Hayula: The Complete Vision — Democratizing Cybersecurity AI on Commodity Hardware

We present Hayula, an integrated ecosystem for cybersecurity AI, multi-agent orchestration, and autonomous bug bounty operations—built entirely on a single Apple Mac Studio M2 Ultra workstation (192GB unified memory, $6,000 retail). The ecosystem comprises nine specialized 7B language models for security analysis, a hierarchical multi-agent framework with 21 agents across four functional divisions, an automated reconnaissance-to-submission pipeline targeting 23 HackerOne programs, and supporting infrastructure spanning bilingual Arabic-English AI, terminal tooling, and a custom Linux distribution. Over a two-week deployment, Hayula identified server-side request forgery vulnerabilities across five major technology companies (Amazon, Meta, Apple, MongoDB, Shopify), discovered exposed GraphQL endpoints, and produced verified HackerOne submissions with an estimated bounty value of $53,500–$198,000—all at \$0 cloud compute cost. This work demonstrates that specialized cybersecurity AI, previously accessible only through enterprise licenses costing $100,000+/year, can be built, trained, and operated on consumer hardware by a single researcher. We release all components under open source licenses (Apache 2.0, CC0, MIT) as the Hayula ecosystem at https://huggingface.co/BinSaqban and https://github.com/HayulaLab.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-24
DOI
https://doi.org/10.5281/zenodo.21537044
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Hayula: The Complete Vision — Democratizing Cybersecurity AI on Commodity Hardware

Yahya Saqban
Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
article

Hayula: The Complete Vision — Democratizing Cybersecurity AI on Commodity Hardware

Yahya Saqban
article en

Abstract

We present Hayula, an integrated ecosystem for cybersecurity AI, multi-agent orchestration, and autonomous bug bounty operations—built entirely on a single Apple Mac Studio M2 Ultra workstation (192GB unified memory, $6,000 retail). The ecosystem comprises nine specialized 7B language models for security analysis, a hierarchical multi-agent framework with 21 agents across four functional divisions, an automated reconnaissance-to-submission pipeline targeting 23 HackerOne programs, and supporting infrastructure spanning bilingual Arabic-English AI, terminal tooling, and a custom Linux distribution. Over a two-week deployment, Hayula identified server-side request forgery vulnerabilities across five major technology companies (Amazon, Meta, Apple, MongoDB, Shopify), discovered exposed GraphQL endpoints, and produced verified HackerOne submissions with an estimated bounty value of $53,500–$198,000—all at \$0 cloud compute cost. This work demonstrates that specialized cybersecurity AI, previously accessible only through enterprise licenses costing $100,000+/year, can be built, trained, and operated on consumer hardware by a single researcher. We release all components under open source licenses (Apache 2.0, CC0, MIT) as the Hayula ecosystem at https://huggingface.co/BinSaqban and https://github.com/HayulaLab.

Zenodo (CERN European Organization for Nuclear Research)
Tula University (RU)
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Adversarial Robustness in Machine Learning
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