Author: Aituglo
AI is everywhere now. Depending on who you ask, it might be something that revolutionizes security and personal life—or it might be a completely useless slop generator. The reality is that AI, in its current form, is a mix of both. AI is not replacing hackers, but we still need to learn from it and use it to augment our skills. Hackers who can harness the benefits of AI will absolutely outperform those who don’t.
The fear of AI is often founded on reasonable worries. Not only is AI a big topic of conversation, it’s fast. It iterates quicker than humans. AI’s capacity to generate everything from realistic images to a fully automated pen test made by agents can feel jarring and even scary. But rest assured, we’re simply on the precipice of yet another technological era. AI is not a threat; it is an amplifier of existing skills and work capacity. Think of it primarily as a new tool that is powerful, flexible, and very good at the repetitive parts of hacking that most people didn’t like in the first place.
AI won’t replace the human intuition or creativity needed to find bugs. That feeling you get when you approach a target knowing that something feels a little off? Yeah, that’s your human intuition talking, and AI can’t replicate it. But it can explain complex systems in a matter of minutes, decode virtually anything, and provide quick analytical shortcuts that typically take a long time to discover manually. For example, you can ask it how a specific OAuth flow works, have it rewrite a complex regular expression, or have it help structure a CSRF or XSS proof of concept (PoC) with clean, reliable code. AI helps maintain momentum and spring you from research purgatory.
When you accept that AI is a companion rather than a competitor, you can start to visualize ways to integrate it into workflows and make life a lot easier.
Implementing automation for the first time can feel overwhelming, as there is so much to learn. It can feel like if you don’t hyper optimize every option, you’ll miss out on something (hacker FOMO). Try to resist doing everything at once. Take your time, learn, and slowly curate tools and strategies that work best for your style.
Pro tip: I don’t recommend starting with long automation and heavy stuff. These things are complex and will likely cause you to give up altogether (I certainly did).
There are frameworks available that will help you initiate your automation process. For example, you might start by using nodes and simple tools. Nodes are basically building blocks that you connect together to create a workflow. Each node does one specific thing. For example, one node can fetch data from an API, another can filter results, and yet another can send a message to Telegram. You don’t need to write code. You just drag and drop these nodes and connect them visually. It’s pretty much like drawing a flowchart, but the flowchart actually runs. This simple automation can help tremendously because you can focus on the logic of what you want to achieve instead of struggling with implementation details. Another simple tool worth mentioning is Zapier, which works similarly but is more beginner-friendly and cloud-based. I personally prefer n8n because it’s open source and you can self-host it, but Zapier is a good starting point if you just want to try automation without setting up anything.
You only need a handful of solid automation scripts to reduce the amount of repetitive work in your day. One of the easiest tools to start with is n8n. It’s designed to remove friction from your everyday process and allow you to focus on the logic of a method rather than the implementation.
I recommend using the open-source version and installing it on your device.
You can install it on a server, your computer, or almost anywhere.
You should see something that resembles the image below. In n8n, you can create different workflows and add nodes that are straightforward and easy to understand.
Pro tip: Take a look at these templates to gain a better idea of the types of workflows you can build. Simply download the templates and import them into your instance.
One way to use n8n that I find interesting is monitoring the latest news or common vulnerabilities and exposures (CVE) to stay up to date on what’s going on in the hacker and cybersecurity field. It’s very useful to stay instantly informed on PoCs that are available for a specific CVE.
A significant example is the recent React2Shell incident. This was a critical RCE vulnerability (CVE-2025-55182) affecting React Server Components and Next.js, rated CVSS 10.0 (basically the worst possible score). When it was publicly disclosed in December 2025, threat actors started exploiting it within hours. If I had had my n8n workflow set up to monitor new CVEs, it would have pinged me the same morning with a summary explaining that this was a big deal and why. Being alerted directly means that you could have quickly checked which of your targets were running Next.js with App Router. I found a few that were vulnerable before they had time to patch. Instead of having to manually scroll through security news or Twitter, this workflow saved me a ton of time. I got a clean Telegram message explaining the impact and what to look for.
