Image Scanning Tools (Anchore, Clair)

Image Scanning Tools: Anchore vs. Clair - A Comprehensive Comparison

Containerization has revolutionized software development and deployment, offering portability, scalability, and resource efficiency. However, this revolution has also introduced new security challenges. Container images, often assembled from various layers and external dependencies, can harbor vulnerabilities, misconfigurations, and outdated software, creating potential entry points for malicious actors. Image scanning tools are crucial for mitigating these risks by analyzing container images for potential security flaws before they are deployed into production. This article delves into two popular open-source image scanning tools: Anchore and Clair, comparing their features, advantages, disadvantages, and implementation.

1. Introduction

Image scanning tools perform static analysis of container images to identify vulnerabilities and policy violations. They examine the image's layers, software packages, configurations, and file system to detect:

• Vulnerabilities: Known vulnerabilities in software packages identified through vulnerability databases like the National Vulnerability Database (NVD).
• Misconfigurations: Non-compliant configurations that deviate from security best practices, such as insecure passwords or exposed ports.
• Malware: Malicious software that may be embedded within the image.
• Secrets: Unintentionally included sensitive information like API keys or passwords.
• License Compliance: Violations of software license agreements.

By identifying and addressing these issues early in the development lifecycle, organizations can significantly reduce the risk of security breaches and maintain a secure container environment. Anchore and Clair are both powerful tools designed to perform these tasks, but they differ in their architecture, features, and usage.

2. Anchore

Anchore is an open-source platform that offers a comprehensive solution for analyzing, validating, and securing container images. It goes beyond basic vulnerability scanning and provides policy-based governance, allowing organizations to define and enforce security policies for their container deployments.

2.1 Prerequisites

Before installing and using Anchore, you'll need to ensure the following prerequisites are met:

• Docker: Docker must be installed and running on the host machine.
• Docker Compose (Recommended): Docker Compose simplifies the deployment and management of Anchore's multiple components.
• Python (for Anchore CLI): Python 3.6 or later is required to install and use the Anchore CLI.
• Storage (Persistent Volume): Anchore requires persistent storage for its database and configuration data.

2.2 Installation

The simplest way to install Anchore is using Docker Compose:

1. Download docker-compose.yaml:
   

   curl -O https://raw.githubusercontent.com/anchore/anchore-engine/stable/docker-compose.yaml
   

2. Start Anchore Engine:
   

   docker-compose up -d
   

3. Install Anchore CLI:
   

   pip install anchorecli
   

4. Configure Anchore CLI (set environment variables):
   

   export ANCHORE_CLI_URL=http://localhost:8228
   export ANCHORE_CLI_USER=admin
   export ANCHORE_CLI_PASS=foobar
   

2.3 Key Features

• Vulnerability Scanning: Identifies known vulnerabilities in software packages using multiple vulnerability databases.
• Policy-Based Governance: Allows defining custom policies to enforce security requirements. Policies can be based on vulnerability severity, package versions, configuration settings, and other criteria.
• Whitelisting/Blacklisting: Enables defining whitelists and blacklists for specific packages or vulnerabilities to reduce false positives or enforce specific requirements.
• Image Analysis: Provides detailed insights into the contents of container images, including installed packages, configuration files, and exposed ports.
• Integration: Integrates with CI/CD pipelines, registries (Docker Hub, ECR, GCR), and other security tools.
• Reporting: Generates detailed reports on image analysis results, including vulnerability findings and policy violations.

2.4 Advantages

• Comprehensive Policy Engine: Anchore's policy engine allows for highly customizable and granular security controls.
• Detailed Image Analysis: Provides extensive information about the image's contents, aiding in vulnerability remediation and compliance efforts.
• Strong Integration Capabilities: Integrates seamlessly with various development and deployment tools.
• Active Community Support: Benefit from an active open-source community.

2.5 Disadvantages

• Complexity: Setting up and configuring Anchore can be complex, especially for beginners.
• Resource Intensive: Anchore can be resource-intensive, especially when analyzing large images or a large number of images concurrently.
• Initial Setup and Configuration: Requires significant initial setup and configuration, including setting up a database and configuring policies.

3. Clair

Clair is an open-source vulnerability static analysis project for containers. Developed by CoreOS (now Red Hat), it focuses primarily on identifying vulnerabilities in container images based on data from vulnerability databases. It's designed to be a lightweight and scalable solution for vulnerability scanning.

3.1 Prerequisites

• Docker: Docker must be installed and running.
• Docker Compose (Recommended): Simplifies deployment.
• PostgreSQL Database: Clair relies on a PostgreSQL database to store vulnerability information and image metadata.

