Security testing guides — vulnerability scanning, penetration testing basics, and secure SDLC practices.
Security Testing
Security testing is not the exclusive domain of penetration testers. Developers who understand the OWASP Top 10 and can write test cases against each category catch vulnerabilities before they ever reach a staging environment — let alone production. This guide walks through each OWASP Top 10 item (2021 edition) with a
Fuzz Testing
Fuzz testing (fuzzing) automatically generates random, malformed, or unexpected inputs and feeds them to your program looking for crashes, hangs, memory corruption, and assertion violations. Modern coverage-guided fuzzers like AFL++ and LibFuzzer generate millions of test cases per second guided by code coverage feedback and have found thousands of
Security Testing
Penetration testing at scale requires the right toolset. Even experienced security professionals who rely heavily on manual testing use automated tools to accelerate reconnaissance, identify low-hanging fruit, and validate findings. The difference between a skilled tester and a script kiddie isn't whether they use automated tools — it&
Security Testing
Container security is different from traditional application security. Your attack surface includes the base image, installed packages, runtime configuration, Kubernetes RBAC, network policies, and more — not just your application code. Aqua Security is purpose-built for this environment. This guide covers what Aqua does, how to integrate it into your
Fuzz Testing
Basic AFL++ usage — compile with afl-clang-fast, create a seed corpus, run afl-fuzz — finds bugs. Advanced AFL++ usage finds them 10–100x faster, or finds bugs that basic usage misses entirely. This post covers the techniques that make AFL++ effective against hard targets: persistent mode, comparison logging, custom
Security Testing
Every security tool your team buys or builds generates findings. The critical design question isn't "what findings does this tool produce" — it's "what happens when it finds something?" Without a deliberate gate design, you end up in one of two failure modes:
Security Testing
A complete AppSec pipeline combines three layers: SAST (static analysis of source code), SCA (vulnerable dependency scanning), and DAST (dynamic testing of the running app). Each layer catches different vulnerabilities. This guide shows you how to wire all three into a CI/CD pipeline, where to place each gate, and
AFL++
AFL++ (American Fuzzy Lop++) is the most widely used coverage-guided fuzzer for C and C++ programs. It instruments your binary at compile time to track code coverage, then mutates inputs guided by that coverage to explore your program's logic exhaustively. Used by Google, Mozilla, and security researchers
Testing
OSS-Fuzz is Google's free continuous fuzzing service for open source software. Once integrated, your project gets fuzzed 24/7 on Google's infrastructure using libFuzzer, AFL++, and Honggfuzz. Crashes are automatically deduplicated, tracked, and reported. As of 2024, OSS-Fuzz has found over 10,000 vulnerabilities
Testing
AFL++ is the most widely used coverage-guided fuzzer. It's responsible for finding thousands of CVEs in real-world software — in image parsers, network libraries, file format handlers, and more. This tutorial walks through everything you need to go from installation to finding actual bugs. Installation Ubuntu/Debian:
gRPC
gRPC security testing is often skipped because certificates are annoying to set up in test environments. That's exactly why certificate misconfigurations, expired credentials, and bypass vulnerabilities make it to production. This guide covers practical approaches to testing gRPC TLS and authentication without making your CI pipeline miserable. What
Chaos Engineering
Traditional chaos engineering focuses on infrastructure failure: pods terminating, networks degrading, databases slowing down. Security chaos engineering extends this to adversarial conditions: authentication systems under attack, authorization bypasses attempted, API rate limits hammered. The question isn't just "does the system survive?" — it's "does