Evaluate Bug Bounty Program Manager candidates across 4 weighted areas: technical depth, real incidents and findings, risk judgement, and getting things fixed. Technical depth leads at 35%, so check they can triage submissions themselves: reproducing a PoC, assigning CWE and CVSS v3.1 vectors, spotting chained SSRF or IDOR versus a duplicate. Use the rubric to compare role-specific evidence consistently.
For technical depth, look for evidence the candidate reproduces reports independently, defends CVSS vector choices component by component, and distinguishes real chained impact from theoretical severity inflation. For real incidents and findings, look for evidence the candidate cites named programs with report volumes, bounty tables, valid-report percentages, and a specific critical finding they drove from inbox to fix.
Apply the written 1–5 anchors to every answer, record the evidence behind each rating, and use the factor weights to reach a consistent overall assessment.
Complete evaluation framework
What to assess and how to score it
Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.
01
Evaluation factor
Technical depth
35% weight
Check they can triage submissions themselves: reproducing a PoC, assigning CWE and CVSS v3.1 vectors, spotting chained SSRF or IDOR versus a duplicate or out-of-scope report.
Evidence to listen for
Command of the specific attack surface, tooling, and controls the role covers
Understands how the underlying system works, not just how the tool reports on it
Can explain an attack or control chain end to end
Distinguishes what they found themselves from what a scanner flagged
Five-point scoring guide
1
Poor
Tool operator only; no understanding of the systems underneath.
2
Needs Improvement
Runs tooling but cannot explain findings or how the attack works.
3
Satisfactory
Solid working knowledge; depth thins outside familiar tooling.
4
Very Good
Strong command of the domain; explains attack and control chains clearly.
5
Excellent
Reproduces reports independently, defends CVSS vector choices component by component, and distinguishes real chained impact from theoretical severity inflation.
02
Evaluation factor
Real incidents and findings
30% weight
Probe actual program history: platforms run (HackerOne, Bugcrowd, Intigriti, YesWeHack), submission volume, payout budget, median triage time, and one critical report they escalated.
Evidence to listen for
Brings specific incidents, findings, or audits they personally worked
States their own role rather than the team's
Describes what was actually at risk and what changed afterwards
Can talk about a finding that turned out to be wrong
Five-point scoring guide
1
Poor
No hands-on work; knowledge is entirely certification or coursework.
2
Needs Improvement
Limited exposure; cannot describe their contribution to an incident.
3
Satisfactory
Real casework with adequate detail; ownership sometimes vague.
4
Very Good
Specific incidents with clear personal scope and what changed after.
5
Excellent
Cites named programs with report volumes, bounty tables, valid-report percentages, and a specific critical finding they drove from inbox to fix.
03
Evaluation factor
Risk judgement
20% weight
Assess how they set scope, safe harbour terms and reward tiers, and how they handle duplicates, beg bounties, out-of-scope submissions and disclosure timeline disputes.
Evidence to listen for
Prioritises by actual exploitability and business impact, not raw severity scores
Can argue for accepting a risk as well as fixing it
Knows the difference between a finding and a problem
Does not cry wolf or wave things through
Five-point scoring guide
1
Poor
Treats every finding as critical, or waves real risk through.
2
Needs Improvement
Follows severity scores mechanically; no business context.
3
Satisfactory
Reasonable prioritisation; less confident arguing for risk acceptance.
4
Very Good
Prioritises by exploitability and impact; can justify accepting a risk.
5
Excellent
Explains scope and payout decisions with reasoning on signal-to-noise and researcher goodwill, and handles disputed duplicates without inflaming reputation.
04
Evaluation factor
Getting things fixed
15% weight
Look for evidence they moved findings into engineering: Jira tickets filed, remediation SLAs tracked, retests confirmed, and researcher relationships kept warm through slow fixes.
Evidence to listen for
Writes findings engineers can act on rather than a wall of output
Has persuaded a team to fix something they did not want to fix
Explains risk to executives in business terms
Works with the org rather than policing it
Five-point scoring guide
1
Poor
Adversarial with engineering; findings never get fixed.
2
Needs Improvement
Reports are unactionable; no influence beyond raising tickets.
3
Satisfactory
Adequate reporting; relies on mandate rather than persuasion.
4
Very Good
Actionable findings and a real record of getting fixes shipped.
5
Excellent
Shows remediation SLA data, closed-loop retest evidence, and concrete tactics for keeping top researchers engaged when engineering timelines slip.
Evidence-led prompts
Interview questions for a Bug Bounty Program Manager
Use these prompts to surface evidence for the weighted factors above and compare candidates against the same role-specific criteria.
01
Can you describe your experience managing bug bounty programmes?
02
Can you discuss an instance where a programme led to a significant security improvement?
03
Can you discuss your approach to scaling a bug bounty programme?
04
How do you prioritise and triage vulnerabilities reported through a programme?
05
What steps do you take to verify the validity of a reported vulnerability?
