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nishu2402/README.md
Typing SVG



     




[ 01 ]SYSTEM PROFILE: WHOAMI

┌──(HEAVEN㉿kali-offensive)-[~]
└─$ sudo cat /root/.profile

╔══════════════════════════════════════════════════════════════════════════╗
║                                                                          ║
║    ███╗   ██╗██╗███████╗ █████╗ ██████╗  ██████╗                        ║
║    ████╗  ██║██║██╔════╝██╔══██╗██╔══██╗██╔════╝                        ║
║    ██╔██╗ ██║██║███████╗███████║██████╔╝██║  ███╗                       ║
║    ██║╚██╗██║██║╚════██║██╔══██║██╔══██╗██║   ██║                       ║
║    ██║ ╚████║██║███████║██║  ██║██║  ██║╚██████╔╝                       ║
║    ╚═╝  ╚═══╝╚═╝╚══════╝╚═╝  ╚═╝╚═╝  ╚═╝ ╚═════╝                       ║
║                                                                          ║
║  >> ALIAS     :  HEAVEN                                                  ║
║  >> IDENTITY  :  Nisarg Chasmawala                                       ║
║  >> ROLE      :  Offensive Security Engineer | Penetration Tester        ║
║  >> LOCATION  :  England, United Kingdom                                 ║
║  >> EDUCATION :  MSc Cyber Security — Birmingham City University         ║
║                  (Expected Graduation: March 2027)                       ║
║                                                                          ║
║  >> CERTS     :  CPENT | CEH Master | CHFI | ISO 27001 Lead Auditor      ║
║                  CEH v13 | EHE (96%) | CRTOM | CTIGA | CCEP | CCPP      ║
║                  Foundations of Log Analysis | TOEFL iBT 91/120          ║
║                                                                          ║
║  >> WEAPONS   :  Metasploit · Burp Suite · Nessus · Maltego              ║
║                  Wireshark · Autopsy · FTK Imager · MITRE ATT&CK         ║
║                  TensorFlow · XGBoost · NetworkX · AWS IAM               ║
║                                                                          ║
║  >> ML WINS   :  DDoS Detection    — 99.99% Accuracy | 1.0000 Precision  ║
║                  Malware Engine    — 98.47% F1-Score | Near-Perfect AUC  ║
║                  CVSS Prediction   — R² = 0.9989     | 337,705 CVEs     ║
║                                                                          ║
║  >> MISSION   :  Uncover vulnerabilities. Secure critical systems.       ║
║                  Shape international cyberspace policy.                  ║
║                  Build a safer digital world — one exploit at a time.    ║
║                                                                          ║
║  [STATUS]  ████████████████████████████████  ACTIVE — ALWAYS HUNTING     ║
╚══════════════════════════════════════════════════════════════════════════╝

[HEAVEN@offensive-sec ~]$ _

[ 02 ] ⚔️ ATTACK SURFACE: SKILLS MATRIX

— CORE LANGUAGES & PLATFORMS —

— AI & MACHINE LEARNING ARSENAL —

— OPERATING SYSTEMS —


┌──(HEAVEN㉿kali-offensive)-[~/os-arsenal]
└─$ uname -a --all-platforms

  [+] macOS              ............... Daily Driver
  [+] Kali Linux         ............... Primary Offensive Platform
  [+] Parrot OS          ............... Alternate Offensive Platform
  [+] Ubuntu / Debian    ............... Server & Dev Environments
  [+] Windows 10 / 11    ............... Target Simulation & Forensics
  [+] iOS / Android      ............... Mobile Security Research

