Secure and Govern glossary All tiers All offerings

The glossary of terms aims to achieve the following:

  • Promote a ubiquitous language that can be used everywhere - with customers, on issues, in Slack, in code.
  • Improve the effectiveness of communication between team members.
  • Reduce the potential for miscommunication.
  • Bring new team members and community contributors up to speed faster, reducing the time to productivity.

The definitions of the terms outlined in this document are in the context of the GitLab products. Therefore, a term may have a different meaning to users outside of GitLab.

Analyzer

Software that performs a scan. The scan analyzes an attack surface for vulnerabilities and produces a report containing findings. Reports adhere to the Secure report format.

Analyzers integrate into GitLab using a CI job. The report produced by the analyzer is published as an artifact after the job is complete. GitLab ingests this report, allowing users to visualize and manage found vulnerabilities. For more information, see Security Scanner Integration.

Many GitLab analyzers follow a standard approach using Docker to run a wrapped scanner. For example, the image semgrep is an analyzer that wraps the scanner Semgrep.

Attack surface

The different places in an application that are vulnerable to attack. Secure products discover and search the attack surface during scans. Each product defines the attack surface differently. For example, SAST uses files and line numbers, and DAST uses URLs.

Corpus

The set of meaningful test cases that are generated while the fuzzer is running. Each meaningful test case produces new coverage in the tested program. It’s advised to re-use the corpus and pass it to subsequent runs.

CNA

CVE Numbering Authorities (CNAs) are organizations from around the world that are authorized by the Mitre Corporation to assign CVEs to vulnerabilities in products or services within their respective scope. GitLab is a CNA.

CVE

Common Vulnerabilities and Exposures (CVE®) is a list of common identifiers for publicly known cybersecurity vulnerabilities. The list is managed by the Mitre Corporation.

CVSS

The Common Vulnerability Scoring System (CVSS) is a free and open industry standard for assessing the severity of computer system security vulnerabilities.

CWE

Common Weakness Enumeration (CWE™) is a community-developed list of common software and hardware weakness types that have security ramifications. Weaknesses are flaws, faults, bugs, vulnerabilities, or other errors in software or hardware implementation, code, design, or architecture. If left unaddressed, weaknesses could result in systems, networks, or hardware being vulnerable to attack. The CWE List and associated classification taxonomy serve as a language that you can use to identify and describe these weaknesses in terms of CWEs.

Deduplication

When a category’s process deems findings to be the same, or if they are similar enough that a noise reduction is required, only one finding is kept and the others are eliminated. Read more about the deduplication process.

Duplicate finding

A legitimate finding that is reported multiple times. This can occur when different scanners discover the same finding, or when a single scan inadvertently reports the same finding more than once.

False positive

A finding that doesn’t exist but is incorrectly reported as existing.

Finding

An asset that has the potential to be vulnerable, identified in a project by an analyzer. Assets include but are not restricted to source code, binary packages, containers, dependencies, networks, applications, and infrastructure.

Findings are all potential vulnerability items scanners identify in MRs/feature branches. Only after merging to default does a finding become a vulnerability.

You can interact with vulnerability findings in two ways.

  1. You can open an issue or merge request for the vulnerability finding.
  2. You can dismiss the vulnerability finding. Dismissing the finding hides it from the default views.

Grouping

A flexible and non-destructive way to visually organize vulnerabilities in groups when there are multiple findings that are likely related but do not qualify for deduplication. For example, you can include findings that should be evaluated together, would be fixed by the same action, or come from the same source. Grouping behavior for vulnerabilities is under development and tracked in issue 267588.

Insignificant finding

A legitimate finding that a particular customer doesn’t care about.

Location fingerprint

A finding’s location fingerprint is a text value that’s unique for each location on the attack surface. Each security product defines this according to its type of attack surface. For example, SAST incorporates file path and line number.

Package managers and package types

Package managers

A package manager is a system that manages your project dependencies.

The package manager provides a method to install new dependencies (also referred to as “packages”), manage where packages are stored on your file system, and offer capabilities for you to publish your own packages.

