Adopting Agile Development with AI in Application Security

Software development has always moved fast, and the integration of Artificial Intelligence (AI) has sped things up exponentially. Unfortunately, this also means that security threats are growing at lightning speed, and security teams are struggling to keep up. Is your security team working in a blazingly fast, agile environment, or are you struggling to keep up with the pace of security threats?

Another unfortunate reality is that security teams are not growing at the same pace that development teams are able to push out new features. This means that security teams are often left behind. This is where AI can help.

How can we use AI to help us keep up with the pace of security threats?

AI in Security

AI is not a new concept, even in security. It's been used for decades to automate a wide range of tasks, as well as make better decisions using vast amounts of data. In the realm of application security, AI is transforming the way we approach things. AI-driven automated vulnerability detection, integration into the agile SDLC, and the future outlook of AI in security are all areas where AI is making a significant impact.

But wait, aren't most of the tools I'm talking about based on the traditional machine-learning algorithms? Yes, kind of... Newer, LLM based AI is becoming more and more popular, and it's starting to make its way into the application security world. LLMs do have some interesting use cases, but we need to be careful not to over-rely on them, and selective on where they fit into our security workflows.

Automated Vulnerability Detection

AI based vulnerability detection has been around for a long time now. It has been helping teams around the world detect, triage, and remediate vulnerabilities at a much faster rate than manual pen-testing and security reviews. These AI based tools are great for general security, but they tend to miss complex, business logic based vulnerabilities that require human expertise to detect and remediate. Additionally, there are not many that are great at combining multiple vulnerabilities to create a chain of events that can be exploited at a higher severity by an attacker.

Integration of AI into the Agile SDLC

What does your SDLC look like? Do you have any security gates? Are they automated, manual, a mix of both? I've had great success implementing security reviews based on simple threat models or security questionnaires that developers can complete in only a couple of minutes. These are great for agile development environments, but they can be a bit time consuming and may not be as effective as a more automated approach. In addition, some people who may not be as eager to spend time on security reviews may be more inclined to work find a way around the system.

This is an area where I see a great opportunity for LLMs in security workflows. LLMs are good at understanding context from a given prompt: If the prompt contains the contents of a development ticket, the AI can identify common security pitfalls associated with that type of work. These pitfalls can be used to generate security recommendations for the developer working on the ticket, similar to how an experienced application security engineer would think about the ticket and communicate with the team.

AppSec Assistant - An AI Application Security Jira Plugin

AppSec Assistant is a Jira Cloud application that provides security recommendations directly within your tickets, with just the click of a button. These recommendations are tailored to the context of the ticket, offering guidance to your teams as early as the grooming process begins. Embedding security this early demonstrates a true commitment to secure-by-design methodologies. Your developers are happier because they don’t have to wait for availability from the security team, and your security teams can focus on higher priority tasks that are best handled by humans. Using AI in application security programs helps you scale your efforts without adding more people.

Challenges and Considerations

Data Privacy

While AI can significantly enhance security, it should also raise data privacy concerns. Using AI requires access to crazy amounts of data, posing risks of sensitive information mishandling. Ensuring that AI tools comply with data protection regulations and standards is crucial. AppSec Assistant allows you to bring your own OpenAI key, ensuring that your data remains under your control and is protected by your existing contracts and agreements.

Complexity and Cost

Implementing AI in application security is challenging. The complexity of setting up and maintaining AI systems requires skilled engineers and significant investment, which can be a barrier for smaller organizations. Alternatively, low-overhead, ready-to-use solutions can be implemented.

Shrinking Teams, Growing Products

In recent years, tech companies have had to become increasingly lean. Developers and security teams are expected to do more with less. Without advances in technology like AI, this model would be unsustainable. While AI cannot replace security professionals, it augments their capabilities, allowing teams to scale without the need to add expensive headcount.

Future Outlook

The future of AI in application security looks promising, and I'm really excited to see the creative ways that our industry will take advantage of this emergent technology. LLMs are getting better every day, and I think that we are only starting to scratch the surface of their potential in the security workd. As AI technology becomes more sophisticated, so do our attackers. I believe that integrating AI into security strategies will soon be the norm.

Conclusion

Embracing AI in application security is quickly becomming a necessity for those looking to stay ahead in today's digital environment. As we anticipate future security challenges, AI is just another tool in our kit, delivering better security with fewer human resources.

If you are trying to scale your application security program, now is the time to consider integrating AI-driven security solutions. It's not a silver-bullet, but security has always been a game of defense in depth. Adding another layer can help you stay ahead of the curve and mitigate the risks of new and emerging threats. And if you're interested in moving towards a secure-by-design methodology using cutting edge technology, why not give AppSec Assistant a try?