Challenges and Pitfalls of Automating Bug Bounty Submissions with AI

AI has found its way into the bug bounty space and is being utilized by hunters in all sorts of ways. While AI can certainly be used to find bugs in various software, one of its most important applications has been the submission of bug bounty reports.

Any hunter will tell you that sometimes, compiling reports and sending them in can be a cumbersome task that they’d rather skip. The AI market has responded to this demand with a host of tools that can do this instantly. However, even with this convenience comes a few pitfalls:

Formatting Errors

One thing to note about bug bounty programs is that each one has its own standard format for submission. Some ask for a report to be generated by the hunter and submitted manually and some offer a form for submission. Even within these, there is some variance in how the information should be presented. Things like summary and console logs might be required in different ways from one program to the next. The point of each program having a standardized format is the make the review process faster and more organized for all involved.

By using AI to automatically submit bug bounties, there is a higher chance of formatting errors. A human bug hunter submitting errors will know, in real-time, to adjust the data to fit the format of the programs they are submitting to but an AI can make mistakes. Think of how autofill on basic online forms can overlook certain presentation nuances. By using AI for the submission process, hunters risk submitting the correct information in the wrong format. In best best-case scenario, the review process takes a bit longer and the reviewer is annoyed. Worst-case scenario, their eligibility for the program and ability to get paid is compromised.

Reduced Quality Control

Bug bounty hunting relies on human intuition, and sometimes, this kicks in at the submission stage. Perhaps the wrong screenshot was taken, or an error was made in the report. It is virtually a cliche at this point that we sometimes only spot errors right as we’re about to submit things. By outsourcing the submission process entirely to AI, we remove this final layer of quality control from our bug bounty process. And given how important quality control is to ensure the highest-quality software, many bug bounty hunters might deem this too big of a risk to take.

Submission Spam

The process of submitting bug reports can be a bit cumbersome and is very admin-heavy. But we have to acknowledge that there is a major benefit to this, namely that it helps to prevent spam. A bug bounty hunter is less likely to go through the stress of filling report forms for every suspected bug if they aren’t at least a little confident that it is legitimate. This stops bounties, especially the higher-paying ones, from being inundated with spam from hunters essentially playing a numbers game.

But when AI comes in and automates the process, this partially goes out the window. A bug hunter (especially one who already uses AI in the bug discovery process) can then choose to submit every suspected bug to raise their chances of getting the bounty.

The bounty programs, in turn, could find themselves dealing with a larger influx of spam reports.

Skill Impact on Bounty Hunters

AI is being used in several parts of bug bounty hunting, including teaching new hunters and as part of the bug discovery process. While this makes bug bounty education more accessible, overreliance on AI can lead to hunters, especially new ones, having limited hands-on experience. If you fill dozens of bug report forms in a single year, you’ll be so good at it that you can do it in your sleep. You’ll also have your finger on the pulse of the submission process, including how it changes over time. If AI is doing all of this for you, that technical know-how and deep understanding of the system can be a bit lost.

This might be less of an issue for bug bounty veterans but newbies will be most impacted.

Now that we’ve looked at some of the possible pitfalls of using AI for buy bounty submission, the question remains of whether or not hunters should continue to use AI or skip these tools altogether. This is a complex answer and depends on several factors.

Formatting errors will become less of an issue with time as AI tools become better developed and more equipped to handle the nuances of the submission process. Submission spam, like all AI-powered spam, is something that the platforms themselves will have to handle. As long as AI makes it possible to submit bug reports, many will be willing to cut corners and turn bug reporting into a numbers game. Limiting the number of reports a single hunter can submit could be one way to cut down on it.

Reduced quality control and skill impact illustrate the core issue as well as the core solution. If bug hunters become so reliant on AI for their processes that they don’t apply human intuition or double-check its output, issues will arise. If bug hunters approach AI as more of an assistant and a collaborator than a digital workhorse designed to do their tasks for them, this will be less of an issue. By reviewing their reports before submission and doing a good chunk of the submission manually, the bug bounty space will benefit.

AI has revolutionized the bug bounty space and can seemingly do everything from looking for common issues in code to generating and submitting reports. But before you rush to submit tons of reports using AI, it is worth being aware of some of the drawbacks. AI limits quality control and can end up making mistakes in the submission process, among other things. Bug hunters are, therefore, advised to use such tools for collaboration and not to substitute their own efforts.