— CYBERSECURITY TOOLS MATRIX —

⚔️ Exploitation 🔍 Recon & OSINT 🧪 Digital Forensics ☁️ Vuln Management
Metasploit Advanced Nmap / Netcat Advanced Autopsy Advanced Nessus Advanced
Burp Suite Advanced OSINT Framework Advanced FTK Imager Advanced OpenVAS Advanced
SQLmap Advanced Maltego Advanced Magnet AXIOM Advanced AWS IAM Advanced
Hydra Advanced Wireshark Advanced Magnet DVR Examiner Advanced MITRE ATT&CK Advanced
John the Ripper Advanced Shodan Advanced MOBILeadit Advanced NetworkX Advanced
Aircrack-ng Advanced Nikto / Acunetix Advanced Passware Kit Advanced CVSS Scoring Advanced
Ghidra (RE) Very Good Snort Very Good Volatility Advanced ISO 27001 Audit Certified

[ 03 ] 🚀 REAL-WORLD PROJECTS: ZERO-DAY TO DEPLOY


PROJECT 01 — AEGIS-IAM DASHBOARD

Cloud Security & Risk Intelligence Platform

Repo

╔─ MISSION BRIEF ──────────────────────────────────────────────────────────╗
  THREAT VECTOR  : AWS Cloud IAM Over-Privilege & Privilege Escalation
  TECH STACK     : Python · NetworkX · MITRE ATT&CK · AWS JSON · OWASP
  KEY RESULT     : Automated detection of assume-role chaining & SoD conflicts
  COMPLIANCE     : OWASP-compliant data validation + vector-based risk reports
╚──────────────────────────────────────────────────────────────────────────╝

Architected a Python IAM risk analysis platform ingesting AWS JSON exports, auto-detecting over-privileged cloud identities and mapping privilege escalation paths via graph-based detection (NetworkX). Integrated MITRE ATT&CK tactic/technique categorisation with a dynamic CLI patch command pipeline and automated, vector-based risk intelligence reporting.


PROJECT 02 — ANDROID MALWARE DETECTION SYSTEM

ML-Powered Mobile Threat Engine — 98.47% F1-Score

Repo

╔─ MISSION BRIEF ──────────────────────────────────────────────────────────╗
  THREAT VECTOR  : Android APK Permissions & API Call Static Analysis
  TECH STACK     : Python · Scikit-Learn · XGBoost · Drebin (15,000+ records)
  KEY RESULT     : 98.47% F1-Score · Near-perfect ROC-AUC
  INNOVATION     : Behaviour-based detection replacing signature scanning
╚──────────────────────────────────────────────────────────────────────────╝

Engineered enterprise-grade Android malware pipeline evaluating L1 Regularisation, Chi-Square extraction and Random Forest feature importance on the Drebin dataset. Trained XGBoost, RF, Logistic Regression & KNN to transition from signature-based to behaviour-based threat identification at production scale.


PROJECT 03 — AI-POWERED DDoS DETECTION SYSTEM

NIDS with Deep Learning — 1.0000 Precision · 99.99% Accuracy

Repo

╔─ MISSION BRIEF ──────────────────────────────────────────────────────────╗
  THREAT VECTOR  : Volumetric DDoS Network Intrusion Classification
  TECH STACK     : Python · TensorFlow · XGBoost · CIC-DDoS2019 (225K+ rows)
  KEY RESULT     : 1.0000 Precision · 99.99% Accuracy · ZERO false positives
  MODELS TESTED  : 1D-CNNs · MLPs · XGBoost · Random Forest
╚──────────────────────────────────────────────────────────────────────────╝

Built an AI-driven NIDS on the CIC-DDoS2019 dataset with robust preprocessing handling severe class imbalance. XGBoost achieved a flawless 1.0000 precision — zero false-positive alerts for security analysts while maintaining near-perfect recall for all active volumetric attack vectors.


PROJECT 04 — PREDICTIVE CVSS VULNERABILITY SCORING PIPELINE

ML Threat Assessment — R² = 0.9989 · 337,705 CVE Records

Repo

╔─ MISSION BRIEF ──────────────────────────────────────────────────────────╗
  THREAT VECTOR  : Automated NVD Severity Assessment via ML Regression
  TECH STACK     : Python · Scikit-Learn · Gradient Boosting · NVD Dataset
  DATASET        : 337,705 historical CVE records (National Vuln. Database)
  KEY RESULT     : R² = 0.9989 (Gradient Boosting) · Near-perfect accuracy
  FEATURE SELECT : Pearson · Mutual Info · Chi-Square · F-Regression · RFE
╚──────────────────────────────────────────────────────────────────────────╝

