DEF CON 31 (2023), DEF CON 32 (2024) & DEF CON 33 (2025) — Finalist: 2nd place all three times.
A collection of my research in exploits, malware, reverse engineering, and client-side security.
A lightweight service and approach to detect prompt injection before your model sees it.
A learning-focused secure code review story that re-finds a 2014 bug.
A GitHub hub for collecting and sharing AWS threat intelligence.
How malicious actors hijack traffic and commit affiliate fraud—and defenses that work.
Deep dive into the compromise chain and mitigations.
Limits of IoCs and how to augment them.
OAuth abuse patterns on the client side.
Multi-platform targeting via UI manipulation.
Abusing web app install flows for fraud.
Mass injections and redirect monetization.
Campaign evolution and blockers.
Third-party supply chain risk realized.
Operational impact and how we adapted.
Indicators and containment.
Where inline protections fall short.
Cross-platform payload delivery.
Infrastructure re-use and takedown paths.
Obfuscation tricks and exfil flows.
Third-party trust boundaries tested.
Merchant-side script compromise analysis.
Repeat patterns, repeat impact.
Mitigations and lessons from the field.
ML-driven detections in practice.
Rapid response at scale.
Trends from global traffic.
Attack surface and mitigations.
Rule design and tuning.
Field report on active exploitation.
Localization tactics in fraud ops.
Social lures meet exploit delivery.
AI firewall for detecting & preventing prompt injection attacks.
Unsupervised clustering of malware families.
High-fidelity public cloud threat intel and atomic IOCs.
LLaMA-based personal model on Cloudflare Workers.
Tracking blocked websites and apps worldwide.
A calendar built with ChatGPT & Cloudflare Workers.