Chapter 3. Clair security scanner
Clair v4 (Clair) is an open source application that leverages static code analyses for parsing image content and reporting vulnerabilities affecting the content. Clair is packaged with Quay.io, is automatically enabled, and is managed by the Red Hat Quay development team.
For Quay.io users, images are automatically indexed after they are pushed to your repository. Reports are then fetched from Clair, which matches images against its CVE’s database to report security information. This process happens automatically on Quay.io, and manual recans are not required.
3.1. About Clair
Clair uses Common Vulnerability Scoring System (CVSS) data from the National Vulnerability Database (NVD) to enrich vulnerability data, which is a United States government repository of security-related information, including known vulnerabilities and security issues in various software components and systems. Using scores from the NVD provides Clair the following benefits:
- Data synchronization. Clair can periodically synchronize its vulnerability database with the NVD. This ensures that it has the latest vulnerability data.
- Matching and enrichment. Clair compares the metadata and identifiers of vulnerabilities it discovers in container images with the data from the NVD. This process involves matching the unique identifiers, such as Common Vulnerabilities and Exposures (CVE) IDs, to the entries in the NVD. When a match is found, Clair can enrich its vulnerability information with additional details from NVD, such as severity scores, descriptions, and references.
- Severity Scores. The NVD assigns severity scores to vulnerabilities, such as the Common Vulnerability Scoring System (CVSS) score, to indicate the potential impact and risk associated with each vulnerability. By incorporating NVD’s severity scores, Clair can provide more context on the seriousness of the vulnerabilities it detects.
If Clair finds vulnerabilities from NVD, a detailed and standardized assessment of the severity and potential impact of vulnerabilities detected within container images is reported to users on the UI. CVSS enrichment data provides Clair the following benefits:
- Vulnerability prioritization. By utilizing CVSS scores, users can prioritize vulnerabilities based on their severity, helping them address the most critical issues first.
- Assess Risk. CVSS scores can help Clair users understand the potential risk a vulnerability poses to their containerized applications.
- Communicate Severity. CVSS scores provide Clair users a standardized way to communicate the severity of vulnerabilities across teams and organizations.
- Inform Remediation Strategies. CVSS enrichment data can guide Quay.io users in developing appropriate remediation strategies.
- Compliance and Reporting. Integrating CVSS data into reports generated by Clair can help organizations demonstrate their commitment to addressing security vulnerabilities and complying with industry standards and regulations.
3.1.1. Clair vulnerability databases
Clair uses the following vulnerability databases to report for issues in your images:
- Ubuntu Oval database
- Debian Security Tracker
- Red Hat Enterprise Linux (RHEL) Oval database
- SUSE Oval database
- Oracle Oval database
- Alpine SecDB database
- VMware Photon OS database
- Amazon Web Services (AWS) UpdateInfo
- Open Source Vulnerability (OSV) Database
3.1.2. Clair supported dependencies
Clair supports identifying and managing the following dependencies:
- Java
- Golang
- Python
- Ruby
This means that it can analyze and report on the third-party libraries and packages that a project in these languages relies on to work correctly.
When an image that contains packages from a language unsupported by Clair is pushed to your repository, a vulnerability scan cannot be performed on those packages. Users do not receive an analysis or security report for unsupported dependencies or packages. As a result, the following consequences should be considered:
- Security risks. Dependencies or packages that are not scanned for vulnerability might pose security risks to your organization.
Compliance issues. If your organization has specific security or compliance requirements, unscanned, or partially scanned, container images might result in non-compliance with certain regulations.
NoteScanned images are indexed, and a vulnerability report is created, but it might omit data from certain unsupported languages. For example, if your container image contains a Lua application, feedback from Clair is not provided because Clair does not detect it. It can detect other languages used in the container image, and shows detected CVEs for those languages. As a result, Clair images are fully scanned based on what it supported by Clair.
3.2. Clair severity mapping
Clair offers a comprehensive approach to vulnerability assessment and management. One of its essential features is the normalization of security databases' severity strings. This process streamlines the assessment of vulnerability severities by mapping them to a predefined set of values. Through this mapping, clients can efficiently react to vulnerability severities without the need to decipher the intricacies of each security database’s unique severity strings. These mapped severity strings align with those found within the respective security databases, ensuring consistency and accuracy in vulnerability assessment.
3.2.1. Clair severity strings
Clair alerts users with the following severity strings:
- Unknown
- Negligible
- Low
- Medium
- High
- Critical
These severity strings are similar to the strings found within the relevant security database.
Alpine mapping
Alpine SecDB database does not provide severity information. All vulnerability severities will be Unknown.
| Alpine Severity | Clair Severity |
|---|---|
| * | Unknown |
AWS mapping
AWS UpdateInfo database provides severity information.
| AWS Severity | Clair Severity |
|---|---|
| low | Low |
| medium | Medium |
| important | High |
| critical | Critical |
Debian mapping
Debian Oval database provides severity information.
| Debian Severity | Clair Severity |
|---|---|
| * | Unknown |
| Unimportant | Low |
| Low | Medium |
| Medium | High |
| High | Critical |
Oracle mapping
Oracle Oval database provides severity information.
| Oracle Severity | Clair Severity |
|---|---|
| N/A | Unknown |
| LOW | Low |
| MODERATE | Medium |
| IMPORTANT | High |
| CRITICAL | Critical |
RHEL mapping
RHEL Oval database provides severity information.
| RHEL Severity | Clair Severity |
|---|---|
| None | Unknown |
| Low | Low |
| Moderate | Medium |
| Important | High |
| Critical | Critical |
SUSE mapping
SUSE Oval database provides severity information.
| Severity | Clair Severity |
|---|---|
| None | Unknown |
| Low | Low |
| Moderate | Medium |
| Important | High |
| Critical | Critical |
Ubuntu mapping
Ubuntu Oval database provides severity information.
| Severity | Clair Severity |
|---|---|
| Untriaged | Unknown |
| Negligible | Negligible |
| Low | Low |
| Medium | Medium |
| High | High |
| Critical | Critical |
OSV mapping
| Base Score | Clair Severity |
|---|---|
| 0.0 | Negligible |
| 0.1-3.9 | Low |
| 4.0-6.9 | Medium |
| 7.0-8.9 | High |
| 9.0-10.0 | Critical |
| Base Score | Clair Severity |
|---|---|
| 0.0-3.9 | Low |
| 4.0-6.9 | Medium |
| 7.0-10 | High |