3.2 Installation

Clair can also be installed using Docker Compose:

1. Create a docker-compose.yml file (example):
   

   version: "3.7"
   services:
     postgres:
       image: postgres:12
       restart: unless-stopped
       environment:
         POSTGRES_USER: clair
         POSTGRES_PASSWORD: password
         POSTGRES_DB: clair
       volumes:
         - postgres_data:/var/lib/postgresql/data
   
     clair:
       image: quay.io/quay/clair:v4.7.3
       restart: unless-stopped
       depends_on:
         - postgres
       ports:
         - "6060:6060"
         - "6061:6061"
       environment:
         CLAIR_CONF: |
           version: v1
           loglevel: info
           metrics:
             enabled: true
           api:
             addr: :6060
           updater:
             interval: 30m
             disable_redirects: false
           database:
             type: pgsql
             source: host=postgres port=5432 user=clair password=password dbname=clair sslmode=disable
       volumes:
         - clair_config:/etc/clair
   volumes:
     postgres_data:
     clair_config:
   

2. Start Clair:
   

   docker-compose up -d
   

3.3 Key Features

• Vulnerability Scanning: Identifies known vulnerabilities in container images based on multiple vulnerability databases (NVD, Debian Security Tracker, etc.).
• API-Driven Architecture: Provides a RESTful API for interacting with the scanner, enabling integration with other tools and systems.
• Database Updates: Regularly updates the vulnerability database to ensure the scanner has the latest information.
• Image Layer Analysis: Analyzes each layer of the container image to identify the origin of vulnerabilities.
• Scalability: Designed to be scalable and handle a large number of images concurrently.

3.4 Advantages

• Lightweight and Fast: Clair is designed to be lightweight and efficient, providing fast vulnerability scanning.
• Simple API: The API-driven architecture allows for easy integration with other tools and systems.
• Scalable Architecture: Scalable to handle a large number of container images.
• Focused on Vulnerability Scanning: Focused solely on vulnerability scanning which results in a leaner and more performant solution.

3.5 Disadvantages

• Limited Policy Enforcement: Clair lacks the advanced policy enforcement capabilities of Anchore. It primarily focuses on vulnerability scanning and doesn't offer built-in mechanisms for enforcing custom security policies.
• Less Detailed Analysis: Provides less detailed image analysis compared to Anchore. It primarily focuses on vulnerabilities and doesn't offer as much information about the image's contents and configuration.
• Requires External Tools for Orchestration: Requires external tools and scripts to orchestrate the scanning process.

4. Comparison Table

Feature	Anchore	Clair
Core Functionality	Policy-driven container image analysis	Vulnerability Scanning
Policy Engine	Highly customizable and granular	Limited
Image Analysis	Detailed analysis of image contents	Primarily vulnerability-focused
Architecture	Multi-component, Engine-based	API-driven
Scalability	Scalable, but can be resource-intensive	Designed for scalability and performance
Complexity	More complex to set up and configure	Simpler to set up and use
Integration	Extensive integration capabilities	Requires custom scripts for orchestration
Reporting	Detailed reporting on vulnerabilities and policy violations	Basic vulnerability reporting
Ease of Use	Steeper learning curve	Easier to use, especially for basic scans

5. Code Snippets (Examples)

5.1 Anchore CLI Example (Scanning an image and checking policy):

anchore-cli image add docker.io/library/alpine:latest
anchore-cli image wait docker.io/library/alpine:latest  # Wait for analysis to complete
anchore-cli image vuln docker.io/library/alpine:latest os
anchore-cli image check docker.io/library/alpine:latest

5.2 Using Clair API (Example - Simplified):

To use the Clair API, you would typically need to interact with it through HTTP requests. The following illustrates a general overview (specific details would depend on the Clair version and client library):

1. Create a Layer Resource: Push each layer of your image to Clair.
2. Create a Manifest Resource: Create a manifest that describes the layers of your image.
3. Query for Vulnerabilities: Query the Clair API for vulnerabilities associated with the manifest.

While a direct CLI command isn't part of Clair, you'd use curl or a similar tool to interact with the API endpoints. For instance:

# Example (Illustrative only - specific endpoints and data structures depend on Clair's API version):

# 1. Push Layer (simplified example)
curl -X POST -H "Content-Type: application/json" -d '{"name": "layer1", "path": "/path/to/layer1.tar.gz"}' http://localhost:6060/v1/layers

# 2. Create Manifest
curl -X POST -H "Content-Type: application/json" -d '{"schemaVersion": 2, "layers": [{"name": "layer1"}]}'  http://localhost:6060/v1/manifests

# 3. Get Vulnerabilities
curl -X GET http://localhost:6060/v1/manifests/<manifest_id>/vulnerability

Important: These Clair examples are highly simplified for illustrative purposes. The exact API endpoints, request bodies, and authentication methods will vary based on the specific version of Clair you are using. Refer to the official Clair documentation for detailed information on the API.

6. Conclusion

Both Anchore and Clair are valuable tools for securing container images. The choice between them depends on your specific requirements and priorities.

• Choose Anchore if: You need a comprehensive solution with advanced policy enforcement capabilities, detailed image analysis, and extensive integration options, and you're willing to invest the time and resources to set it up and configure it properly.
• Choose Clair if: You need a lightweight, fast, and scalable solution for vulnerability scanning, and you prefer a simpler setup and API-driven architecture. It is a good choice when primarily focused on identifying vulnerabilities and integrating into other systems that can handle policy enforcement.

Ultimately, the best approach is to evaluate both tools and determine which one best fits your organization's security needs and technical capabilities. Integrating either of these tools into your CI/CD pipeline is a critical step towards building a more secure container environment.