From Beginner to Bug Hunter: Learning Cybersecurity in the AI Era.

Finding a real security flaw and getting paid for it is an appealing goal when you are learning cyber security. Bug bounties give you a chance to test your skills on real software and help its developers make it safer.

Headlines about programs closing or pausing under a flood of AI reports can make that route feel less certain.

Earlier this year, curl, the widely used data transfer tool and library, ended its paid bounty program after similar problems.

As a beginner, these decisions raise a practical question about where to put your effort.

A useful starting point is understanding what went wrong, then building the skills to produce findings that someone else can verify.

Why some bug bounty programs are pulling back

A bug bounty program rewards eligible security findings under a defined set of rules. Developers must still review each submission, reproduce the issue and assess its impact.

A convincing report about an imaginary vulnerability can consume time that a small security team needs for genuine problems.

When curl ended its program on January 31, 2026, maintainer Daniel Stenberg explained how the quality of submissions had deteriorated. He confirmed vulnerabilities fell from above 15% in previous years to below 5% starting in 2025. Across its lifetime, the program had helped uncover 87 confirmed vulnerabilities and paid researchers more than $100,000.

Those figures describe curl’s experience specifically.

Google’s pause also has a defined scope: supply chain submissions and outstanding reports remain unaffected. Its wider vulnerability rewards programs paid researchers $17.1 million in 2025. The closures and restrictions show pressure on particular programs, while other opportunities continue.

A glimmer of hope

In April, Stenberg reported that submission quality had improved and the share of confirmed vulnerabilities had returned to roughly 15% to 16%.

He observed extensive AI use in those reports. Researchers were finding real problems, although the growing volume still created work for maintainers.

For someone learning, the lesson is to take responsibility for the evidence behind a finding. Generating a report is easy compared with establishing whether its claim holds up.

Build the foundations you need to check a finding

Before chasing your first payout, learn how the systems you plan to test work. For web security, that means understanding HTTP requests, login sessions, permissions and how applications handle data.

Basic networking and command line skills help you investigate what is happening when a tool produces an unexpected result.

Practise these ideas in an environment designed for learning. You can make mistakes, repeat a test and inspect the result without affecting a live service. Choose a specific skill for each session, such as explaining a request or identifying which account is allowed to access a resource.

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

After a lab, write down what you changed, what happened and why. Then repeat the task with your notes closed. Being able to explain and reproduce the result is a useful way to check your progress.

Use AI to support your learning

AI can help explain an unfamiliar error, suggest questions to investigate or review the clarity of your notes. You will get more useful practice if you attempt the task first and give the model a specific point of confusion.

After inspecting a lab request, for example, ask the model to explain how the session cookie relates to the logged-in account. If you are stuck, ask for one hint and describe what you have already tried. Then test your next step and explain why it worked.

Finish the session by doing the task again without assistance. If you can explain which evidence supports the finding and what would disprove it, you have learned something you can use beyond that exercise.

Make every report possible to reproduce

Imagine an authorized training application with two test accounts. Changing an invoice identifier returns a successful response. To establish an access control flaw, you still need to show that one account can access the other account’s private test invoice and that this violates the application’s intended permissions.

Record the behavior you can demonstrate, including the conditions required for it to happen. Keep any claim about wider impact tied to evidence.

Before submitting the finding, check that your report includes:

• The affected asset or software version, with confirmation that your testing falls within the program's scope.
• The setup and exact steps needed to reproduce the issue, including any required account permissions.
• The expected behavior and the actual result, supported by relevant requests, responses or other evidence with sensitive information removed.
• The demonstrated security impact, with any assumptions or untested possibilities clearly identified. 

Give your first month a clear purpose

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

• In week one, work through networking, operating system and web basics. Draw a simple request flow and explain where identity and permissions are checked.
• In week two, choose one vulnerability type and practise it across several authorized labs. Keep a short record of the evidence behind each result.
• In week three, use AI for hints after making your own attempt. Revisit an earlier lab without help, then examine the logs or other evidence a defender could use to spot the activity.
• In week four, write a complete report for a lab finding. Ask a peer to reproduce it from your instructions, or follow them yourself from a fresh setup and fix anything missing.

By the end, you should have a record of your reasoning and a report you can improve. Continue practicing wherever you still need help. Readiness for a live program depends on your skills and its rules, so use the month as a starting point.

Keep your career options open

Bug bounty work is one way to apply security skills. The same habit of checking evidence matters in security operations, incident response and penetration testing.

When you investigate a lab, practice explaining how a defender could detect the issue and what a developer could change to fix it.

Bounty income depends on a finding being valid, eligible and covered by the program’s payment rules.

Learning will be easier to sustain if you judge progress by the skills you are building. Save clear lab notes and share write-ups where the training platform permits them, so you have concrete work to discuss as you explore security roles.

For your next session, choose one exercise, make your own attempt and keep the evidence that explains the result.

And if you need guidance along the way, TryHackMe offers the ultimate path to get you started just as you would in an actual security environment.

Sponsored and written by TryHackMe.