Check reporting gaps
Provide program scope and your draft. Ask which asset, role, precondition or evidence item is unclear before the triage team has to ask.
AI bug bounty / verified evidence first
Give your finding a report that explains it.
A promising observation is not yet a complete bug bounty report. Use LLMsRelay's API to organize verified evidence, identify missing reproduction details and explain impact without inventing claims.
Sign in or create an account. Continue directly to the Uncensored wallet.
Put AI to work on the task
From rough notes to a report ready for your review.
Separate impact from speculation
Describe what you actually demonstrated. Request a clear impact section that distinguishes observed consequences from possible but unverified extensions.
Prepare a readable report
Structure your verified steps, expected behavior, actual behavior and supporting excerpts. Translate your own report while preserving technical identifiers.
A workflow you can verify
- 1
Confirm the program rules
Supply the relevant scope and submission requirements. Keep excluded assets and prohibited actions visible in your working notes.
- 2
Review what is reproducible
Provide your own verified steps and evidence. Ask the model to flag gaps, ambiguous language and claims unsupported by that evidence.
- 3
Edit before you submit
Check every step, remove secrets, review impact and format the final report. Submit through the program's own channel yourself.
Example prompt
Review this bug bounty draft against the supplied program scope. Identify missing evidence and unclear reproduction details. Rewrite the impact section using only demonstrated behavior. Preserve technical identifiers and mark all assumptions.
Ask for a useful result
- A report-completeness checklist
- A concise, evidence-based impact section
- A draft in the language your program accepts
Spend less effort untangling your notes.
Add AI review to your reporting workflow while keeping verification and submission in your hands.
One wallet. Usage you control.
One wallet. Usage you control.
Choose a prepaid pack in your dashboard. The $500 and $1,000 packs include extra usage balance.
You pay
$45
Usage balance
$45
You pay
$100
Usage balance
$100
You pay+20% Bonus
$500
Usage balance
$600
You pay+30% Bonus
$1000
Usage balance
$1300
| Model | Context | Input | Output |
|---|---|---|---|
| glm-5-3-uncensored | 262,144 | $4 | $12 |
| glm-5-3-uncensored-1m | 1,000,000 | $12 | $20 |
Rates depend on the selected model. Input, output and cached tokens are billed separately; a dollar balance is not a fixed number of tokens.
Connect your own workflow
- 1Top up the Uncensored wallet in your existing LLMsRelay account.
- 2Create an Uncensored API key in the dashboard.
- 3Set https://api.llmsrelay.com/v1 in your OpenAI-compatible client and choose a public model ID.
Before you connect
Does AI assistance guarantee a bounty?
No. Eligibility, duplicates, scope, severity and rewards are decided by the program. A model cannot guarantee acceptance or payment.
Will it submit reports for me?
This API offering does not automatically access a bug bounty platform or submit reports. You review and submit the final material yourself.
Should I submit a model-generated finding?
Submit findings you have verified and can reproduce within the program's rules. A plausible model explanation without supporting evidence is not a confirmed vulnerability.
Explore another security workflow
Make the evidence easy to understand.
Connect the API, review your draft and prepare a clearer report for the program.
Top up your AI balanceLLMsRelay provides model API access for authorized security research. Your tools run the tests; you verify the model's analysis.