Analyze trends and performance

The GitGuardian Analytics feature enables you to closely monitor the evolution of your security posture and quickly identify potential threats. In just a few clicks, you can, for instance:

• Monitor the progression of new incidents.
• Determine the total count of open incidents.
• Understand how your incidents are categorized by severity and validity.

The Analytics page is divided into two sections: Insights and Charts. Insights provides high-level metrics, while Charts offer a detailed view of incident trends based on various parameters.

Analytics Insights

The "How GitGuardian protects you" panel of your Analytics section illustrates how GitGuardian has been able to help your team with secrets detection, whether through the dashboard or a shift-left approach.

The default time range is Last month. You can change the time range in the top right-hand corner of the page. For stat metrics, GitGuardian compares the metric with the previous period (computed to have the same number of days).

Dashboard protection

Secrets detectors: total number of secrets detectors used from the GitGuardian secrets detection engine. You can even see how many new secrets detectors were added by our dedicated R&D team during the selected time period. The entire list is accessible in your settings or in the secrets detection section of our documentation.

Historical protection

All time historical scans: total number of historical scans performed by GitGuardian. You can also see how many historical scans were triggered during the period.

All time percentage of historical scans detecting secrets: "all time" percentage of historical scans that uncovered a secret incident. This metric counts incidents that are already open or brand new (already resolved or ignored secret incidents are no longer taken into account during the historical scan). You can even see this same percentage but only for historical scans performed during the selected time period.

Real-time protection

Commits scanned: number of commits scanned on server side (post-receive hook stage) through your native VCS integrations (GitHub, GitLab, Bitbucket).

Evolution of commits scanned over time: distribution of commits scanned on server side (post-receive hook stage) through your native VCS integrations over time. It shows your developers' activity monitored by GitGuardian.

Secret occurrences detected per 1000 commits: ratio of secret occurrences found per commits analyzed. Note that a commit can contains more than 1 secret occurrence.

Shift left protection

GitGuardian CLI (Command Line Interface) application ggshield allows you to deploy GitGuardian's secret detection engine in a shift-left approach.

ggshield scans: number of ggshield scans through git hooks or CI/CD integrations.

Secret detected by ggshield scan: number of secrets detected with ggshield scans. If the secret was detected with a ggshield scan at git hooks level (pre-commit, pre-push, pre-receive), it is a secret prevented from reaching the VCS and therefore, one less incident!

Evolution of ggshield scans over time: distribution of ggshield scans over time per ggshield mode (CI/CD integrations, git hooks). For each mode, you will find the number of ggshield scans over the period and the percentage of those scans that detected secrets.

Analytics Charts

Introduction

Analytics Charts is a powerful feature designed to help you visualize and get insights on your incidents over time. Whether you are a developer, security lead, or manager, Analytics Charts provides valuable tools to track progress, measure performance, and make informed decisions. With Analytics Charts, you can turn your data into actionable insights and drive your team's success.

Let's dive in and explore how to get started.

Getting Started

Steps to get started

1. Access the Analytics Charts

2. Review pre-built charts: Get a quick overview of your incidents data with our pre-built charts.

• "Real time" chart: select it from the top menu.

• Modify the chart by adding a new filter. Select the "Secret Validity" filter and choose the option "Valid".

• You have just modified your first chart! The chart is now filtered by incidents detected in real time and valid. You can add as many filters as you like.

Using pre-built charts

Find a variety of pre-built charts to provide you with quick insights into your data. These charts are designed to highlight key metrics.

Available pre-built charts:

1. Critical: Track the rate of new incidents over time, broken down by high and critical severity.
2. Real time: All secret incidents detected in real time.
3. New incidents: Track the daily count of new incidents.
4. Open incidents: Track the distribution of open incidents.
5. Public exposure: Track the number of secret exposed in public codebases to identify high risks.
6. Severity distribution: Tracking the distribution of secret severity.
7. Severity validity: Assess the overall validity of secrets.

Accessing pre-built charts:

1. Navigate to the Analytics Charts page: Access all charts available from the "+" button.
2. Explore charts details: Change the time frame (daily, weekly, monthly).
3. Customize the chart: Add or remove filters following your needs.
4. Export the data: Export the data in CSV format.
5. Duplicate, hide or delete a chart: Decide to duplicate, hide or delete a chart.

Note: Updating a pre-built GitGuardian chart is not possible. It is necessary to create a new chart or duplicate the existing one before saving it as a new chart.

Understanding your data

By understanding the types of data available and how to leverage it, you can gain valuable insights into your team's performance and security posture.

Data sources

Currently, Analytics Charts supports the following data sources:

• Stock: Open secret incidents over time
• Flow: Newly detected secrets over time

Filtering and "group by" options

You can filter or group by charts data by:

• Time
• Team
• Detector type
• Publicly leaked/exposed
• Real-time
• Secret validity
• Severity
• Detector type
• Publicly leaked/exposed
• Real-time
• Secret Validity

Data visualization

There are various visualization options such as line charts, bar charts, area charts to help you understand data trends and patterns. You can change the way you display your data when creating or updating a chart.

Charts visibility

Charts can be accessible to all workspace members or kept private and visible only to the creator. Additionally, if a member is part of a specific team, he can only visualize data related to his team.

This visibility option is accessible from the side panel when you are creating or updating a chart.

Charts options

• Charts can be duplicated.
• Charts data can be exported in CSV format.
• Charts can be deleted.

How to create your custom chart

Analytics empowers you to create custom visualizations that perfectly suit your needs. You can easily build charts that highlight the most important aspects of your data.

Steps to create a custom chart

Firstly, click on the "+" button next to the list of pre-built charts. This will open a side panel allowing you to create a new chart and select options.

1. Add a title and a description: Provide a clear and concise title and description for your chart.
2. Select the data source: Choose the data sources you want to include in your chart.
3. Select the way to display data: Choose how you want your data to be displayed, such as a line chart, bar chart and so on.
4. Group by option: Group your data by a specific category or dimension (for instance: detector type).
5. Filters options: Apply filters to your data to focus on specific time periods.
6. Visibility options: Determine whether the chart should be accessible to all workspace members or kept private.
7. Save your new chart: Save your custom chart for future use and easily share it with colleagues and stakeholders.

By following these steps and taking advantage of the customization options, creating custom charts is easy and a powerful tool for communicating your data effectively.