What Bug Hunting Actually Looks Like When You're Not Getting Paid for It
Most people treat vulnerability discovery like it's a sport you can get good at by reading two blog posts. It isn't. It's more like trying to find a specific crack in a concrete wall while someone's watching TV in the room. You need a method, you need patience, and you need to understand that your first fifty attempts will return nothing interesting. Start with recon. I know that sounds obvious, but the number of hunters who open Burp Suite without knowing what the target does is staggering. Spend the first two hours just mapping the application. Click every link. Submit every form. Check the robots.txt, sitemap.xml, and any exposed endpoints. This alone takes most people about an hour if the target is reasonably sized, sometimes three or four for enterprise-level targets with sprawling attack surfaces. Once you have the map, you prioritize by attack surface area. API endpoints, authentication flows, file upload functionality, and third-party integrations are where bugs actually live. The login page itself is rarely vulnerable unless it's doing something unusual like exposing stack traces on error.
I work through my toolchain in a specific order. First, I fire up an intruder for low-hanging enumeration — directory brute-forcing with a curated wordlist. wpscan for WordPress sites. ffuf as a faster alternative when the target throws a lot of 404s. Then I move to manual testing with Burp Suite's professional edition. The community edition handles basic interception fine, but you'll hit a wall fast once you need repeater, decoder, and comparer all working together. That's when the license fee pays for itself in about a week of actual use.
The Process Most People Skip
Here's the thing nobody puts in their write-ups: after you find something that looks like a bug, you spend more time proving it's real and not a false positive than you do finding it. A reflected XSS payload might render on screen, but that doesn't mean it's exploitable. Maybe there's a Content Security Policy you missed. Maybe the input gets double-encoded. Maybe the app rejects your request at the WAF level before it even reaches the backend. I once spent six hours hunting a potential stored XSS on a client portal. The input field reflected my payload cleanly, the schema looked vulnerable, and the parameter name literally contained "comment." I had the proof of concept written up. Then I realized the application was using a server-side template engine that escaped HTML entities before storage. The vulnerability existed in the input handler, but the rendering pipeline neutralized it entirely. That's a false positive that would have gotten my report rejected and possibly blacklisted from the program. The workaround is simpler than it sounds. Test everything in a controlled environment first. Set up your own instance when the vendor provides one. Use test accounts to verify the full request-response chain. Don't submit until you can demonstrate actual impact, not just that the input reached the server.
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What Beginners Keep Missing
Logic flaws are where the money is, and they're also where beginners consistently fail. They hunt for known CVE patterns — SQL injection signatures, obvious path traversal, that sort of thing. But a well-hardened application with patched dependencies is going to have none of that. What it will have is business logic that makes sense to the developer but creates an exploitable gap for someone who actually reads the requirements. For example, I worked a program where the checkout flow applied a discount code before validating that the user had sufficient account balance. The discount was capped at 50 percent, but there was no minimum price floor on the final transaction. A user could apply the code to a $10 item, drop the price to $5, then purchase it with a payment method that had exactly $0.01 in it. The system processed the $5 charge, the remaining $4.99 was effectively free money, and the payment gateway handled it because the transaction amount was below the fraud threshold flagging limit. Two lines of code in the backend handler would have prevented it. The vendor paid out a medium-severity bounty for it. Another thing: rate limiting. Everyone mentions it as if it's a silver bullet. It isn't. I've seen rate limiting implemented by IP address on applications behind NAT, which means legitimate users sharing an office network get blocked while attackers rotate through residential proxies without issue. I've also seen token-based rate limiting where the counter resets on session expiry rather than on a rolling window, allowing burst attacks that slip through between resets.
The Hard Truths About Bug Hunting Activities
Your success rate will be low. Really low. In my experience, a single bug report takes between four and twelve hours of focused work from initial recon to validated proof of concept. The acceptance rate across most programs hovers somewhere between 5 and 15 percent for first-time submitters. That means you're spending forty-eight to seventy-two hours of effort for every accepted report, and that's being generous. Bug bounty programs also have a selection bias problem. The ones that pay well have thousands of hunters competing for the same targets. The ones with fewer hunters tend to be lower-paying or have narrower scopes that don't match your skill set. There's no middle ground that works for everyone. If you're new to this, I'd recommend starting with VDPs — vulnerability disclosure programs that offer points, swag, or hall of fame recognition instead of cash. The competition is lighter, the feedback is usually more detailed since the triage team has more time, and you learn the reporting format without the pressure of being up against veterans who've been doing this for years. Once you've had five or six accepted reports from VDPs, the transition to paid programs is considerably smoother.
The other hard truth is that automation helps but it doesn't replace manual testing. Tools like Nuclei, SQLmap, and Dirsearch will find the obvious stuff. They'll also generate hundreds of false positives that you'll need to triage manually. I'd estimate that automated scanning covers roughly 30 percent of the surface area on any given target, leaving the remaining 70 percent to be found by hand. That 70 percent is also where the high-severity findings live.
Tools Worth Your Time
Burp Suite Professional remains the standard for a reason. The intruder module handles complex payload manipulation better than anything else I've used. The collaborator feature for detecting out-of-band vulnerabilities is genuinely useful and hard to replicate with open-source alternatives. ffuf is faster than dirb or gobuster for directory enumeration. It handles wildcard responses well and the rate-limiting flags prevent you from getting yourself blocked during aggressive scans. I typically run it with a concurrency of 50 and a delay of 100 milliseconds between requests. Nikto is still relevant for web server misconfigurations, though it's shown its age. Pair it with whatweb for fingerprinting and you'll have a reasonable baseline within twenty minutes of opening a target.
For API-focused testing, Postman with its Collection Runner is surprisingly effective when combined with Burp's proxy. You can export collections directly from Burp, add dynamic authentication handling, and iterate through endpoints systematically. It's slower than writing a custom script but easier to maintain when the target changes its API structure mid-engagement.
What Actually Gets Reports Accepted
Clear reproduction steps. Video or screenshot proof of the impact. A description of the business risk that doesn't rely on CVSS scores copied from a generator. Most rejected reports fail on one of these three points, not because the vulnerability isn't real. Write your reports as if the triage engineer has never seen your target before and is evaluating whether to spend their own time investigating your claim. That means including the exact URL, the HTTP method, the full request with headers, and a step-by-step sequence that anyone can follow without asking you clarifying questions. If you can't write a clear report, you probably don't understand the vulnerability well enough to submit it. The field moves slowly enough that the fundamentals haven't changed in fifteen years. Reconnaissance still accounts for the majority of successful findings. Manual testing still finds what automation misses. And persistence still beats cleverness every time.
