How to Use WormGPT AI for Bug Bounty Triage

Bounty Math

Bug bounty reward is a function of three variables: how many valid reports you submit, how fast you submit them, and how much of the triager's time you waste. Most hunters optimise the first and ignore the other two.

AI-assisted triage helps with all three — it shortens the path from code to confirmed finding, and it forces structure into the report, which is what keeps triagers on your side.

Step 1: Choose Targets by Code Shape

Before writing a single payload, look at the program's scope and ask where an analysis engine will be most productive:

• Programs with source in scope, or open-source components.
• Large JavaScript or Python codebases where data flow is long and sanitisation is inconsistent.
• Programs with an authentication surface worth chaining — reset flows, invite flows, tenant boundaries.
• Programs where the crowd is already saturated with XSS duplicates; look at authorisation and business logic instead.

A crowded target's obvious bugs are already submitted. Depth beats breadth.

Step 2: Rank Before You Read

Point the platform at the in-scope repository or the code paths you can legitimately obtain. Use file ranking to decide where to spend the first hour. On a codebase of hundreds of handlers, the top-ranked handful typically contains the reachable sinks — the rest is either dead code or well-guarded.

Step 3: Confirm, Then Reduce

Bounty triagers reject unproven claims. Before writing a report:

1. Reproduce in your own account, with the minimum privilege required.
2. Reduce the PoC to the smallest request that still works.
3. Note the exact impact with your privilege level — not with an admin's.

"Any authenticated user can..." is a valid claim. "Any user could probably..." is not.

Step 4: Beat Duplicates by Going Deeper

Duplicates come from stopping at the first symptom. If you find an IDOR, the field that matters is which data can be reached and whether the same pattern exists on other endpoints. If you find reflected XSS, the question is whether a CSP bypass or a stored variant exists in the same flow.

Chain analysis is your differentiator: a single medium bug is often already reported, a two-step chain reaching another tenant usually is not.

Step 5: Write the Report the Triager Wants

A report that gets triaged in one pass has six things:

• Title naming the vulnerability class and the endpoint.
• Summary in two sentences: what you can do, and what you needed to do it.
• Steps to reproduce, numbered, with real requests and responses, redacted for your own account only.
• Impact, stated with the privilege level you actually held.
• Evidence, a PoC script or a recording — never a screenshot of a console alone.
• Suggested fix, one line.

Do not pad. Do not include five unrelated observations to seem thorough; those become five separate reports or a slow triage.

Step 6: Track What Repeats

Keep your own workspace per program. Over months you will see the same classes recur in the same components — that pattern is worth more than any single report, and it is the shortest path to a bounty the crowd has not already filed.

Key Takeaways

• Choose targets where code shape favours analysis: large, long-data-flow, weak-authorisation codebases.
• Use file ranking to pick where to spend the first hour of a program.
• Confirm and reduce PoCs before writing anything.
• Beat duplicates by chaining findings, not by reporting the first symptom.
• Structure reports: title, summary, steps, impact at real privilege, evidence, fix.

FAQ

Does using AI count as automated scanning that some programs ban? Read the program's rules. Analysis of code you are permitted to obtain, with manual validation before submission, is normal research; mass automated probing of live targets often is not.

Can I submit findings generated entirely by the tool? Validate them yourself first. Unvalidated AI output is the fastest route to being marked as a low-quality reporter.

What stops me from wasting time on duplicates? Depth: chains and privilege-boundary bugs are rarer than single reflected parameters, so fewer people get there first.

Should I mention the platform in the report? Not required. What matters is the evidence and the reproducibility.