Ali Murtaza Bhutto
MSc Cybersecurity (SZABIST, Sindh HEC Indigenous Scholar) who builds production security systems across OSINT, digital forensics, and applied AI. Work spans intelligence-acquisition pipelines, cryptographic chain-of-custody tooling, agentic multi-agent systems, and the frameworks that keep open-source intelligence defensible and lawful. Currently building a multi-framework compliance platform at Complai and deploying multi-agent systems at OWS (openworkforce.systems).
Experience
- Engineered scalable OSINT acquisition pipelines across a large and varied set of sources.
- Designed high-performance scraping systems in Python and Selenium with custom concurrency patterns.
- Operated containerised data pipelines on Docker and Linux with high availability.
- Applied regex parsing, deduplication, and real-time enrichment on large datasets under OSINT and GDPR compliance.
- Conducted security assessments against ISO 27001, NIST, and regional standards.
- Performed penetration testing and vulnerability assessments for enterprise clients.
- Led incident response and forensic investigations, with risk-rated technical reports and remediation plans.
- Conducted firmware security reviews and identified vulnerabilities in embedded systems.
- Developed and executed custom exploits to validate weaknesses, then verified patch effectiveness.
- Authored security documentation aligning product requirements with technical implementation.
Selected Projects and Research
Turns public-source intelligence into tamper-evident, audit-ready evidence: a SHA-256 forward-chained audit log, three independent attestation backends (local, GitHub, Sigstore Rekor), and a multi-agent OSINT pipeline across six LLM providers, with an optional SAT auditability trace. TypeScript, Next.js, Prisma. Live at forenix.tech.
Content-addressed, cryptographically signed claim graphs with a revocation waterfall for autonomous multi-agent systems. Python.
LangGraph ReAct agent over five read-only OSINT tools (WHOIS, DNS, Shodan InternetDB, GitHub dorks, Wayback) with a deterministic evidence ledger and a real 20-target benchmark.
Adversarial harness of 47 probes plus 8 jailbreaks mapped to the OWASP LLM Top 10 (2025), with a deterministic heuristic scorer and a runtime authorization gate.
Pre-deployment risk evaluation of LLM system prompts against the OWASP LLM Top 10, NIST AI RMF 1.0, and the EU AI Act, with a reproducible labelled eval (rules-only F1 0.96).
Retrieval-augmented CVE and threat-intel Q&A on Ollama, pgvector, and FastAPI, comparing three chunking strategies with MRR and answer-faithfulness evaluation.
osint-pipeline-demo (async OSINT collection), secure-python-pipeline-template (four-gate DevSecOps), threat-model-generator (STRIDE), dark-web-monitor-lite, osint-methodology-vault, meshtastic-security-audit, docker-osint-stack, firmware-analysis-walkthrough, credential-leak-scanner, sovereign-llm-quickstart, cursor-vibe-starter. Each carries an MIT licence, a CITATION.cff, and a resolving Zenodo DOI. Full list at github.com/thunderstornX.
Preprints
Master's-project preprints, self-archived on Zenodo.
- OSINT in Action: a comparative study of OSINT tools for social-media and network intelligence. DOI 10.5281/zenodo.16921792
- Navigating the Legal Labyrinth: a framework for ethical and compliant OSINT operations. DOI 10.5281/zenodo.16924934
- A Comprehensive Review of Meshtastic and Similar Networks: applications, security, and performance. DOI 10.5281/zenodo.16925037
Education
Skills
Certifications
CEH v13 (EC-Council) . Belkasoft Android and Windows Forensics . ISO/IEC 27001:2022 Information Security Associate . Certified Network Security Practitioner . Certified AppSec Practitioner v2 . Google Data Analytics and Business Intelligence . Stanford Machine Learning
Languages
English (professional). Urdu (native). Sindhi (native).