Aaron SawitSecurity engineer · Singapore

Security engineer · Singapore

Security engineer who builds.

I do security risk and compliance for a living. Outside work I build things people actually use, run my own servers, keep AI on a short leash, and chase bugs down to the real cause.

Aaron Sawit

useful, but supervisedAI engineering

I use AI every day, and I don't trust it by default. Everything here has a limit, a test or a person checking the model's work, because that's the bit most AI projects skip.

Play "Break my bot" a six-level game I made. Try to talk a chatbot into leaking its password and see which defences hold up.

  1. Versed

    AI inside a free product for kids

    An AI helper in Versed Study with a hard cap on it, and AI-built flashcard decks in Versed Learn. Both are in tools students use.

    The guardrailLimits per visitor and per day live in a Durable Object, after I proved a KV counter can't hold a rate limit. A deck costs about 3 cents to generate, so the free tier has a real number behind it. No user photo uploads on public content, and chat goes through a word filter with reporting.

    Write-up: the rate limit that did not limit
  2. DART assignment, 2025

    AI marking for a selection exam

    I rebuilt an early prototype into an AI marking system for a cybersecurity bootcamp's selection exam: Claude on AWS Bedrock, versioned prompts and an evaluation harness. It marked several hundred scripts, past papers and live applicants.

    The guardrailI didn't trust anything I hadn't measured. Every prompt change got re-run against the instructors' marking, and agreement went from about 60% to about 77%. That number is the point. The model is a fast first marker, not the judge, and the disagreements are where a person needs to look.

    On my CV
  3. GitHub, open source

    Open-source tools for AI security

    Three small tools that came out of my own AI work: regression tests for prompt-injection defences, a bit-level check of a model file against the base it claims, and a probe that tells you if a model really calls tools.

    The guardrailAll three grade on facts, not opinions. A random token either came back or it didn't. A bit either changed or it didn't. None of them needs a second model to judge the first, and each README says what it can't do, including the case the model audit can't see.

    Code and passing tests on GitHub

All 10 AI projects, and the guardrail on each one

three kinds of workWhat I'm good at

The work I do most, and the tools I usually reach for in each.

Detection and response

I do log analysis, SIEM work and incident handling. I write detections other people can read and test, and I keep digging until I can name the one thing that caused it.

  • Sigma rules mapped to MITRE ATT&CK
  • Elastic Stack and Splunk
  • Sysmon and Windows event logs
  • incident handling (SANS SEC504)
  • Wireshark
  • Nmap
  • YARA
  • Snort

Security-minded infrastructure

I run Linux, containers, networking and monitoring as code, with backups I've actually restored from and a threat model I can explain.

  • Linux
  • Docker and Compose
  • systemd
  • iptables
  • WireGuard and Tailscale
  • DNS filtering
  • backups and monitoring

Shipping secure products

I take products from a blank page to real users on Cloudflare's edge, and I sort out privacy and abuse as part of the design, not as a patch later.

  • AWS Bedrock and IAM
  • Cloudflare Workers
  • Durable Objects
  • D1
  • KV and Pages
  • TypeScript
  • authentication and sessions
  • rate limiting
  • CSP and security headers

the side projectsMore work

Stuff I run on my own hardware, plus the small open-source tools that fell out of it.

  1. Decode speed, tokens per second 35B MoE model · 2× GTX 1080 Ti · same hardware default runtime46 + speculative decoding43net loss quantised cache, 64K42not free tuned, full 32K depth60 tuned, empty context71 48K context passed every check, then crashed. Test at full depth.

    Performance engineering

    Local AI on 2017 hardware

    A 35-billion-parameter model made 44% faster on nine-year-old GPUs by measuring every assumption.

    • 46 to 71 tokens a second
    • +44% on the same hardware
    • 1 crash found before it shipped
    Read the case study
  2. phoneanywhere laptophome or away TV boxliving room WireGuard, end to end one server2017 gaming PC · 2 GPUs · 40+ apps DNS filterfor every device VPN exit nodefails closed photos · passwordsdocuments · recipes media serverGPU transcoding game streamingheadless 1080p60 local LLMsacross both GPUs backups · uptime checks · alertsrebuilt from one folder public internet0 open ports blocked

    Infrastructure, self-hosted

    One box, forty services

    A recycled gaming PC running my family's photos, passwords, media and AI, reachable from anywhere and exposed to no one.

    • 40+ services
    • 0 ports open to the internet
    • 14 days of restorable backups
    Read the case study

Also built

Aaron Sawit
Aaron SawitSingapore · UTC+8

About

I work in cybersecurity full time, on the risk and compliance side. I also tutor special needs kids, and have since 2020. That's why the Versed tools exist and why they're free: my students needed calmer, simpler tools than the ones schools pay for, so I built them.

Most of my training has been hands-on. I hold the GIAC Certified Incident Handler and worked through Hack The Box's SOC analyst path. My favourite part of any investigation is when a vague "it's broken" turns into one specific line in one specific log.

Six years of teaching kids who struggle with reading has made me good at something most engineers dodge: explaining a hard thing to someone who isn't technical, without talking down to them.

Credentials

  • BSc (Hons) Computer Science, First Class HonoursCoventry University, United Kingdom
  • Diploma in Information TechnologyPSB Academy, Singapore
  • GIAC Certified Incident Handler (GCIH)SANS SEC504: Hacker Tools, Techniques and Incident Handling
  • Hack The Box AcademySOC Analyst path: SIEM, Windows event logs, incident handling
  • Red AlphaCybersecurity specialist training, Singapore
  • CSIT TISC CTFNational capture-the-flag. In 2026, the year AI tools were allowed, cleared four of ten levels in a single day.

Get in touch

I read and reply to every message. Happy to walk through any of this on a call, too.