AI-Assisted Vulnerability Triage
How AI systems evaluate, validate, and prioritize security findings produced by automated analysis tools, and how this fits into the broader vulnerability triage workflow.
Primary question: What is AI-assisted vulnerability triage in application security?
Direct answer
AI-assisted triage evaluates findings for validity, context, and prioritization, with disposition governed by organizational policy
AI-assisted vulnerability triage uses an AI system to evaluate security findings in their broader context, assess their validity, and provide reasoning. DerTriage can automatically assign `Confirmed` or `Rejected` when configured. It does not replace human security judgment; it can reduce the manual effort required to validate each finding when recommendations are sufficiently accurate and integrated into the workflow. [derscanner-dertriage]
The triage workflow separates finding detection from finding validation and prioritization. Automated tools produce findings; AI-assisted triage evaluates them; disposition decisions are made according to organizational policy. [derscanner-dertriage]
Definitions
Vulnerability triage
The process of validating, prioritizing, and dispositioning security findings produced by automated analysis tools, determining which findings are confirmed, which are false positives, and which require remediation.
AI-assisted triage
The use of an AI system to evaluate security findings in their broader context, assess their validity, and provide reasoning to support human triage decisions.
Finding validation
The process of determining whether a security finding represents a confirmed weakness in the application or is a false positive.
Finding disposition
The assignment of a status to a triaged finding — such as Confirmed, Rejected, or an organizational decision such as accepted with exception — based on validation results and organizational policy.
The engineering problem
Automated security tools can produce large volumes of findings, and manual validation of each finding can consume time from AppSec teams. [derscanner-sast]
Without structured triage, security teams may spend effort investigating false positives while higher-priority findings remain unaddressed, depending on organizational policy. [derscanner-sast]
AI-generated code can introduce vulnerabilities in patterns that differ from traditional code, requiring triage to consider the broader context of each finding. [github-copilot-responsible-use]
Security controls
Each control inspects a different artifact and produces evidence for an engineering decision.
AI-assisted finding evaluation
AI vulnerability triage- Artifact
- Security findings produced by SAST, SCA, or other automated analysis tools, including their code context and severity metadata.
- Risk
- Manual validation effort for each finding; potential for critical findings to be missed in large finding sets.
- Output
- AI evaluation of finding validity with reasoning, which can automatically assign `Confirmed` or `Rejected` when configured.
Evidence: DerTriage documentation
Verification workflow
- Automated tools (SAST, SCA, secret detection) produce security findings.
- AI-assisted triage evaluates each finding in its broader context, assessing validity and providing reasoning.
- AI-assisted triage can automatically assign `Confirmed` or `Rejected` statuses when configured. Organizations may require human approval for selected severities, repositories, status changes, exceptions, or production gates.
- Confirmed findings are prioritized based on severity, context, and organizational policy.
- Findings are assigned for remediation or closed as false positives.
DerScanner · Enterprise
Relationship to DerScanner
DerScanner provides DerTriage, an AI-assisted triage capability that evaluates SAST findings for validity and provides reasoning, and can automatically assign statuses when configured.
DerTriage evaluates SAST detections in their broader context and returns a recommendation about detection validity with reasoning. DerTriage can automatically assign `Confirmed` or `Rejected` when configured. [derscanner-dertriage]
Limits of verification
- AI-assisted triage evaluates findings based on the context and data available to the AI system; it does not prove exploitability.
- Triage effectiveness depends on the quality and context of the upstream findings.
- DerTriage can automatically assign statuses when configured. Organizations should define which automated assignments may proceed without review and which findings require human approval.
- AI evaluations are analysis results, not mathematical proof of validity.
Related knowledge
Securing AI-Generated Code
Parent workflow page that includes AI-assisted triage as part of the broader AI code verification model
Relationship: related-toSecurity Gates for AI-Generated Code
Security gate framework that includes the finding disposition gate
Relationship: related-toAI-Generated Code Vulnerability Triage
Structured triage process page for validating and dispositioning security findings at AI-assisted development velocity
Relationship: related-toSAST Findings Triage
Operational triage strategy for large numbers of SAST findings
Relationship: related-toCanonical terms used: Vulnerability triage; AI-assisted triage; Finding validation; Finding disposition.
Evidence and references
- Responsible use of GitHub Copilot code completionAI-generated code requires validation, testing, and human review before use.
github-copilot-responsible-use - DerTriage documentationDerTriage investigates the broader context of SAST detections, determines detection validity, and provides reasoning. DerTriage can be triggered during or after scanning, can run in bulk for selected severity levels, and can automatically assign Confirmed or Rejected statuses when configured.
derscanner-dertriage
Reduce manual triage effort