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# Clair
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[![Build Status ](https://api.travis-ci.org/coreos/clair.svg?branch=master "Build Status" )](https://travis-ci.org/coreos/clair)
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[![Docker Repository on Quay ](https://quay.io/repository/coreos/clair/status "Docker Repository on Quay" )](https://quay.io/repository/coreos/clair)
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[![Go Report Card ](https://goreportcard.com/badge/coreos/clair "Go Report Card" )](https://goreportcard.com/report/coreos/clair)
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[![GoDoc ](https://godoc.org/github.com/coreos/clair?status.svg "GoDoc" )](https://godoc.org/github.com/coreos/clair)
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[![IRC Channel ](https://img.shields.io/badge/freenode-%23clair-blue.svg "IRC Channel" )](http://webchat.freenode.net/?channels=clair)
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Clair is an open source project for the static analysis of vulnerabilities in [appc] and [docker] containers.
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Vulnerability data is continuously imported from a known set of sources and correlated with the indexed contents of container images in order to produce lists of vulnerabilities that threaten a container.
When vulnerability data changes upstream, the previous state and new state of the vulnerability along with the images they affect can be sent via webhook to a configured endpoint.
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All major components can be [customized programmatically] at compile-time without forking the project.
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Our goal is to enable a more transparent view of the security of container-based infrastructure.
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Thus, the project was named `Clair` after the French term which translates to *clear* , *bright* , *transparent* .
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[appc]: https://github.com/appc/spec
[docker]: https://github.com/docker/docker/blob/master/image/spec/v1.md
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[added programmatically]: #customization
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## Common Use Cases
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### Manual Auditing
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You're building an application and want to depend on a third-party container image that you found by searching the internet.
To make sure that you do not knowingly introduce a new vulnerability into your production service, you decide to scan the container for vulnerabilities.
You `docker pull` the container to your development machine and start an instance of Clair.
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Once it finishes updating, you use the [local image analysis tool] to analyze the container.
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You realize this container is vulnerable to many critical CVEs, so you decide to use another one.
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[local image analysis tool]: https://github.com/coreos/clair/tree/master/contrib/analyze-local-images
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### Container Registry Integration
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Your company has a continuous-integration pipeline and you want to stop deployments if they introduce a dangerous vulnerability.
A developer merges some code into the master branch of your codebase.
The first step of your continuous-integration pipeline automates the testing and building of your container and pushes a new container to your container registry.
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Your container registry notifies Clair which causes the download and indexing of the images for the new container.
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Clair detects some vulnerabilities and sends a webhook to your continuous deployment tool to prevent this vulnerable build from seeing the light of day.
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## Hello Heartbleed
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### Requirements
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An instance of [PostgreSQL] 9.4+ is required.
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All instructions assume the user has already setup this instance.
During the first run, Clair will bootstrap its database with vulnerability data from its data sources.
This can take several minutes.
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[PostgreSQL]: http://postgresql.org
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### Docker
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The easiest way to get an instance of Clair running is to simply pull down the latest copy from Quay.
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```sh
$ mkdir $HOME/clair_config
$ curl -L https://raw.githubusercontent.com/coreos/clair/config.example.yaml -o $HOME/clair_config/config.yaml
$ $EDITOR $HOME/clair_config/config.yaml # Add the URI for your postgres database
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$ docker run -p 6060-6061:6060-6061 -v $HOME/clair_config:/config quay.io/coreos/clair -config=/config/config.yaml
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```
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### Source
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To build Clair, you need to latest stable version of [Go] and a working [Go environment].
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[Go]: https://github.com/golang/go/releases
[Go environment]: https://golang.org/doc/code.html
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```sh
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$ go get github.com/coreos/clair
$ go install github.com/coreos/clair/cmd/clair
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$ $EDITOR config.yaml # Add the URI for your postgres database
$ ./$GOBIN/clair -config=config.yaml
```
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## Documentation
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Documentation can be found in a `README.md` file located in the directory of the component.
