Learn Cybersecurity and Become a Bug Hunter in the Age of AI

Bug bounty programs can give aspiring security researchers hands-on experience and a chance to earn money by finding vulnerabilities in real software. However, recent program closures and suspensions, along with a surge in AI-generated reports, have made the path less predictable. For beginners, the most reliable approach is to build strong technical foundations, test responsibly in approved environments, and produce findings that other people can reproduce and verify.

Earlier this year, curl, the widely used data transfer tool and library, ended its paid bug bounty program after facing similar issues. These decisions raise practical questions about where new researchers should focus their time and how they can develop skills that remain valuable beyond any single bounty program.

Why some bug bounty programs are withdrawing

Bug bounty programs reward eligible security discoveries according to a defined set of rules. Developers and maintainers must review each submission, reproduce the reported behavior, and assess its security impact.

Reports describing fictitious or unverified vulnerabilities can consume the time of small security teams that need to focus on genuine issues.

When the curl program ended on January 31, 2026, maintainer Daniel Stenberg explained that the quality of submissions had declined. He confirmed that the proportion of submissions representing vulnerabilities had fallen from more than 15% a year earlier to less than 5% in 2025 and beyond. Over its lifetime, the program contributed to the discovery of 87 confirmed vulnerabilities and paid researchers more than $100,000.

Those figures reflect curl’s experience with its own bounty program and do not necessarily describe every program.

Google’s suspension is also limited in scope. It does not affect supply chain submissions or outstanding reports. Google’s extensive vulnerability bounty program paid researchers $17.1 million in 2025. Although closures and restrictions indicate pressure on some programs, other opportunities remain available.

A possible improvement in report quality

In April, Stenberg reported that the quality of submissions had improved, with the percentage of confirmed vulnerabilities rising from around 15% to 16%.

He also observed extensive use of AI in those reports. Although researchers had identified the real problem, the increased volume of submissions was still creating additional work for maintainers.

The lesson for people learning security is to take responsibility for the evidence behind every finding. Writing a report is easier than checking whether its claims are accurate, reproducible, and within scope.

Build the foundation needed for security research

Before chasing a first bounty payment, learn how the system you plan to test works. For web security, that includes understanding HTTP requests, login sessions, permissions, and how applications handle data.

Basic networking and command-line skills can help you investigate unexpected results when a security tool behaves differently from what you anticipated.

Practice these concepts in an environment designed for learning. Labs allow you to make mistakes, repeat tests, and inspect results without affecting a real service. Give each session a specific objective, such as explaining a request or identifying which accounts should be allowed to access a resource.

TryHackMe’s Cyber Security 101 Learning Path covers networking, Linux and Windows fundamentals, web application fundamentals, and offensive and defensive security. Following a structured path gives each tool a purpose and helps you understand the evidence it produces.

After completing a lab, record what you changed, what happened, and why. Then repeat the task without looking at your notes. Being able to describe and reproduce your results will make your progress easier to measure.

Use AI to support learning

AI can explain unfamiliar errors, suggest questions to investigate, and help check the clarity of your notes. You will get more useful practice if you attempt the task first and give the model specific details about what you do not understand.

For example, after inspecting a lab request, ask the model to explain how session cookies relate to login accounts. If you get stuck, request one hint and describe what you have already tried. Then test the next step and explain why it worked.

End the session by running the task again without assistance. If you can explain which evidence supports or disproves your findings, you have learned a skill that can be applied beyond the exercise.

Make every security report reproducible

Consider an approved training application with two test accounts. Changing an invoice identifier returns a successful response. To demonstrate an access control flaw, you must show that one account can access the other account’s private test invoices and explain why this violates the application’s intended permissions.

Record demonstrable actions and the conditions required for them to occur. Keep claims about broader impact tied to evidence rather than assumptions.

What to include in a vulnerability report

• Confirmation that the affected asset or software version is in scope and that testing followed the program’s rules.
• The setup and exact steps required to reproduce the issue, including any necessary account privileges.
• Expected behavior and actual results, supported by relevant requests, responses, or other evidence with sensitive information removed.
• Proven security impact, with assumptions and untested possibilities clearly identified.

Give your first month a clear purpose

A month of focused practice can help establish productive habits. Adjust the pace to your starting point and measure progress by what you can explain and repeat.

• First week: Learn the basics of networking, operating systems, and the web. Draw a simple request flow and explain where identity and permissions are checked.
• Second week: Choose one vulnerability type and practice it in multiple certification labs. Record the evidence behind each result.
• Third week: Use AI as a hint only after trying the task yourself. Revisit previous labs without assistance and examine logs and other evidence that defenders can use to identify activity.
• Fourth week: Create a complete report based on your test results. Ask a colleague to reproduce the instructions, or follow them yourself from a new setup and correct anything that is missing.

By the end of the month, you should be able to record your reasoning and create a report that can be improved. Continue practicing areas where you still need help. Use the month as a starting point, since preparation for a live program will depend on your skills and that program’s rules.

Keep your cybersecurity career options open

Bug bounty work is one way to apply security skills. The same discipline of reviewing evidence is important in security operations, incident response, and penetration testing.

As you work through labs, practice explaining how defenders could detect a problem and what developers could change to fix it.

Your bounty earnings will depend on whether your findings are valid, eligible, and covered by the program’s payment rules.

Measuring progress by the skills you are building can make it easier to continue learning. Keep clear lab notes and share them if your training platform allows it. This gives you specific tasks to discuss when considering security roles.

For your next session, choose one exercise, attempt it yourself, and preserve enough evidence to explain your results.

If you need guidance along the way, TryHackMe provides the ultimate path to get started, much like working in a real security environment.

Sponsored and written by TryHackMe.

Source: www.bleepingcomputer.com