How AI is Making Bug Bounties More Accessible for New Hackers

Bug Bounty hunting is one of the most important processes when securing computer programs, tools, games, and all sorts of software post launch. Bug Bounty hunting sees program developers invite hackers and programmers to review their products and find flaws and vulnerabilities within them.

The idea is simple; find these issues before the public (or, worse still, a malicious actor) does. In exchange for finding these bugs, the bounty hunters get rewards, usually monetary. But as AI is touching every part of the world, bounty hunting isn’t being left behind. More specifically, it is making these bounties more accessible in the following ways:

For a lot of aspiring bug bounty hunters, getting adequate training is a major barrier to entry. Bug bounty hunting courses can cost hundreds of dollars depending on where you buy from and sometimes, free materials offer a complicated explanation of the different concepts. This is where AI comes in. Millions of people are already using tools like Chat-GPT to explain their schoolwork to them and the same can be done with bug bounty training.

Simply imputing a prompt like ‘explain compatibility bugs in simple English’ means that even the less tech-savvy of us can start on their journey to becoming a bug bounty hunter. Besides learning to find bugs themselves, AI can also be used to generate recommendations for hunters looking to begin work. By analysing the hoards of information available online, AI programs can recommend the best companies to reach out to based on the hunter’s skill level, expertise, and interests. The result of this is not only bug bounty hunters who can learn faster and easier but also those who can begin their careers with fewer pitfalls and errors.

A big part of bug bounty hunting is analysing a large mass of data and trying to find inconsistencies or flaws in them. This is often done by looking through the code in the program to find errors that will show up in execution. For example, imagine the code that grants access only when provided with a password that has a flaw. This means, essentially, that even users who don’t provide the correct password may be granted access to an account or certain services. Thus, bug bounty hunting involves looking through a mass of code to find this out.

The problem is that this process can be slow and tedious, especially for newer hackers whose eyes are not yet as fast to spot these errors in a flash. But with AI, these issues can be found much quicker. By Simply pasting in the lines of code, the AI can look through them and spot common issues in a flash. Think of the way text editing software can spot grammatical errors even a human might miss. For newbies, this saves a lot of time and effort.

One challenge that bug bounty hunters face, especially when they are first starting out, is making sure that their findings are accurate. The last thing they want to do is report a false positive or negative test and lose out on their rewards. In this sense, AI can come in to not only help with findings but also ensure the accuracy of reports. As we covered in our last point, AI tools can look through a mass of codes to spot errors. In the world of bug bounty hunting, there is the 80/20 rule, also known as the Pareto principle. It states that 80% of bugs are found in 20% of the program and these are the biggest causes of issues for users. As such, finding that flawed 20% of the program solves a majority of user issues.

If AI tools are utilized to review the program, the areas with the most issues can be found, meaning bounty hunters can more accurately identify the issues. After the bounty hunter has identified the issues, AI can further verify that they are indeed correct and this saves them the awkwardness of misreporting bugs.

Anyone who has done bug bounty hunting will know that it is not enough to simply find the issues; you also have to compile a report of them and submit it to the company to get your reward. Sometimes, writing this report can be just as tedious as actually finding the issues and for newer hunters, getting the format correct can be an issue. But just as AI can write emails, social media posts, and even entire novels, it can create bug bounty reports.

By importing the flaws detected and giving the tool a prompt, it can instantly generate a report. On top of this, users can have the tool follow exact guidelines, saving them hours of back-and-forth trying to get it right.

AI is one of the most groundbreaking tools of our time because they are designed to learn from both the data we give them and their own performance. In the context of bug bounty hunting, this means that they have the capability to get better and better. A model used for bug bounty hunting in 2024 has years of experience helping hunters to spot errors in code and performance. As such, a tool in 2034 will be even more efficient.

This means that new hackers will constantly have new and improved tools to help them learn faster and deliver results more efficiently.

Getting started with the world of bug bounty can be very intimidating. You’ll need to learn about the right companies to offer your services to, and the format to present your findings, and this is all before you begin finding the flaws. But in 2024, AI is making the transition easier for newbies by automating and simplifying processes.

Those looking to learn can have different concepts broken down for them and even as they begin looking for bugs, AI comes in handy, saving time and effort. Thanks to AI new hackers can look forward to an easier journey with bug bounty hunting.