Welcome to My Blog on Cybersecurity, Computing, and Other Topics
Python has great exception-handling with nice traceback messages that can help debug issues with your code. Here’s an example of a typical traceback message: I usually read these from the bottom-up to zero-in on the issue. Here I can see that my program is trying to pop the last item off a list called parsed_line,Continue reading “More Comprehensive Tracebacks in Python”
JC version 1.11.1 includes custom colors, dmidecode parser, enhanced netstat parser, more macOS support, new packaging, and more!
jello works similarly to jq but uses the python interpreter, so you can iterate with loops, comprehensions, variables, expressions, etc. just like you would in a full-fledged python script.
jtbl is simple and elegant. It just takes in piped JSON or JSON Lines data and prints a table. There’s only one option to turn on column truncation vs. wrapping columns if the terminal width is too narrow to display the complete table. It ‘does the right thing’.
In this post we will implement the Sidecar-on-Sidecar pattern in an Istio Service Mesh to provide application layer security and micro-segmentation.
In this post we’ll configure a Security Sidecar Pattern which will provide application level protection and micro-segmentation within the Kubernetes cluster.
In this post we will take an insecure deployment and implement a Security Service Layer Pattern to block application layer attacks and enforce strict segmentation between services.
In this post we will set the groundwork to deep dive into the Security Service Layer Pattern with a live insecure deployment on Google Kubernetes Engine (GKE). By the end of this post you will be able to bring up an insecure deployment and demonstrate layer 7 attacks and unrestricted access between internal services.
In this multi-part blog series, I will describe some microservice security design patterns to implement micro-segmentation and deep inspection in the interior of your Kubernetes cluster to further secure your microservice applications, not just the cluster. I will also demonstrate the design patterns with working Proof of Concept deployments that you can use as a starting point.
Do One Thing Well The Unix philosophy of using compact expert tools that do one thing well and pipelining them together to manipulate data is a great idea and has worked well for the past few decades. This philosophy was outlined in the 1978 Foreward to the Bell System Technical Journal describing the UNIX Time-SharingContinue reading “Bringing the Unix Philosophy to the 21st Century”
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