About
A security research lab for complex software.
LucidBit Labs combines experienced vulnerability researchers, structured LLM workflows, reverse engineering, exploitability analysis, and proprietary tooling to uncover high-impact vulnerabilities and help teams build stronger systems.
The Lab
Built for difficult targets.
We are senior vulnerability researchers, reverse engineers, exploitability-focused auditors, and security engineers. Our work is strongest where standard testing breaks down: complex systems, native code, mobile internals, blockchain/DLT, protocol logic, security-critical flows, and unusual trust boundaries.
We approach targets as capable attackers would: understand the system, map realistic attack paths, investigate high-risk logic, validate exploitability, and turn findings into practical defense.
AI-amplified workflows help us reason across more code, generate better hypotheses, analyze changes faster, and search for variants. Human researchers decide what matters and prove every reported issue.
Capabilities
Research depth across complex software.
Vulnerability Research
Focused discovery of high-impact vulnerabilities in complex attack surfaces, critical logic, parsers, protocols, and implementation paths.
Reverse Engineering
Static and dynamic analysis of binaries, native libraries, mobile components, obfuscated logic, and proprietary protocols.
Exploitability Analysis
Manual validation of root cause, realistic attack paths, runtime behavior, impact, and remediation requirements.
Mobile & Application Security
Android and iOS application research, mobile wallets, RASP/root-detection review, native components, IPC, deep links, and backend interactions.
Blockchain/DLT & Protocols
Review of protocol logic, node and client behavior, smart contracts, wallets, bridges, validators, and off-chain/on-chain trust boundaries.
Remediation & Variant Analysis
Root-cause guidance, fix validation, variant hunting, secure design feedback, and hardening recommendations grounded in attacker behavior.
Principles
How we engage.
Evidence before reporting
Every reported issue is backed by technical evidence: code references, reproduction steps, runtime behavior, exploitability analysis, proof-of-concept work, reverse-engineering evidence, or fix validation where appropriate.
Direct senior collaboration
Clients work directly with experienced researchers who can reason with engineering teams, explain tradeoffs, and help prioritize fixes that reduce real risk.
Research translated into defense
The same research process that finds vulnerabilities helps teams improve architecture, threat models, secure design, detection ideas, and engineering practices.
AI with human judgment
Structured LLM workflows increase coverage and speed, but model output is never treated as a finding. Human researchers validate, reproduce, and assess impact.
Get Started
Bring us a hard target.
Tell us what you are building, what you are worried about, and we’ll take it from there.
Reach Out