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Showing posts with the label python3

Trivy for docker image scanning

  We have seen a lot of security scanning tools like Blackduck, Fortify, SonarQube etc.. these tool scan source code and the built binaries, it is all well and good I think they do the best job in their respective feature kits. in a industry where we are shipping the solutions in containers bundled with the binaries, it is relevant if we had a tool that could scan the final product. That is what Trivy an open source project is offering. it is developed by aqua security. I think it is a brilliant little tool that scans for security issues in a docker image for free!! well what and all it will scan? it scans for operating system libraries that support your application and the application itself. it scans for any misconfigurations, secrets as well. only thing it don't have is a dashboard like sonarqube and blackduck. still it generates text and JSON based reports that can be used to create dashboards in grafana or superset. Operating System Libraries : Trivy scans the base image and a...

K-means using ‘seed-randint-numpy’

K-means classification K-means, a simple Machine learning algorithm used for classification purposes. Machine learning is an awesome field, full of interesting topics and scenarios to study. While starting in this track one of the basics we study is classifiers, these things can be complex as hell and also easy as watching Tom chasing Jerry on television. I have implemented the K-means with a simple NumPy library of python 3. It’s a good start for someone who is started to learn or teaching this classifier. No Oop used, just some function call which intern makes some more function calls. View the full code in my GitHub repository follow this link K-means notebook