offensive security research & services

trace37 labs

original vulnerability research, proprietary offensive tooling, and technical writeups from active bug bounty engagements. DOM XSS, OAuth bypass, cache poisoning, postMessage exploitation, WAF evasion — tested against real-world defences.

// recent posts

// disclosures

view all →

// tools

view all →

Parallax

A purpose-built cache exploitation toolkit that finds the gap between what the cache thinks a request is and what the origin server actually processes. 13,000+ lines of Python and Bash across twelve tools and three shared libraries. # Pipeline Probe – CDN fingerprint, cache behaviour detection, TTL measurement Discover – Find cached endpoints via wordlists, katana crawling, GAU historical URLs, and BigQuery traffic data Diff – Byte-level path delimiter fuzzing, response diffing across cache/origin Poison – Binary search 10,000+ headers in ~560 requests, unkeyed query strings, parameter cloaking, fat GET, cookie testing Weaponize – Auto-classify exploits (XSS, redirect, CP-DoS, session fixation, CSP bypass) and generate proof-of-concept chains # Key Capabilities CDN-aware scanning: Akamai, Cloudflare, Fastly, Varnish, CloudFront detection with CDN-specific oracles Multi-signal response diffing: status changes, body size deltas, new headers, security header modifications Integrated WCP + WCD in a single pipeline Path normalization detection and exploitation Internal/application-level cache detection via multi-request priming # Read More For the full technical exploration of every component, research foundations, and design decisions: Parallax: A Research-Based Cache Exploitation Toolkit

DOMPurify Evolutionary Fuzzer

A large-scale evolutionary fuzzing system targeting DOMPurify, the industry-standard XSS sanitization library (24M+ weekly npm downloads). Instead of random fuzzing, it treats vulnerability discovery as an optimization problem – evolving payloads through fitness functions, mutation operators, and crossover to systematically explore the sanitizer’s attack surface. # Approach Evolutionary algorithms over wordlists – payloads evolve based on what survives sanitization, not random generation Fitness functions – measure partial success (what survives even if it doesn’t execute) and evolve from there 5-Rotor mutation operators – context-aware mutations drawn from the Enigma XSS methodology Population management – crossover, selection pressure, diversity maintenance across generations # Why DOMPurify Core DOMPurify bypasses continue to be discovered (CVE-2025-26791, CVE-2024-45801), demonstrating that even battle-tested sanitizers have undiscovered attack surfaces.