We Slashed Duplicate Report Investigation Time by Up to 85%

Every successful bug bounty program eventually faces the same challenge - duplicate reports.

The problem is that duplicate reports rarely look like duplicates. Two researchers can discover the exact same vulnerability but describe it using completely different titles, terminology, proof-of-concepts, and reproduction steps. Traditional searches based on keywords or report titles often miss these connections, forcing analysts to manually dig through historical submissions.

The Hidden Cost of Duplicate Hunting

When a potentially duplicate report arrives, analysts typically search previous submissions, compare affected assets, review reproduction steps, and validate whether the underlying issue has already been reported.

For mature bug bounty programs, this manual process can easily take 15-25 minutes per report whenever duplicate risk is high. As submission volumes grow, this becomes one of the biggest contributors to triage time, consuming valuable analyst bandwidth that could be spent validating new vulnerabilities.

A Better Way

We built Similar Reports to make duplicate discovery significantly faster.

One of the biggest lessons during development was that duplicate detection isn't a search problem-it's a context problem. Two reports may share very few keywords yet describe the exact same root cause, while reports with similar titles can represent entirely different security issues.

Instead of relying solely on keyword matching, Similar Reports uses semantic AI to understand the context of a vulnerability report and compare it with historical submissions. Rather than searching for matching words, it searches for matching meaning, helping analysts discover related reports even when the language, structure, or proof-of-concept is completely different.

The feature integrates directly into the existing triage workflow, surfacing the most relevant historical reports within seconds without changing how analysts work.

Built to Assist, Not Replace

One design principle was clear from the beginning: AI should assist analysts, not replace them.

Similar Reports never automatically marks a report as a duplicate. Instead, it provides ranked recommendations and similarity scores, allowing security teams to make the final decision based on technical context, affected assets, and their own expertise.

Security triage still requires human judgment. AI simply removes the repetitive effort of searching through historical reports so analysts can focus on validating vulnerabilities instead of finding them.

The Impact

The improvement has been substantial.

Instead of spending 15-25 minutes searching and comparing historical reports, analysts typically review the suggested matches in 2-5 minutes.

This has resulted in:

• 75-85% reduction in duplicate discovery effort

• 20-25% faster triage for reports requiring duplicate verification

• 10-15% increase in overall analyst capacity across active programs

• Up to 40% faster investigations on high-volume assets where similar findings are frequently reported

While every program is different, reducing repetitive investigation allows analysts to spend significantly more time assessing the quality and impact of new vulnerabilities.

Looking Ahead

Duplicate detection is only the beginning.

Semantic understanding creates opportunities far beyond identifying similar reports. The same foundation can help security teams recognize recurring vulnerability patterns, improve report prioritization, surface related findings faster, and build a stronger knowledge base from historical submissions.