Engineered a supervised ML pipeline to automate NVD severity assessments, predicting CVSS Base Scores across 337,705 historical CVE records. Processed vulnerability metadata features (attack-type flags, impact, exploitability scores) via 5 feature selection methods isolating 13 optimal predictors. Trained Gradient Boosting, Random Forest, Decision Tree & Linear Regression models — Gradient Boosting achieved near-perfect R² = 0.9989 validated through MAE, RMSE, R² and 5-fold cross-validation for enterprise patch prioritisation.


PROJECT 05 — ADAPTIVE VULNERABILITY RISK SCORING

AI-Driven Real-Time Threat Assessment — Beyond Static CVSS

Repo

╔─ MISSION BRIEF ──────────────────────────────────────────────────────────╗
  THREAT VECTOR  : Dynamic CVSS Replacement — Context-Aware Risk Scoring
  TECH STACK     : Python · Scikit-Learn · XGBoost · Feature Engineering
  KEY RESULT     : Real-time 0–10 context risk scores · MSE/RMSE/MAE/R² val.
  INNOVATION     : TCP flags · port categories · protocol features as inputs
╚──────────────────────────────────────────────────────────────────────────╝

Designed an adaptive ML framework transitioning vulnerability assessments from static CVSS to real-time, context-aware scoring. Processed raw network traffic features (TCP flags, port categories, protocols) via One-Hot Encoding and feature engineering. Evaluated XGBoost, RF, Decision Tree & KNN; validated with MSE, RMSE, MAE and R² for enterprise threat response prioritisation at scale.


[ 04 ] 🏅 CERTIFICATIONS: BATTLE RIBBONS

🏅 Certification Issuer Date Score / Credential
☠️ CPENT — Certified Penetration Tester Professional EC-Council 2024-11 ECC6970842153
☠️ CEH Master — Certified Ethical Hacker Master EC-Council 2024-04 ECC1382059467
☠️ CEH Practical EC-Council 2024-04 180/200 · ECC7804965321
☠️ CEH v13 — Certified Ethical Hacker EC-Council 2025-12 ID 776964
☠️ CEH — Certified Ethical Hacker EC-Council 2024-01 91.2% · ECC5081642397
☠️ CHFI — Computer Hacking Forensic Investigator EC-Council 2023-12 90.7% · ECC4925367081
🔒 ISO/IEC 27001:2022 Lead Auditor Mastermind 2026-01 ttuf1fci7e
🔒 EHE — Ethical Hacker Essentials EC-Council 2026-01 96% · ECC8416329075
🔴 CRTOM — Certified Red Team Operations Management Red Team Leaders 2026-01
🔴 CTIGA — Threat Intelligence & Governance Analyst Red Team Leaders 2026-01
🔴 CCEP — Certified Cybersecurity Educator Professional Red Team Leaders 2026-01
🔴 CCPP — Certified C++ Practitioner Red Team Leaders 2026-01
🔴 Foundations of Log Analysis for Cyber Defense Red Team Leaders 2026-01
📄 TOEFL iBT ETS 2024-07 91 / 120

