Vulnerability-Research

Comprehensive Fuzzing Guide 🆕 Updated September 12, 2026 — added NASK/CERT Polska’s LLM-supervised autonomous fuzzing pipeline, plus the QEMU DMAR and ModSecurity findings it produced. A practitioner’s reference for fuzz testing — fundamentals, coverage feedback, harness construction, corpus strategy, sanitizer usage, and the tool stack for web, binary, kernel, API, and smart-contract targets. Table of Contents Fundamentals Fuzzing Taxonomy Coverage-Guided Fuzzing Harness Construction Corpus Management & Seed Selection Dictionaries & Structure-Aware Fuzzing Sanitizers Binary Fuzzing (AFL++, libFuzzer, honggfuzz, LibAFL) Web Fuzzing (ffuf, wfuzz, feroxbuster, Burp Intruder) API Fuzzing (REST, GraphQL, Protobuf) Kernel & OS Fuzzing Directed & Grammar-Based Fuzzing AI-Augmented Fuzzing JVM Fuzzing (Jazzer, LibAFL) Rust & Python Fuzzing Snapshot Fuzzing (Nyx, HyperHook) Smart Contract Fuzzing Protocol & Network Fuzzing (Boofuzz, ICS) Crash Triage & Minimization CI/CD Integration Bugs That Survive Continuous Fuzzing Real-World Wins & CVEs Tools & Frameworks Reference Wordlist & Corpus Resources Quick Reference Cheatsheet 1. Fundamentals Fuzzing is automated software testing by bombarding a target with a large volume of semi-random, invalid, or unexpected inputs and watching for crashes, hangs, memory errors, or assertion failures. The technique originates with Barton Miller’s 1988 University of Wisconsin-Madison experiment, where random inputs crashed roughly a third of tested Unix utilities. ...

Comprehensive Bug Bounty Hunting Guide 🆕 Updated September 12, 2026 — added the WPForms PayPal webhook duplicate story (CVE-2026-4986): what being reporter #11 tells you about target selection. A practitioner’s reference for modern bug bounty hunting — AI-augmented methodology, 2026 platform analysis, advanced reconnaissance pipelines, emerging vulnerability classes (SAML, WebAuthn, WASM), automated chaining, and data-driven career strategy. Enhanced with insights from 45+ methodology articles. Table of Contents Fundamentals & Mindset Bug Bounty Platforms Scope Analysis & Target Selection The End-to-End Methodology 2026 Methodology Advances Reconnaissance Pipeline Subdomain Enumeration Deep Dive Asset Discovery & Attack Surface Mapping JavaScript Analysis & Secret Hunting Content Discovery & Fuzzing Vulnerability Classes to Hunt Business Logic & Chaining Cloud, API & Web3 Attack Surfaces AI / LLM Testing Real-World Disclosed Writeups Report Writing & Triage Tools & Automation Stack Income & Payout Strategies Common Mistakes & Anti-Patterns Learning Resources Quick Reference Cheat Sheets 1. Fundamentals & Mindset Bug bounty hunting is the practice of finding and responsibly disclosing security vulnerabilities to organizations that reward researchers for their findings. Unlike traditional penetration testing, bug bounty is outcome-driven: no bug, no bounty. Payouts range from $50 nuisance bugs to $2M+ for critical cloud / crypto findings. ...

Use-after-free (UaF) vulnerabilities are one of the most exploited classes of memory corruption bugs. They’ve been at the heart of browser zero-days, Linux kernel privilege escalations, and countless CVEs. Despite being well understood, they remain stubbornly common — a testament to how easy they are to introduce and how hard they are to catch with conventional testing. What Is a Use-After-Free? A use-after-free occurs when a program: Allocates a chunk of memory on the heap Frees that memory (returning it to the allocator) Continues to use a pointer that still references the now-freed region The memory is no longer “owned” by the program. The allocator is free to give it to something else. When the program reads or writes through the dangling pointer, it’s operating on memory that may now belong to an entirely different object — or may have been zeroed, corrupted, or repurposed by an attacker. ...