Every security team faces the same frustrating question: "Are these two vulnerabilities actually the same issue?" At SQUR, we've seen how getting this wrong wastes remediation effort, inflates risk metrics, and frustrates researchers. Through our autonomous pentesting work, we've developed a systematic approach to eliminate this confusion.
The Real Cost of Duplicate Confusion
When security teams can't clearly identify duplicates, the consequences ripple throughout the organization:
- Wasted development cycles fixing the same root cause multiple times
- Inflated vulnerability counts that misrepresent actual risk to executives
- Researcher frustration from legitimate findings marked as duplicates
- Budget inefficiencies from duplicate bounty payments
- Poor prioritization when teams lose track of the real security landscape
Traditional approaches to duplicate identification often rely on subjective judgment calls, leading to inconsistent decisions and team friction. That's why we built our framework—to bring objectivity and consistency to these critical decisions.
How Industry Leaders Handle Duplicates
Current Industry Standards
Major bug bounty platforms have established working definitions, but they vary in precision:
HackerOne's Approach
HackerOne considers vulnerabilities duplicates when they share the same root cause and can be fixed with a single remediation action. They emphasize that similar vulnerability types in different components are typically not duplicates.
Bugcrowd's Framework
Bugcrowd's "Three Principles" focus on:
- Root cause analysis beyond surface-level classification
- Location and context matter—same vulnerability class doesn't equal same vulnerability
- Fix-based assessment—if fixing one doesn't eliminate another, they're not duplicates
Synack's Method
Synack treats multiple vulnerabilities from the same underlying issue as one valid report, using a first-come, first-served basis for duplicate submissions.
Where Current Approaches Fall Short
While these frameworks provide good starting points, they often lack:
- Precise technical criteria for edge cases
- Clear component boundary definitions
- Systematic decision procedures
- Concrete examples for complex scenarios
The SQUR Framework for Duplicate Definition
At SQUR, we've developed a comprehensive framework through our autonomous pentesting experience that eliminates ambiguity in duplicate identification:
SQUR's Core Definition
At SQUR, we consider two findings duplicates if and only if a single, concrete remediation change, applied once within the same component boundary, simultaneously eliminates both vulnerabilities under identical preconditions.
The Four Pillars of Duplication
1. Same Root Cause
- Identical defect mechanism: Both exploit the same underlying flaw
- Same vulnerable code path: Both trace to the same function, query, or configuration
- Matching attack surface: Both leverage the same entry point
2. One Remediation Unit
- Single change requirement: Only one edit to one file/function/config needed
- Simultaneous resolution: The single change eliminates both vulnerabilities
- No secondary fixes: If two distinct edits are required, they're not duplicates
3. Identical Context
- Same service/application: Both affect the same deployed system
- Same logical component: Both impact the same handler or business logic unit
- Same authorization context: Both occur under identical permissions
4. Same Affected Component
- Same deployment unit: Both exist within the same microservice
- Same logical boundary: Both affect the same controller or policy enforcement point
- Same architectural layer: Both exist at the same application stack level
Practical Decision Procedure
When evaluating potential duplicates, follow this systematic approach:
Step 1: Extract Core Elements
For each finding, identify:
- Root cause classification and technical details
- Affected code location or configuration object
- Component boundary and architectural context
- Environmental and authorization requirements
Step 2: Propose Single Remediation
Ask these critical questions:
- What single file, function, or configuration needs modification?
- Can this single change eliminate both vulnerabilities completely?
- Are any secondary changes required?
Step 3: Validate Context Alignment
Confirm that both findings:
- Exist in the same service/deployment
- Share identical authorization boundaries
- Operate under the same environmental conditions
Step 4: Apply Evidence Test
For uncertain cases, require concrete evidence:
- Direct link between both findings and the same vulnerable code
- Proof of identical handler or configuration involvement
- Verification of matching context through system analysis
Real-World Examples
Clear Duplicates
Scenario: Three SQL injection vulnerabilities in /api/users, /api/profile, and /api/settings that all trace to the same database query function in utils/db.js:42
Decision: Duplicates—fixing the parameterized query in utils/db.js eliminates all three
NOT Duplicates
Scenario: Two XSS vulnerabilities, one in the main application's comment system and another in the admin panel's user management interface
Decision: Not duplicates—require separate fixes in different components with different authorization contexts
How Our Framework Powers Autonomous Pentesting
This framework is integral to how SQUR's autonomous penetration testing platform operates:
- Accurate reporting: AI agents can systematically group related findings without over-consolidation
- Efficient remediation: Development teams receive precise guidance on fix locations and scope
- Better risk assessment: Security metrics reflect actual, unique vulnerabilities rather than inflated counts
- Faster cycles: Reduced time spent on duplicate triage allows focus on new vulnerability discovery
How Security Teams Can Apply Our Approach
Learning from SQUR's Methodology
- Consider the four-pillar framework for duplicate assessments
- Document decision criteria in vulnerability management processes
- Train team members on the systematic decision procedure
- Create assessment templates to ensure consistent evaluation
- Establish appeal processes for disputed duplicate decisions
Tool Integration
- Implement decision criteria in vulnerability management systems
- Build automated checks for obvious duplication patterns
- Create audit trails for all duplication decisions
- Establish human review processes for complex edge cases
Measuring Success
Track these key metrics to validate your duplicate identification process:
- Accuracy rate: Percentage of correctly classified duplicates
- Appeal success rate: How often duplicate decisions get overturned
- Time to determination: Speed of duplicate assessment
- Remediation efficiency: Development time saved through proper grouping
- Team satisfaction: Researcher and developer feedback on duplicate decisions
Future-Proofing Your Approach
As technology evolves, duplicate definitions must adapt to new challenges:
- Microservices architectures: Ensuring component boundaries remain clear across distributed systems
- Cloud-native applications: Handling infrastructure-as-code and container-based duplicates
- AI/ML systems: Applying duplicate logic to algorithmic vulnerabilities
- DevSecOps integration: Automated duplicate detection in CI/CD pipelines
Conclusion: How SQUR Ensures Clarity
Precise duplicate vulnerability definition isn't academic—it's essential for effective security programs. The SQUR framework we've shared here enables consistent decision-making, efficient remediation, and fair treatment of security findings.
Through our systematic approach to duplicate identification, SQUR helps organizations optimize security investments, improve researcher relationships, and maintain accurate risk assessments. Whether you're managing bug bounty programs, internal security teams, or external partnerships, our clear duplicate methodology ensures everyone focuses on what matters: fixing unique vulnerabilities that genuinely improve security posture.
SQUR's autonomous pentesting platform incorporates these principles, providing validated findings with minimal duplicates and comprehensive remediation guidance. Our approach combines technical precision with systematic processes to deliver the clarity security teams need.
Interested in seeing how SQUR's autonomous pentesting eliminates duplicate confusion while discovering real vulnerabilities? Learn more about our approach.