[ 05 ] 💼 FIELD OPERATIONS: EXPERIENCE LOG

╔════════════════════════════════════════════════════════════════════════╗
║  TIMELINE                                                              ║
╠════════════════════════════════════════════════════════════════════════╣
║                                                                        ║
║  [2025-03 → 2025-09]  IT HARDWARE SUPPORT ENGINEER                    ║
║                        NIVA TECHNO TRANSITION, Surat, India           ║
║                        ▸ Enterprise system installation & maintenance  ║
║                        ▸ Hardware, software & network diagnostics      ║
║                        ▸ LAN/Wi-Fi & peripheral management            ║
║                        ▸ Regular security checks & offsite support     ║
║                                                                        ║
║  [2024-02 → 2025-02]  VULNERABILITY ASSESSMENT & PENETRATION TESTER   ║
║                        SYSAP TECHNOLOGIES, Pune, India (Remote)       ║
║                        ▸ Full-scope enterprise penetration tests       ║
║                        ▸ Executive + technical risk report delivery    ║
║                        ▸ Vulnerability remediation & hardening        ║
║                        ▸ Maintained currency with emerging threats     ║
║                                                                        ║
║  [2023-07 → 2024-01]  VULNERABILITY SCANNING & PEN TEST INTERN        ║
║                        SYSAP TECHNOLOGIES, Pune, India                ║
║                        ▸ Security & vulnerability scanning            ║
║                        ▸ Exploitation, threat intel & compliance docs  ║
║                        ▸ Security research & record keeping           ║
║                                                                        ║
║  [2023-01 → 2023-04]  NETWORK SPECIALIST INTERN                       ║
║                        AIRLINK COMMUNICATION PVT. LTD, Surat          ║
║                        ▸ Network troubleshooting & monitoring          ║
║                        ▸ Network configuration & documentation         ║
║                                                                        ║
║  [2022-06 → 2022-07]  NETWORK ENGINEER INTERN                         ║
║                        NIVA TECHNO TRANSITION, Surat                  ║
║                        ▸ Network infrastructure & structured cabling   ║
║                        ▸ Documentation, reporting & customer support   ║
║                                                                        ║
╚════════════════════════════════════════════════════════════════════════╝

[ 06 ] 🎓 MSc MISSIONS: ACADEMIC PROJECTS — BCU

🔴 [CLASSIFIED-10] Consolidated Pentesting & RCE Assessment

Conducted end-to-end penetration testing across Redis, Openfire, and Gitea environments. Achieved system-level access via Redis replication abuse, Openfire admin console exploitation, and Git Hooks weaponization. CVSS scores up to 10.0 Critical.

Nmap · Metasploit · Redis Exploit · Git Hooks · Reverse Shells · CVSS

🔵 [CLASSIFIED-10] Digital Forensic Strategy — Missing Person Investigation

Designed an ISO-aligned forensic investigation plan covering corporate systems, mobile devices, IoT, cloud platforms & CCTV. Applied ISO 27037/27035/27042/27043/17025 with full UK GDPR, NPCC & FSR compliance and chain-of-custody management.

FTK Imager · Magnet AXIOM · Magnet DVR Examiner · MOBILeadit · Autopsy · Passware Kit

🟡 [CLASSIFIED-10] Strategic Security Audit — Cyberzone AI Ltd.

Led ISO/IEC 27001:2023 audit of AI-driven healthcare & fintech systems. Identified identity gaps, patching weaknesses & source code exposure. Evaluated compliance with UK GDPR, Data Protection Act 2018, and US HIPAA. Proposed FIDO2 MFA, immutable backups, automated patching & Purple Team exercises. Delivered full risk-scored audit report + phased mitigation roadmap.

🟣 [CLASSIFIED-10] AI & Autonomous Pentesting Frameworks — Research

Systematic literature review evaluating Deep Reinforcement Learning & LLMs for autonomous offensive cybersecurity. Synthesized quantitative performance metrics assessing architectural evolution from single-agent LLMs to collaborative Multi-Agent Systems (MAS). Identified the "Sim2Real" transfer gap, algorithmic hallucination risks and dual-use ethical concerns. Formulated a Neuro-Symbolic AI + HITL architecture for EU AI Act & GDPR compliance.

DRL · LLMs · Multi-Agent Systems · Neuro-Symbolic AI · EU AI Act · GDPR

🟢 [CLASSIFIED-10] IT Project Management: Autonomous AI-Driven Pentesting

Orchestrated a 7-week Hybrid Agile-PRINCE2 project for an autonomous AI cybersecurity system using Monday.com as the Work OS. Managed a 5-phase WBS, sprint execution, capacity planning & automated approvals. Led EU AI Act compliance deliverables under crisis resource reallocation with HITL + Neuro-Symbolic safety guardrails.

