conftest
clair
Our great sponsors
conftest | clair | |
---|---|---|
9 | 21 | |
2,785 | 10,030 | |
1.0% | 0.9% | |
8.5 | 9.2 | |
7 days ago | 6 days ago | |
Go | Go | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
conftest
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Validation on list(object) variables
I wrote following conftest.dev (OPA), sample policy
- The default.go file meaning
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Introducing Conftest and setting up CI with Github Actions to automate reviewing of Terraform code
name: tf-plan-apply on: pull_request: branches: [ main ] env: TF_VERSION: 1.0.0 CONFTEST_VERSION: 0.28.3 WORKING_DIR: ./ jobs: terraform: name: aws-eureka-pairs-etc-s3 runs-on: ubuntu-latest steps: - name: Checkout uses: actions/checkout@v2 - name: Install conftest run: | wget -O - 'https://github.com/open-policy-agent/conftest/releases/download/v${{ env.CONFTEST_VERSION }}/conftest_${{ env.CONFTEST_VERSION }}_Linux_x86_64.tar.gz' | tar zxvf - ./conftest --version //❶ - name: Setup Terraform uses: hashicorp/setup-terraform@v1 with: terraform_wrapper: false //❷ terraform_version: ${{ env.TF_VERSION }} cli_config_credentials_token: ${{ secrets.YOUR_CRED_NAME}} - name: Terraform Init ${{ env.WORKING_DIR }} working-directory: ${{ env.WORKING_DIR }} run: terraform init - name: Terraform Plan ${{ env.WORKING_DIR }} if: github.event_name == 'pull_request' env: GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} working-directory: ${{ env.WORKING_DIR }} id: plan run: terraform plan -out=tfplan -no-color -lock=false -parallelism=50 - name: Convert terraform plan result to json formmat if: github.event_name == 'pull_request' id: convert working-directory: ${{ env.WORKING_DIR }} run: terraform show -json tfplan > tfplan.json - name: conftest test if: github.event_name == 'pull_request' id: conftest run: ./conftest test --no-color ${{ env.WORKING_DIR }}/tfplan.json //❸
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Kubernetes Security Checklist 2021
Workload configuration should be audited regularly (Kics, Kubeaudit, Kubescape, Conftest, Kubesec, Checkov)
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Don't let your Terraform go rogue with Conftest and the Open Policy Agent
Insert Conftest! As they state in their GitHub description, Conftest tests against structured configuration data using the Open Policy Agent Rego query language. In the case of Terraform, this means we're actually running unit tests against sample JSON and actual tests against the Terraform state JSON.
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Using Open Policy Agent and Conftest to Validate Your Openshift 4 IPI Configuration
While Rego is the policy language we use to assemble our policies, we still need something to run those policies with. If you have a cluster and you want to actively evaluate policies, you can end up running an instance of Open Policy Agent and it's associated tooling. However in our case, we just want to check things at runtime (or just on some recurring basis such as when changes get checked in or a pull request is submitted). In the latter instance, we are able to use another tool from the Open Policy Agent project called ConfTest. What ConfTest allows us to do is to specify a file or directory of files that we want to inspect along with the set of policies we want to inspect them with. It then takes all of that and dumps out the associated outputs from those policies and tell us the results (i.e. the messages, how many policies were checked and the results of those policies). This tool is much better suited for our use case, so this is what we will proceed with. To grab the latest version of ConfTest, you can grab the latest release from here.
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!!!*IMP: Conftest Integration with AWS or Other*!!!!
OR HOW TO RUN https://github.com/open-policy-agent/conftest AS CI/CD in Circle CI to apply policies?
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Terraforming in 2021 – new features, testing and compliance
If you like terraform-compliance, Conftest might also be worth having a look. It has its own DSL to write policies, and allows you to test multiple frameworks. We found this blog post from Lennard Eijsackers very informative, and would thus rather recommend you to check it out.
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Mental models for understanding Kubernetes Pod Security Policy PSP
Can Gatekeeper and Conftest single-source the same set of rules? I'm looking at https://github.com/open-policy-agent/conftest/issues/54#issuecomment-528988831 and not seeing how.
clair
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I looked through attacks in my access logs. Here's what I found
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/
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General Docker Troubleshooting, Best Practices & Where to Go From Here
Clair. Vulnerability Static Analysis for Containers.
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Open source container scanning tool to find vulnerabilities and suggest best practice improvements?
https://github.com/quay/clair 9.4k stars, updated 17 hours ago
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Postgres: The Graph Database You Didn't Know You Had
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
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Homelab vulnerability/virus scanner
Clair GitHub
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Implement DevSecOps to Secure your CI/CD pipeline
Open source: Trivy, Gryp and Clair are widely used open source tools for container scanning.
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Sublime Music - A FLOSS desktop client for Subsonic API servers (Airsonic, Navidrome, Gonic, etc)
Testing the image with github.com/fullhunt/log4j-scan and https://github.com/quay/clair shows no vulnerabilities
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Automatically tag your Docker images as vulnerable in ECR
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.
- Clair – Vulnerability Static Analysis for Containers
What are some alternatives?
checkov - Prevent cloud misconfigurations and find vulnerabilities during build-time in infrastructure as code, container images and open source packages with Checkov by Bridgecrew.
trivy - Find vulnerabilities, misconfigurations, secrets, SBOM in containers, Kubernetes, code repositories, clouds and more
terratest - Terratest is a Go library that makes it easier to write automated tests for your infrastructure code.
grype - A vulnerability scanner for container images and filesystems
tfsec - Security scanner for your Terraform code [Moved to: https://github.com/aquasecurity/tfsec]
syft - CLI tool and library for generating a Software Bill of Materials from container images and filesystems
tflint - A Pluggable Terraform Linter
Harbor - An open source trusted cloud native registry project that stores, signs, and scans content.
inspec - InSpec: Auditing and Testing Framework
dagda - a tool to perform static analysis of known vulnerabilities, trojans, viruses, malware & other malicious threats in docker images/containers and to monitor the docker daemon and running docker containers for detecting anomalous activities
gatekeeper-library - 📚 The OPA Gatekeeper policy library
kubescape - Kubescape is an open-source Kubernetes security platform for your IDE, CI/CD pipelines, and clusters. It includes risk analysis, security, compliance, and misconfiguration scanning, saving Kubernetes users and administrators precious time, effort, and resources.