Far to often organisations do all their security work on the few systems that are exposed to the internet. This might be acceptable when you begin the structured and ongoing work with security, but you should try to move on to defence in depth as soon as possible. Defence in depth is where you do not leave security to one layer of an application (or solution), but instead validate the security every step of the way. A common example for this is that even if you have a network firewall you do not disable the firewall in the operating system. This can be transferred to software development as well. In a more complex system each component should get the same security controls. It should not only be the frontend API that validates the input, instead each component should validate the data as untrusted when it receives it from another component. By doing so the resilience of the solution as a whole is greatly improved, where a single issue have limited impact, and might not even be exploitable. ...

In my role I always have to balance how I should spend my time. I usually have one project I’m currently working on, and a couple that are in the planning phase for the future. In addition there are requests of different sizes that interrupt any schedule. I love this dynamic, but it isn’t always easy. I’ve been using a simple todo software for quite a while now, to keep track of my tasks. However, I have used the list in an ad hoc manner. Not having a routine in my task management meant that the list always was incomplete. About a month ago I had enough and began figuring out a better way to organise my life. Without having reached the final and optimal organisation routine I wish to share my thoughts so far. ...

In my years of working as an application security (appsec) penetration tester I’ve come to the conclusion that there are so much more value to be added than pure technical vulnerabilities. To deliver the most value you have to be willing and able to walk the extra mile. Before getting into what can be done to increase the value, let’s dig into the two most common types of vulnerabilities. Technical Vulnerabilities The technical vulnerabilities are the most common vulnerabilities we see. This is where the application is abused to do something it shouldn’t, for example by injecting code or abusing weak cryptography. Even though the vulnerability is technical, it is important for the reporter to describe how it will impact the business. Otherwise the receiving organisation might not have enough of an understanding to prioritise the issues, and handle them accordingly. Even though a code injection can be used to pivot to other machines, the main impact for the business can often be linked to the confidentiality, integrity and availability of the application. As a tester it can be hard to accept, but a dom based XSS might be an accepted risk if the only impact is defacing the sight by pasting code into the searchbox. ...

We live in a world where technology compete for our attention, especially on our smartphones. Apps do everything they can to get us to open the app, and not leave it. At least that’s how I feel, with endless newsfeeds, notifications and autoplay, it’s so easy to just open the phone and get stuck. The feeling is not new, but the thing that pinned it down for me was the book Zucked by Roger McNamee [1]. It highlighted the reason for the feelings, both why companies do it and what they do. By using data companies have on their users they maximise their consumption. This can be in the form of video content on a streaming platform or browsing the newsfeed on social media. ...

Technical debt has become a common term when discussing the quality and maintainability of code. There are a lot of definitions of the debt, but they all have some things in common, that debt are the things in the solution that should be fixed but haven’t been fixed yet. This could include everything from lack of documentation or test coverage to code complexity. The debt might not have been there from the beginning, but rather been introduce while the solution grows. Another common denominator is that the debt will increase the cost of continued development within the solution. This can be seen in several different ways, for example adding a feature to a complex codebase would require more time than adding the same feature to the simple. ...