Monday.com · Agile-PRINCE2 · WBS · Risk Management · Regulatory Compliance


[ 07 ] 🏢 INTEL BRIEFINGS: VIRTUAL JOB SIMULATIONS 2025

🏢 Organisation 🎯 Operation 🔑 Skills Demonstrated
Deloitte Cyber Job Simulation Threat Analysis · Incident Reports · Mitigation
MasterCard Cybersecurity Job Simulation Payment Security · Fraud Detection · Risk Response
Commonwealth Bank Intro to Cybersecurity Risk Management · Access Control · Data Protection
Telstra Cybersecurity Job Simulation Network Security · Vulnerability Identification
Datacom Cyber Security Operations SOC · Log Analysis · Anomaly Detection
TATA Cybersecurity Analyst Simulation System Scanning · Vuln Prioritisation
AIG Shields Up: Cybersecurity Cyber Defence · Attack Scenarios · Safeguards

[ 08 ] 🎓 EDUCATION: TRAINING GROUND

🎓 Degree 🏛️ Institution 📅 📊
MSc Cyber Security with Professional Placement Birmingham City University, UK Exp. 2027
BE — Computer Science & Engineering SN Patel Institute of Technology (GTU), India 2024 7.86 CGPA
Diploma — Computer Engineering N.G. Patel Polytechnic College (GTU), India 2021 7.80 CGPA
Class 10 — SSC (CBSE) Kendriya Vidyalaya No.1, Surat 2017

[ 09 ] 🌍 SYSTEM LANGUAGES

   

[ 10 ] 💀 SIDE MISSIONS: HOBBIES

┌──(HEAVEN㉿kali-offensive)-[~/hobbies]
└─$ cat interests.txt

  [+] CTF CHALLENGES    ............... Ethical Hacking Research & Capture-the-Flag
  [+] APPLE ECOSYSTEM   ............... Hardware/Software Troubleshooting & Emerging Tech
  [+] MOBILE SECURITY   ............... iOS & Android Security Research
  [+] CULINARY HACKS    ............... Experimenting with Varied Cuisines & Cooking

[ 11 ] 🎯 MISSION OBJECTIVES: CAREER GOALS

#!/usr/bin/env python3
# CLASSIFICATION: TOP SECRET — CAREER INTELLIGENCE BRIEF

class NisargChasmawala_MissionPlan:

    short_term_objectives = [
        "Earn OSCP, CISSP — push elite certification stack further",
        "Build AI-augmented security pipelines for enterprise defence",
        "Deepen red team operations experience with real engagements",
    ]

    mid_term_objectives = [
        "Publish peer-reviewed research at intersection of AI + Cyber",
        "Lead offensive security teams & mentor the next generation",
        "Pioneer autonomous penetration testing methodologies",
    ]

    long_term_objectives = [
        "Become a globally recognised cybersecurity adviser",
        "Lead development of next-generation security tools & frameworks",
        "Shape international cyberspace policy & best practices",
    ]

    ultimate_mission: str = """
        Uncover every vulnerability. Secure every critical system.
        Build a demonstrably safer digital world — for everyone.
    """

    def execute(self) -> None:
        while True:
            hunt(); learn(); build(); secure(); repeat()

[ 12 ] 📈 RECONNAISSANCE: LIVE ACTIVITY GRAPH


[ 13 ] 🐍 CONTRIBUTION SNAKE — LIVE FEED

github contribution grid snake animation



SELECT * FROM elite_security_engineers
WHERE alias     = 'HEAVEN'
  AND name      = 'Nisarg Chasmawala'
  AND certs     IN ('CPENT','CEH_Master','CHFI','ISO_27001','CEH_v13')
  AND location  = 'Birmingham, England, United Kingdom'
  AND status    = 'ACTIVE'
  AND mission   = 'MAKING_DIGITAL_WORLD_SAFER';

-- 1 row returned. Target identified. ☠

GitHub   LinkedIn   Email


[ ALL SYSTEMS SECURED — CONNECTION TERMINATED — ☠ ]

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