Metasploitable2 - FTP Exploitation using vsftpd 2.3.4 Backdoor 1. Objective To identify and exploit a known vulnerability in an FTP service running on a vulnerable target machine using industry-standard reconnaissance and exploitation techniques. 2. Lab Environment Component Description Attacker Machine Kali Linux Target Machine Metasploitable2 Network Type Host-only / NAT
This is Part 1 of a two-part series. Part 2 (coming soon): Connecting to spoke clusters from a controller using multicluster-runtime, driven by ClusterProfile. The Cluster Inventory API (multicluster.x-k8s.io) is driven by SIG-Multicluster and centered on the ClusterProfile resource. It only delivers value when something produces those ClusterProfiles. That something is a cluster manager. Today, t
At the beginning of this series, the problem seemed simple. There were a lot of rocks in the yard. Some were small. Some were large. A few were firmly in what I’ve been calling Engine Block Class. The original idea was straightforward: catalog them, maybe sell a few, and build a small system around the process. Along the way, the project grew. What We Built Across the previous posts, the Backyard
When developers travel, we usually prepare the obvious things. Laptop charger. But there is one dependency that is easy to underestimate until it breaks: mobile internet. A trip to China makes this especially obvious. Not because China is hard to travel in, but because so many basic interactions are mobile-first: navigation, translation, ride-hailing, hotel communication, ticket confirmations, pay
We've been there. JSON Schema gets hard to write as soon as your payload is non-trivial. Conditional logic, cross-field rules, business invariants, and at some point we stop writing contracts at all. We go code-first, generate the schema from annotations, and end up with 200 lines very few understand, and error messages referencing paths like #/properties/items/allOf/0/then/Then that map to nothin
Originally published on graycloudarch.com. You just merged a PR. Now you open Jira, find the ticket, paste the PR link in a comment, transition the status to Done, and update the deployed field. Five minutes. Twenty times a week. That's 1,700 minutes per year per engineer — nearly 30 hours of pure mechanical overhead. And that's assuming you remember. On one team I worked with, we audited the last
Metric Value Django Average Response Time 287ms Node.js Average Response Time 193ms Django Memory Usage (1000 users) 1.8GB We tested Django 4.2 and Node.js 18.16 under identical conditions to measure their performance for reporting dashboard workloads. The test environment consisted of AWS EC2 m5.2xlarge instances (8 vCPUs, 32GB RAM) running Ubuntu 22.04. Both frameworks connected to th
If you've ever built ETL pipelines pulling data from MongoDB into Delta Lake using Spark, you've probably hit this wall. The pipeline works fine — until it doesn't. A single document with an unexpected shape is enough to break the entire write, leave the table in an inconsistent state, and send your on-call engineer digging through Spark logs at 11pm. I built and maintained more than 10 of these j