Skip to content
View huzorobi's full-sized avatar
💭
Building HuzoHunter AI 🚀
💭
Building HuzoHunter AI 🚀

Block or report huzorobi

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
huzorobi/README.md
Typing SVG

Founder and penetration tester  •  AI-assisted offensive security  •  Manchester, UK 🔐

NullCadre Website LinkedIn Email
Profile views

🧠 About Me

name: Robert Huzo
role: Founder and lead penetration tester, HuzoSecurity Ltd
building: NullCadre, an AI-assisted penetration testing and bug-hunting platform
also: HuzoHunter AI, a local-first defensive threat-hunting platform
principle: The engine proves the facts. The AI reasons about them. The model never decides whether a bug exists.
focus: Web and API testing · Authorisation (BOLA/IDOR/BFLA) · LLM application security · Security automation
certs: CompTIA Security+ · CompTIA A+ · EC-Council CEH (5-day hands-on training)
bounty: HackerOne · Bugcrowd · Intigriti · YesWeHack · WordFence
  • 🛰️  Building and running NullCadre, used daily on authorised engagements and bug bounty targets
  • 🛡️  Building HuzoHunter AI, the defensive counterpart, for organisations that can't ship telemetry to a cloud vendor
  • 📄  Read a full worked assessment with the evidence behind every finding
  • 🎓  BSc Cyber Security, Solent University (in progress) · NVIDIA Inception member
  • 💬  Ask me about authorisation testing, LLM attack surfaces, and running AI models locally
  • 📫  Reach me at robert@huzosecurity.com or via huzosecurity.com

🚀 Featured Project

🛰️ NullCadre

AI-assisted penetration testing and bug-hunting platform

Live, and exercised daily against authorised targets and known-answer benchmarks.

Deterministic-first · Fail-closed scope gate · Local AI only · Under 5% false positives

flowchart LR
    T["🎯 Authorised<br/>target"] --> G{{"🚦 Scope gate<br/><code>scope.gate.validate()</code><br/><i>fail closed, in code</i>"}}
    G -->|"out of scope"| X["⛔ Refused<br/><i>no packet leaves</i>"]
    G -->|"in scope"| D["🔬 Deterministic battery<br/>526 modules, exhaustive"]
    D --> E[("📊 Evidence<br/><i>graded, structured</i>")]
    E --> H["🧠 Hunter · local LLM<br/>observation → hypothesis<br/>→ probe → pivot"]
    H -->|"new leads"| G
    E --> V{{"✅ Confirmed out of band<br/><i>working proof of concept</i>"}}
    V -->|"could not run"| N["⚠️ NOT TESTED<br/><i>with the reason</i>"]
    V -->|"proven"| R["📄 Report · 8 formats"]
    N --> R

    style G fill:#7c3aed,stroke:#5b21b6,color:#fff
    style X fill:#dc2626,stroke:#991b1b,color:#fff
    style H fill:#be123c,stroke:#9f1239,color:#fff
    style N fill:#d97706,stroke:#b45309,color:#fff
    style E fill:#0891b2,stroke:#0e7490,color:#fff
Loading

The engine proves the facts. The model reasons about them. The Hunter can only add to the baseline, never reduce it, and every lead it proposes goes back through the same gate.

How it works

  • A deterministic battery runs first, every applicable detector, exhaustively. Each finding carries structured evidence and a grade.
  • An operator-enabled Hunter (a local LLM) then takes those findings as its starting knowledge and builds a real attack chain: observation, hypothesis, probe, pivot, evidence. It can only add to the baseline, never reduce it, and CI tests assert that on every build.
  • Every action, from recon to confirmation, passes a fail-closed scope gate enforced in code (scope.gate.validate()) before a packet leaves. No prompt-based trust, no bypass, no trusted mode.
  • Criticals are confirmed out of band with a working proof of concept. Anything that could not run is reported as NOT TESTED, with the reason, never as a clean result.

Numbers

  • Under 5% false-positive rate, measured across several public vulnerable applications, a published authorisation-testing benchmark, and a fully patched self-hosted target where the correct answer is nothing found
  • 526 integrated scanner and tool modules · 156 Hunter actions · 8 report formats (HTML, PDF, Markdown, CSV, JSON, SARIF, OCSF, executive one-pager)
  • Runs entirely on the operator's estate. No target data leaves the machine, including for report narration.
🎯 What it covers  click to expand

Recon and attack surface mapping · injection classes confirmed out of band (SSRF, SSTI, XXE, SQLi, command injection, request smuggling, cache poisoning) · a two- and three-account BOLA/IDOR/BFLA engine with a third-account control to kill the classic false positives · JWT, SAML, OAuth and session attacks · race conditions and TOCTOU (single-packet) · business-logic abuse · secrets and exposure · cloud and container posture · Active Directory attack paths · WordPress and Drupal read-only assessment · LLM application security (prompt injection, sandbox escape, authorisation boundaries, exposed AI endpoints and MCP servers)

Nothing runs out of scope.

Principles

Report impact, not observations. Absence of evidence is not evidence of absence. Never say "fixed"; the strongest honest claim is "not rediscovered". Confirm, don't weaponise: no persistence, no credential dumping, nothing destructive.

🔒 The core repository is private and proprietary to HuzoSecurity Ltd. The platform runs behind a HuzoSecurity engagement; it is not sold or licensed.


🛡️ Also Building

🤖 HuzoHunter AI

Local-first threat hunting and security automation

The defensive counterpart to NullCadre. Explainable investigations, with sensitive data staying fully under your control.

Local AI · Threat Hunting Automation · Explainable Investigations · M365 + Active Directory Integration


🛠️ Tech & Tools

Python Kali Linux Bash Docker

Burp Suite OWASP ZAP Nuclei BloodHound

Local LLMs NVIDIA Wazuh MITRE ATT&CK


📊 GitHub Stats

GitHub Stats Top Languages
GitHub Streak

🤝 Let's connect

NullCadre Website LinkedIn Email

Authorised testing only. Testing without written permission is an offence under the Computer Misuse Act 1990.


Last updated 2026-10-04 · Building NullCadre 🛰️ & HuzoHunter AI 🔐

Popular repositories Loading

  1. huzorobi huzorobi Public

    Cyber Security, AI Safety, Threat Hunting & Security Automation

    2

  2. curl2spec curl2spec Public

    Turn a browser Copy-as-cURL of a login/signup into a ready-to-use multi-account auth test spec for BOLA/IDOR and BFLA (A owns the data, B attacks, optional admin for function-level authz). Manual m…

    Python 2

  3. weft weft Public

    Free-source OSINT reconnaissance aggregator: weaves open public sources into one entity graph, with a local-AI report narrator and identity assessment (local-only, grounded). Authorised reconnaissa…

    Python 2

  4. nullcadre-research nullcadre-research Public

    The research and engineering method behind NullCadre, a 526-module platform for authorised penetration testing: 237 books and papers, 637 external sources, 16 specifications read in the original, 1…

    2