syft VS clair

Syft is a popular open source CLI tool created by Anchore for generating an SBOM from container images and filesystems. It’s designed to provide a catalog of dependencies for other tools to use as a data source. It supports many popular programming languages, package managers, and container image formats.

Inside of the SBOMs, we can detect a lot: https://github.com/anchore/syft#supported-ecosystems

You're right that the active/dormant detection needs to be customized per type of runtime. We cover rpm/deb, python and java with the node and others coming very soon. The compiled languages will be our main focus next. For example, Go binaries embed some dependency metadata in the binary itself.

Also related to this effort is the "in-toto" integrity chain: https://in-toto.io/in-toto/ Since we're already connecting build to run, we aim to complete the chain.

Installing syft is pretty straight forward. On any Linux/Mac environment you can run the following command to install

The data format is supported by cargo audit, Syft and Trivy. Reading it from your own tools is also very easy.

A Software-Bill-of-Materials (SBOM) lists all the software components included in an image. Buildpacks support SBOMs in CycloneDX, Syft and SPDX formats.

I think you can already do that using Syft.

I'll continue relying on Anitya for the feed and syft/grype to build my SBOM and track vulnerabilities.

Today corporations, open source projects, nonprofit foundations, and even governments are all trying to figure out how to improve the global software supply chain security. While these efforts are more than welcome, for the moment, there is hardly any straightforward way for organizations to improve on that front.

Syft is a popular open source tool that generates SBOMs for software applications and also containers. You can execute it manually and include the generated artifacts into your release, but you can also automate the process using a GitHub Action that will be triggered whenever you have a new release on your repository.

Besides pointing pentester tools like metasploit at yourself, there are some nice scanners out there.

https://github.com/quay/clair

https://github.com/anchore/grype/

Clair. Vulnerability Static Analysis for Containers.

https://github.com/quay/clair 9.4k stars, updated 17 hours ago

It scaled well compared to a naive graph abstraction implemented outside the database, but when performance wasn't great, it REALLY wasn't great. We ended up throwing it out in later versions to try and get more consistent performance.

I've since worked on SpiceDB[1] which takes the traditional design approach for graph databases and simply treating Postgres as triple-store and that scales far better. IME, if you need a graph, you probably want to use a database optimized for graph access patterns. Most general-purpose graph databases are just bags of optimizations for common traversals.

[0]: https://github.com/quay/clair

[1]: https://github.com/authzed/spicedb

Clair GitHub

Open source: Trivy, Gryp and Clair are widely used open source tools for container scanning.

Testing the image with github.com/fullhunt/log4j-scan and https://github.com/quay/clair shows no vulnerabilities

Amazon Elastic Container Registry is a fully-managed Docker container registry. It makes it easy for developers to store and manage Docker images inside their AWS environment. ECR supports two types of image scanning. Enhanced image scanning requires an integration with Amazon Inspector. It will scan your repositories continuously. Basic image scanning will use the Common Vulnerabilities and Exposures (CVEs) database (open-source Clair) to find vulnerabilities in your images. You can trigger scans on image push or manually.