Essential Tools for CTF Challenges When tackling CTF challenges, having the right tools at your disposal can make all the difference. Below is a collection of powerful tools organised by challenge type, including links to download or explore further. Whether you’re dealing with steganography, reverse engineering, web exploitation, or network forensics, these tools will help you navigate the competition. If you have any suggestions reach out to me and I’ll happily add more tools :)

Understanding JSON Web Tokens and How Not to Implement Them Video Walkthrough Trying something new with this, I also have a video of me solving the challenge. Maybe some folks will find it useful to watch. Introduction JSON Web Tokens (JWTs) are a popular method for handling authentication in web applications. They’re compact, self-contained, and can securely transmit information between parties. However, like any security mechanism, they’re only as strong as their implementation.

What is a Large Language Model? If you’d like to skip to the poisoned LLM challenge solution click here This is quite a big question and will be covered in detail in its own blog post. Put simply, Large Language Models (LLMs) are advanced AI systems designed to understand and generate human (or ’natural’) language. They are trained on vast amounts of text data, learning patterns, structures, and nuances of language to predict and produce coherent sentences.

This is a short post aiming to provide some accessible context into the concept of MoEs, not a fully comprehensive or technical look into the technology. See the last section for further reading. That being said, please do reach out if you see any issues with this or any other posts. Prefer to listen? Your browser does not support the audio element. Download and listen to the audio file here!

Evolutionary Computing A Evolutionary Algorithm (EA) is a subset of Artificial Intelligence (AI), drawing inspiration from natural selection and biological evolution. These algorithms are particularly useful for solving complex optimisation problems (see P, NP, NP-Complete and NP-Hard Problems in Computer Science by Baeldung) where traditional methods may fall short. Often referred to as Genetic Algorithms (GAs), a specific type of evolutionary algorithm, they mimic the process of natural evolution to optimise towards a solution.

Understanding Neural Networks with Iris Dataset Today we will specifically look at implementing solutions to classification problems. A classification problem is where we are trying to categorise our input into two or more discrete categories. For example we could be categorising hand drawn numbers, that’s A-Z, a-z, 0-9 - This would be a multiclass classification problem with 62 classes. On the other hand, if we are classifying between malignant skin marks vs benign - this would be a binary classification problem.