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- [Notifier ](https://github.com/coreos/clair/blob/master/notifier/README.md )
- [v1 API ](https://github.com/coreos/clair/blob/master/api/v1/README.md )
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### Architecture at a Glance
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![Simple Clair Diagram ](img/simple_diagram.png )
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### Terminology
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- *Image* - a tarball of the contents of a container
- *Layer* - an *appc* or *Docker* image that may or maybe not be dependent on another image
- *Detector* - a Go package that identifies the content, *namespaces* and *features* from a *layer*
- *Namespace* - a context around *features* and *vulnerabilities* (e.g. an operating system)
- *Feature* - anything that when present could be an indication of a *vulnerability* (e.g. the presence of a file or an installed software package)
- *Fetcher* - a Go package that tracks an upstream vulnerability database and imports them into Clair
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### Vulnerability Analysis
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There are two major ways to perform analysis of programs: [Static Analysis] and [Dynamic Analysis].
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Clair has been designed to perform *static analysis* ; containers never need to be executed.
Rather, the filesystem of the container image is inspected and *features* are indexed into a database.
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By indexing the features of an image into the database, images only need to be rescanned when new *detectors* are added.
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[Static Analysis]: https://en.wikipedia.org/wiki/Static_program_analysis
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[Dynamic Analysis]: https://en.wikipedia.org/wiki/Dynamic_program_analysis
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### Default Data Sources
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| Data Source | Versions | Format |
|-------------------------------|--------------------------------------------------------|--------|
| [Debian Security Bug Tracker] | 6, 7, 8, unstable | [dpkg] |
| [Ubuntu CVE Tracker] | 12.04, 12.10, 13.04, 14.04, 14.10, 15.04, 15.10, 16.04 | [dpkg] |
| [Red Hat Security Data] | 5, 6, 7 | [rpm] |
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[Debian Security Bug Tracker]: https://security-tracker.debian.org/tracker
[Ubuntu CVE Tracker]: https://launchpad.net/ubuntu-cve-tracker
[Red Hat Security Data]: https://www.redhat.com/security/data/metrics
[dpkg]: https://en.wikipedia.org/wiki/dpkg
[rpm]: http://www.rpm.org
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### Customization
The major components of Clair are all programmatically extensible in the same way Go's standard [database/sql] package is extensible.
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Custom behavior can be accomplished by creating a package that contains a type that implements an interface declared in Clair and registering that interface in [init()]. To expose the new behavior, unqualified imports to the package must be added in your [main.go], which should then start Clair using `Boot(*config.Config)` .
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The following interfaces can have custom implementations registered via [init()] at compile time:
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- `Datastore` - the backing storage
- `Notifier` - the means by which endpoints are notified of vulnerability changes
- `Fetcher` - the sources of vulnerability data that is automatically imported
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- `MetadataFetcher` - the sources of vulnerability metadata that is automatically added to known vulnerabilities
- `DataDetector` - the means by which contents of an image are detected
- `FeatureDetector` - the means by which features are identified from a layer
- `NamespaceDetector` - the means by which a namespace is identified from a layer
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[init()]: https://golang.org/doc/effective_go.html#init
[database/sql]: https://godoc.org/database/sql
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[main.go]: https://github.com/coreos/clair/blob/master/cmd/clair/main.go
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## Related Links
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- [Talk ](https://www.youtube.com/watch?v=PA3oBAgjnkU ) and [Slides ](https://docs.google.com/presentation/d/1toUKgqLyy1b-pZlDgxONLduiLmt2yaLR0GliBB7b3L0/pub?start=false&loop=false&slide=id.p ) @ ContainerDays NYC 2015
- [Quay ](https://quay.io ): the first container registry to integrate with Clair
- [Dockyard ](https://github.com/containerops/dockyard ): an open source container registry with Clair integration