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⚡ tsecurity.de Intelligence

This is how I created a game from scratch using AWS

A couple of weeks ago I heard about AWS's Build Games Challenge, I got excited as I saw it as an opportunity to build my first game. At that time the challenge wasn't considering latin american countries, so I couldn't participate, but it…

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A couple of weeks ago I heard about AWS's Build Games Challenge, I got excited as I saw it as an opportunity to build my first game. At that time the challenge wasn't considering latin american countries, so I couldn't participate, but it was a pleasant surprise when I saw an update on the post where AWS was now accepting more countries, including mine, there were no more excuses for me.



As the theme of the challenge was to build retro games, first I started to ask myself, what's "retro"? as for some people it could be a black and white, pixels only Pong game, and for others it could be N64 GoldenEye. I decided to stick with the games that I played as a kid, being nintendo (NES) platform, games like Ninja Gaiden, Megaman, Mario 3 among others really leaved an impression on me, so I started to think which of those games I could build as my first approach to video game development, I recall a mini game on Mario 3, memory card game.



Image description



My intention was to create a game that has some relation with AWS, to facilitate the newcomers on AWS world to get used to AWS services, let them know some AWS Servies names, and which ones are fundamentals, and which ones are more advanced.



I was impressed by Amazon Q, first it helped me on the description of the prompt, that was very helpful as I was considering a list of things, but others were out of my sigh, like adding a timer and other little details that I'm sure helped on completing the game faster by being more specific. Also I really like it that Q iterated on it's own proposals, anticipating fine tunes from me, for example, initially it tried to use emojis for the cards, but without me asking, it iterated and make the icons as SVG format to keep the escense of retro game. Also Q identified screenshots of the game on the root of the repository, and it added them as examples in the README.md file, that was very nice.



I discovered that Q support not only text (prompt), but also images, I just had to reference the filename and it handled it perfectly, no special command or tag to make it work, it was very natural.



My role in the past years has been mostly on Site Reliability Engineer side, so I feel confortable with tools like Infrastructure as Code, Continuos Integration, so I leverange on Amazon Q not only to build the game, but also to automate the deployment process, on creating the infrastructure and CI/CD pipeline, it was perfect for my workflow, I knew what I wanted, I asked for it and then I reviewed the proposed code, it was almost a one-shot prompt, that kept me on the flow which is the porpuse of the tools that we use, accomplish goals.



Here are some screenshots of the game 👇

Easy mode 😌: 4 pair of cards ; fundamental AWS Services

Image description



Hard mode 😰: 9 pair of cards ; advanced AWS Services

Image description



🎮 Play now: http://aws-memory-game-javitech.s3-website-us-east-1.amazonaws.com



✨ Source Code on Github repository: https://github.com/dvst/game-memory-aws-build-challenge



Do you like it the game? give it a star on github. have any ideas to improve the game? play with it and create a Pull Request!



📺 YouTube of video game creation process from scratch (Spanish with English subtitles): https://www.youtube.com/watch?v=tBxS8aDbrPQ

CTI Threat Relationship Graph2 Knoten / 1 Relationen
CVE / Incident Software MITRE ATT&CK CWE Weakness IoC
SOC Incident Playbook: Remote Code Execution (RCE) Defense
title: Detect Exploitation - This is how I created a game from scratch using AWS
id: b0a72f7d-c47f-48d2-adee-32bea6fd5b9f
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-24
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-24"
        description = "YARA Signature for "
    strings:
        $str = "This is how I created a game f" ascii wide
    condition:
        any of them
}
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich This is how I created a game from scratc.... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

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