The Lab · 10 instruments
Things I built to understand how they break.
Every instrument below is real and runs entirely in your browser. Nothing is a mockup, nothing phones home, and each one shows the working underneath it rather than a verdict you have to take on faith.
- Adversarial ML
What a gradient can do to a classifier that looks, to us, completely unchanged.
- Model faithfulness
Whether a model’s stated reasoning is the reason for its answer, tested three ways.
- Applied security
The everyday triage work: indicators, URLs, passwords, frames, hashes.
Adversarial examples playground
Fool a neural network in real time. Draw or pick a digit, add an imperceptible perturbation, and watch the classifier flip while the image looks unchanged.
Open the instrument →Unfaithful reasoning
Add a bias the model is never told about and its answer moves, while its chain of thought never admits why.
Open →Load-bearing reasoning
Break a chain of thought, truncate it, corrupt a step or swap it for filler, and see whether the answer moves. Often it does not.
Open →Faithfulness, answer key held
A deterministic scorer ranks OSINT findings and the model only narrates, so the true cause is known exactly.
Open →Live global attack traffic
Which ports the internet is attacking most right now, live from a worldwide honeypot network, and what each attack actually is.
Open →Phishing URL inspector
Paste a link and see where it truly points. Flags lookalike domains, brand impersonation and typosquats, without ever opening it.
Open →IOC extractor
Drop in a log or a phishing email and pull out the IPs, domains, URLs, hashes and CVEs, de-duplicated and defanged.
Open →Password strength lab
Not a red-yellow-green meter: the actual entropy, the patterns an attacker exploits, and realistic crack times.
Open →CAN frame decoder
Decode a raw automotive CAN bus frame into its ID, type, length and per-byte view. The protocol my research defends.
Open →Hash & encoding workbench
SHA-1/256/512, Base64, hex and URL encode-decode, and a JWT decoder. The everyday conversions, without pasting secrets into a random site.
Open →Built and maintained by Yulan Galagoda alongside research on intrusion detection for in-vehicle networks. The portfolio, with the work these came out of, is at yulan.me.