AI Bug Bounty: Scope, Fairness & Incentive Evaluation
An internal stakeholder survey evaluating scope clarity, decision fairness, and incentive effectiveness in your AI bug bounty program over the past 6 months to guide program improvements.
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AI-Powered Questions
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Template Overview
25
Questions
AI-Powered
Smart Analysis
Ready-to-Use
Launch in Minutes
This professionally designed survey template helps you gather valuable insights with intelligent question flow and automated analysis.
Sample Survey Items
Q1
Chat Message
Welcome! This brief survey collects your feedback on fairness, scope clarity, and incentive design in our AI bug bounty program over the past 6 months.
Your responses are confidential and will be reported in aggregate only. There are no right or wrong answers—we value your honest perspective. The survey takes approximately 8–10 minutes. Participation is voluntary, and you may stop at any time.
Q2
Multiple Choice
In what ways are you involved with the AI bug bounty program? (Select all that apply.)
Program owner/manager
Security/AppSec
Engineering/Platform
AI/ML
Legal/Compliance
Trust & Safety
Procurement/Vendor management
Product/UX
Executive sponsor
Not directly involved but aware of the program
Q3
Dropdown
How long have you been involved with or aware of the AI bug bounty program?
Less than 3 months
3–6 months
6–12 months
1–2 years
Over 2 years
Q4
Opinion Scale
How clear are the program's overall objectives to you today?
Range: 1 – 7
Min: Not at all clearMid: NeutralMax: Extremely clear
Q5
Opinion Scale
How clear is the definition of which AI/ML assets and models are in scope?
Range: 1 – 7
Min: Not at all clearMid: NeutralMax: Extremely clear
Q6
Opinion Scale
How clear is the definition of which vulnerability types and AI-specific attack vectors qualify?
Range: 1 – 7
Min: Not at all clearMid: NeutralMax: Extremely clear
Q7
Opinion Scale
How clear are the severity classification criteria and corresponding payout tiers?
Range: 1 – 7
Min: Not at all clearMid: NeutralMax: Extremely clear
Q8
Opinion Scale
How clear are the out-of-scope exclusions and rules of engagement?
Range: 1 – 7
Min: Not at all clearMid: NeutralMax: Extremely clear
Q9
Long Text
If any scope wording feels ambiguous or incomplete, please share specific examples or phrases you would improve.
Max chars
Q10
Opinion Scale
Thinking about the last 6 months, how fair overall have our bounty decisions been?
Range: 1 – 7
Min: Very unfairMid: NeutralMax: Very fair
Q11
Opinion Scale
How consistent have severity classifications been across similar submissions?
Range: 1 – 7
Min: Very inconsistentMid: NeutralMax: Very consistent
Q12
Opinion Scale
How fair have payout amounts been relative to the effort and impact of submissions?
Range: 1 – 7
Min: Very unfairMid: NeutralMax: Very fair
Q13
Opinion Scale
How timely and communicative has the triage process been?
Range: 1 – 7
Min: Very poorMid: NeutralMax: Excellent
Q14
Opinion Scale
How fairly have duplicate or disputed reports been handled?
Range: 1 – 7
Min: Very unfairlyMid: NeutralMax: Very fairly
Q15
Opinion Scale
How adequate are current payout amounts relative to the effort and impact of submissions?
Range: 1 – 7
Min: Far too lowMid: NeutralMax: Far too high
Q16
Multiple Choice
Which incentives most motivate high-quality submissions? (Select up to 3.)
Cash bounties
Public recognition/leaderboard
Private recognition (internal kudos)
Swag/merchandise
Invitation-only access or beta programs
Faster coordinated disclosure timelines
Access to datasets/APIs/sandboxes
Higher severity multipliers/bonuses
Charity donation option
Q17
Multiple Choice
Which changes would most improve fairness and clarity in the program? (Select up to 3.)
Publish clearer severity examples
Share payout ranges by severity
Standardize triage SLAs
Provide a scope decision tree
Add public case studies
Introduce independent review for disputes
Expand test environment access
Increase frequency of scope updates
Q18
Ranking
Please rank the following success metrics from most to least important for evaluating the program.
Drag to order (top = most important)
Number of valid reports
Reduction in repeat issues
Time to triage
Time to fix
Researcher satisfaction
Severity-weighted impact
Coverage across AI components
Q19
Opinion Scale
How likely are you to recommend our AI bug bounty program to an external security researcher?
Range: 0 – 10
Min: Not at all likelyMid: NeutralMax: Extremely likely
Q20
AI Interview
We'd like to explore your feedback in more depth. An AI moderator will ask you a couple of follow-up questions based on your earlier responses about the bug bounty program.
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Reference questions: 6
Q21
Long Text
Based on your responses in this survey, please share any additional thoughts or suggestions for improving the AI bug bounty program.
Max chars
Q22
Dropdown
How long have you worked at this company?
Less than 6 months
6–12 months
1–3 years
3–5 years
Over 5 years
Prefer not to say
Q23
Dropdown
Which region do you primarily work in?
North America
Latin America
Europe
Middle East
Africa
South Asia
East Asia
Southeast Asia
Oceania
Prefer not to say
Q24
Dropdown
Approximately how many bounty reports have you personally reviewed in the last 6 months?
0
1–5
6–20
21–50
51+
Not applicable
Q25
Chat Message
Thank you for completing this survey. Your feedback will directly inform improvements to scope clarity, evaluation fairness, and incentive design in the AI bug bounty program.
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