stories from real life, all to substantially improve code hygiene. Mistakes, consequences and best practices are our blood, sweat and tears.

All this is put in the context of Java, and extended by core programming issues, discussing security pitfalls of the Java language and framework.

So that you are prepared for the forces of the dark side.

So that nothing unexpected happens.

Nothing.

 

PRACTICAL INFO

• If on-site training is not feasible, we can discuss providing a live, interactive online (virtual) or hybrid training. The standard program with 3-day content can also be delivered in 5 half days (from Monday to Friday).
• Curious about how to quantify the return on investment (ROI) of secure coding trainings? Check out this article.

Your application written in C# 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 -2^32? 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 hand on labs and stories from real life, all to substantially improve code hygiene. Mistakes, consequences and best practices are our blood, sweat and tears.

All this is put in the context of C#, and extended by core programming issues, discussing security pitfalls of the C# language and .NET framework.

So that you are prepared for the forces of the dark side.

So that nothing unexpected happens.

Nothing.

PRACTICAL INFO

• If on-site training is not feasible, we can discuss providing a live, interactive online (virtual) or hybrid training. The standard program with 3-day content can also be delivered in 5 half days (from Monday to Friday).
• Curious about how to quantify the return on investment (ROI) of secure coding trainings? Check out this article.

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 -2^32? 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 hand 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 framework.

So that you are prepared for the forces of the dark side.

So that nothing unexpected happens.

Nothing.

PRACTICAL INFO

• If on-site training is not feasible, we can discuss providing a live, interactive online (virtual) or hybrid training. The standard program with 3-day content can also be delivered in 5 half days (from Monday to Friday).
• Join our free webinar to learn more. 
• Curious about how to quantify the return on investment (ROI) of secure coding trainings? Check out this article.

Your application written in Java or C# 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 -2^32? 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 hand 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 the discussed programming languages, and extended by core programming issues, discussing security pitfalls of the used frameworks.

So that you are prepared for the forces of the dark side.

So that nothing unexpected happens.

Nothing.

PRACTICAL INFO

• If on-site training is not feasible, we can discuss providing a live, interactive online (virtual) or hybrid training. The standard program with 3-day content can also be delivered in 5 half days (from Monday to Friday).
• Join our free webinar to learn more. 
• Curious about how to quantify the return on investment (ROI) of secure coding trainings? Check out this article.