FuzzMind Security Labs is an independent security research lab established in 2026. We investigate high-impact failure modes across modern computing systems, report findings to affected vendors first, and publish technical detail after a reasonable remediation window.

Our work spans AI systems, mobile and desktop operating systems, browsers, kernels, firmware, radio stacks, silicon, and blockchain infrastructure. We test only where we have authorization: public demos and APIs within documented limits, software we license or run locally, open-source projects, and targets in active vulnerability disclosure or bug bounty programs.

We focus on places where deployment has outpaced the threat model. Each finding is reproduced on a clean baseline, reduced to the smallest useful proof, and documented after a fix or disclosure window is available.

Research surface

• AI & Agents — foundation-model safety boundaries, prompt injection, autonomous agents, MCP and tool-use integrations, RAG pipelines, model supply chains, and inference infrastructure such as vLLM, Triton, Ollama, and TGI.
• Android — Bionic, ART, mediaserver, system_server, SELinux, HAL, binder IPC, privilege-escalation chains on shipping devices.
• Apple — macOS and iOS: XNU, IOKit drivers, sandbox, entitlements, TCC, codesigning, WebKit/JSC.
• Browsers — V8, JavaScriptCore, SpiderMonkey, JIT bugs, renderer and GPU process sandbox escapes, DOM attack surface, and browser extension boundaries.
• Kernels — Linux, Windows NT, and BSD: syscall surface, filesystem race conditions, network stack, eBPF.
• Fuzzing — custom harnesses, coverage-guided fuzzers, snapshot fuzzing, differential and grammar-based approaches, and emulation pipelines.
• Silicon & Firmware — basebands, SoCs, TEE/TrustZone, secure elements, UEFI/BIOS, bootloaders, management controllers.
• Blockchain & Smart Contracts — EVM and Solana program auditing, L2 bridge security, wallet and key-management surfaces, DeFi protocol review, reentrancy, and economic attacks.
• Reverse engineering — closed-source firmware, malware, custom protocols, and embedded runtimes.

Operating principles

• Evidence over claims. Every finding is backed by a reproducible proof on a clean, minimal baseline.
• Chains, not tricks. A clever primitive that doesn't compose into real impact doesn't earn a write-up.
• Coordinated by default. 90-day disclosure by default, extendable on request when a concrete remediation plan is in progress; see our policy.
• Open tooling. Supporting fuzzers, harnesses, and replay kits are released on GitHub unless doing so would enable abuse against unpatched users.

Publishing cadence

We publish when the evidence is ready, not on a fixed schedule. Expect fewer posts, with enough detail for reproduction and review. Subscribe to the RSS feed, follow us on Mastodon, or watch the GitHub org for drops.

Contact

For reporting vulnerabilities in our systems, for collaboration, or for press: see /contact. Security-sensitive correspondence can be encrypted with our current team PGP key ( /pgp.asc fingerprint 9B80 FD6F B83A 1D7A 5F29 53D1 191B 3644 0B65 0C07). Email security@fuzzmind.io for disclosure coordination.