KPI Tree

GitHub Metric

Engineering

Security Vulnerability Trends tracks the number, severity, and type of security vulnerabilities discovered across repositories over time. It encompasses Dependabot alerts, code scanning findings, and secret scanning detections. Improving trends indicate maturing security practices and proactive dependency management.

GitHubEngineering

Security Vulnerability Trends

Security Vulnerability Trends tracks the number, severity, and type of security vulnerabilities discovered across repositories over time. It encompasses Dependabot alerts, code scanning findings, and secret scanning detections. Improving trends indicate maturing security practices and proactive dependency management.

Why security vulnerability trends matters for GitHub users

A single snapshot of open vulnerabilities is less informative than the trend. Are new vulnerabilities being introduced faster than they are resolved? Is the severity mix shifting towards more critical findings? These trends reveal whether security investments are working.

For GitHub teams, correlating vulnerability trends with dependency update frequency and security alert resolution time creates a complete security posture picture. It also enables evidence-based decisions about when to prioritise security sprints.

Understand and act on security vulnerability trends with KPI Tree

Aggregate security alert data from GitHub into your warehouse and visualise trends by severity and type in KPI Tree. Link vulnerability trends to security alert resolution time and repository health in your metric tree.

Assign RACI ownership to the security or platform team and configure trend-based alerts when the open-vulnerability count increases over a rolling period.

Get started with your GitHub data

Query using MCP
MCP

Pull metrics from GitHub directly through the Model Context Protocol.

Data Warehouse
SnowflakeBigQueryDatabricksRedshift

Connect your existing warehouse where GitHub data already lands.

Professional Services
FivetranSnowflakedbt

Our professional services team can build you turn-key AI foundations in a matter of weeks. Data warehouse on Snowflake/BigQuery, ELT with Fivetran, all modelled in dbt with a semantic layer.

Related GitHub metrics

Security Alert Resolution Time

Engineering

Metric Definition

Resolution Time = Alert Resolved Timestamp − Alert Created Timestamp

Security Alert Resolution Time measures the elapsed time from when a security alert (Dependabot, code scanning, or secret scanning) is opened to when it is resolved or dismissed in GitHub. It quantifies the organisation's responsiveness to known vulnerabilities and the effectiveness of its security remediation process.

View metric

Repository Health Score

Engineering

Metric Definition

Repository Health Score is a composite metric that evaluates key health indicators for a GitHub repository, including documentation completeness, test coverage, CI configuration, dependency freshness, branch protection rules, and recent maintenance activity. It provides a single number for comparing repository maturity across an organisation.

View metric

Technical Debt Accumulation

Engineering

Metric Definition

Technical Debt Accumulation measures the rate at which technical debt grows across a codebase, using proxies such as TODO/FIXME comment count, aged open issues labelled as tech-debt, increasing cyclomatic complexity, and dependency staleness. Rising accumulation signals that short-term trade-offs are compounding into long-term burden.

View metric

Code Quality Trend Analysis

Engineering

Metric Definition

Code Quality Trend Analysis aggregates signals such as linting violations, cyclomatic complexity, code duplication, and static-analysis findings over time. It provides a longitudinal view of code health across repositories. Consistent improvement indicates maturing engineering practices.

View metric

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