Specifically, you can use n8n to build a workflow that grabs all the latest CVEs and creates a digest that is sent through Telegram or WhatsApp every morning. The AI node can also summarize what’s really important to know. This creates a filtered briefing that is relevant and actionable. It will keep you informed on what technologies are affected, what the potential impact is, and the scenarios in which this vulnerability is applicable to your targets. All of these results can be delivered to your phone as a clean message.
Another great way to use n8n is by implementing a workflow that monitors all your scopes on Bugcrowd. This will keep you focused on which scopes make the most sense for you, when to act on them, and if they’re worth your time.
Pro tip: I use bbscope for this and wire it to the AI to power everything.
Every day, there are new updates, endpoints, and assets. Discovering changes late means missed opportunities. Using n8n, set up a bbscope to run on a schedule. From there, have it compare the latest output with the previous run. Have it send a notification whenever something new pops up.
Take it a step further. An AI node can even summarize changes and explain why they might matter. But don’t stop there. Think even bigger. You can even wire that node to a Model Context Protocol (MCP) server and have it start doing some recon on the new assets directly. It’s amazing how you can build powerful stuff very easily these days.
These two examples are very simple but very helpful in the long run. Here are some other things you can build yourself:
Personally, I don’t use AI to automate a lot of reconnaissance stuff because I prefer to do this myself. That being said, automation is great for managing repetitive tasks so that you can focus on manual exploration. Manual exploration is what separates AI from humans; it’s where the heart of bug bounty lies.
Caido is a good example. On its own, it already provides a clean interface with everything you need to do your manual testing (Burp Suite is another good example). But once you integrate AI into it, it becomes something that resembles an assistant. With Caido + AI, you have a little assistant that watches traffic and helps you understand patterns. You can ask it to summarize a series of requests, highlight unusual behaviors, or explain complex flows. This is especially effective when testing large applications with a lot of functionality.
The main way I use Caido is by leveraging the Caido MCP by Slonser called Ebka. Another great way to implement Caido + AI is with the Shift plugin. Shift can assist you with all kinds of boring tasks and even call different agents for you with a simple question or request.
Here are some additional ways I use Caido:
MCP is a kind of API but for AI. It allows AI models to interact with your real environment. Rather than talking to an isolated chatbot, you talk to an assistant that has access to your external data sources, software applications, and tools. This is far superior because the AI bot has working context. This enables entirely new workflows. For example, you can ask the AI to review all the JavaScript files for suspicious logic and then ask it to analyze all the traffic for your proxy from the last hour. MCP transforms AI from a passive responder into an active tool integrated directly into your hacking environment.
With MCP integration, tools like Cursor and Claude Code can assist directly with PoC development and debugging. With these tools, you simply describe the logic and let the AI generate the PoC for you. For instance, I use it to help me write ATO exploits for XSS. To do this, I usually grab a CSRF token from somewhere and then make a specific fetch to change the email of the account. Manually, this process is very boring, but AI will do this for you, freeing up your time. The result is not only an increase in speed but also lower friction.
You think, and AI does.
It’s easy to look at AI and think it will automate everything, including hackers, but that ignores the nuance of bug bounty and how it actually works. Good hacking is built on creativity, intuition, and inspiration. It’s about exploring edge cases and thinking of new ways to break something that has already been broken. These cannot be automated. Instead, think of AI as a little assistant that helps with the uninteresting stuff. It gives beginners an easier time understanding complex topics, intermediate researchers more time to dive deeper into analysis, and experienced hunters the ability to explore larger systems while automating.
AI is not the end of bug bounty. It’s a new tool that you need to be using. You are not competing against AI; you are competing against hackers who know how to use AI effectively.
If you learn to work with AI now, you won’t just keep up—you’ll get ahead.