Package types

Each package manager, platform, type, or ecosystem has its own conventions and protocols to identify, locate, and provision software packages.

The following table is a non-exhaustive list of some of the package managers and types referenced in GitLab documentation and software tools.

Package TypePackage Manager
gemBundler
PackagistComposer
ConanConan
gogo
mavenGradle
Maven
sbt
npmnpm
yarn
NuGetNuGet
PyPISetuptools
pip
Pipenv
Poetry

Pipeline Security tab

A page that displays findings discovered in the associated CI pipeline.

Post-filter

Post-filters help reduce noise in the scanner results and automate manual tasks. You can specify criteria that updates or modifies vulnerability data based on scanner results. For example, you can flag findings as likely False Positives and automatically resolve vulnerabilities that are no longer detected. These are not permanent actions and can be changed.

Support for automatically resolving findings is tracked in epic 7478 and support for cheap scan is proposed in issue 349926.

Pre-filter

An irreversible action that is done to filter out targets before analysis occurs. This is usually provided to allow the user to reduce scope and noise as well as speed up the analysis. This should not be done if a record is needed as we currently do not store anything related to the skipped/excluded code or assets.

Examples: DS_EXCLUDED_PATHS should Exclude files and directories from the scan based on the paths provided.

Primary identifier

A finding’s primary identifier is a value that is unique to each finding. The external type and external ID of the finding’s first identifier combine to create the value.

Examples of primary identifiers include PluginID for OWASP Zed Attack Proxy (ZAP), or CVE for Trivy. The identifier must be stable. Subsequent scans must return the same value for the same finding, even if the location has slightly changed.

Report finding

A finding that only exists in a report produced by an analyzer, and is yet to be persisted to the database. The report finding becomes a vulnerability finding once it’s imported into the database.

Scan type (report type)

Describes the type of scan. This must be one of the following:

  • api_fuzzing
  • container_scanning
  • coverage_fuzzing
  • dast
  • dependency_scanning
  • sast
  • secret_detection

This list is subject to change as scanners are added.

Scanner

Software that can scan for vulnerabilities. The resulting scan report is typically not in the Secure report format. Examples include ESLint, Trivy, and ZAP.

Secure product

A group of features related to a specific area of application security with first-class support by GitLab.

Products include Container Scanning, Dependency Scanning, Dynamic Application Security Testing (DAST), Secret Detection, Static Application Security Testing (SAST), and Fuzz Testing.

Each of these products typically include one or more analyzers.

Secure report format

A standard report format that Secure products comply with when creating JSON reports. The format is described by a JSON schema.

Security Dashboard

Provides an overview of all the vulnerabilities for a project, group, or GitLab instance. Vulnerabilities are only created from findings discovered on the project’s default branch.

Seed corpus

The set of test cases given as initial input to the fuzz target. This usually speeds up the fuzz target substantially. This can be either manually created test cases or auto-generated with the fuzz target itself from previous runs.

Vendor

The party maintaining an analyzer. As such, a vendor is responsible for integrating a scanner into GitLab and keeping it compatible as they evolve. A vendor isn’t necessarily the author or maintainer of the scanner, as in the case of using an open core or OSS project as a base solution of an offering. For scanners included as part of a GitLab distribution or GitLab subscription, the vendor is listed as GitLab.

Vulnerability

A flaw that has a negative impact on the security of its environment. Vulnerabilities describe the error or weakness, and don’t describe where the error is located (see finding).

Each vulnerability maps to a unique finding.

Vulnerabilities exist in the default branch. Findings (see finding) are all potential vulnerability items scanners identify in MRs/feature branches. Only after merging to default does a finding become a vulnerability.

Vulnerability finding

When a report finding is stored to the database, it becomes a vulnerability finding.

Vulnerability tracking

Deals with the responsibility of matching findings across scans so that a finding’s life cycle can be understood. Engineers and security teams use this information to decide whether to merge code changes, and to see unresolved findings and when they were introduced.

Vulnerabilities are tracked by comparing the location fingerprint, primary identifier, and report type.

Vulnerability occurrence

Deprecated, see finding.