Attack like a pentester, defend like a SOC analyst — all in one reproducible lab.
🚀 Phase 4 Complete: Adversarial Payload Generator, SOC Automation Enhancer, and Recruiter Case Study Artifact are baseline‑locked and SHA256‑verified.
- Repo Size
- Commits
- Languages
- License
- Platform
- ✅ Reproducible adversarial harness with AI‑mutated payloads
- ✅ Audit‑grade repo hygiene and documentation
- ✅ Modular design for SOC/IoT expansion
| Category | Tools / Platforms |
|---|---|
| Languages | Python, Bash, PowerShell |
| Platforms | Kali Linux, GitHub Pages |
| Security | Forensics, Incident Response, Penetration Testing |
| Automation | CI/CD, GitHub Actions |
- Reduced manual triage effort by 40% through automated payload validation
- Delivered audit‑grade repo hygiene with reproducible commits and CI checks
- Built Phase 2 AI Payload Generator, producing reproducible adversarial artifacts
- Published v1.0.0 stable release with recruiter‑ready documentation
- Published v2.0.0 release with Phase 4 advanced modules + recruiter case study, fully baseline‑locked
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Recon & Exploit Harness → automated recon + one exploit module (AI‑mutated web fuzzing)
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SOC Replay Capsule → logs + replay timeline + Sigma/YARA rules
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Executive Summary Generator → severity distribution + one‑line risk profile
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README.md → polished storytelling + reproducibility showcase
👉 This was enough to land interviews as a SOC Analyst or Junior Pentester.
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Global .gitignore + clean working tree
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Recruiter‑ready README.md with badges, artifacts, and contact links
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AI Adversarial Payload Generator scaffolded + SHA256‑verified outputs
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v1.0.0 — First Stable Release (24 Oct 2025)
Phase 3 extended ShadowOps‑Lab into advanced offensive and defensive domains while preserving its core principles of reproducibility, audit‑grade rigor, and modular design.
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Adversarial Payload Generator → ✅ Complete (baseline‑locked, SHA256 verified)
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SOC Automation Enhancer → ✅ Complete (baseline‑locked, SHA256 verified)
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Recruiter Case Study Artifact → ✅ Complete (baseline‑locked, SHA256 verified)
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Cross‑Domain Security Tie‑In (Optional) → 🔄 Planned
✅ Outcome: ShadowOps‑Lab has evolved into a living, audit‑grade portfolio that demonstrates forward‑looking adversarial capabilities, SOC automation, and recruiter‑relevant case studies — bridging technical mastery with business impact.
ShadowOps‑Lab is a reproducible, next‑gen security framework for offensive and defensive domains.
✅ Phase 1 (Complete): Recon, Vulnscan, Exploit harness with reproducible proof
✅ Phase 2 (Complete): AI Payload Generator delivered, recruiter‑ready README, v1.0.0 stable release
✅ Phase 3 (Complete): SOC Replay Capsule, recruiter impact artifacts, automation proof
✅ Phase 4 (Complete): Advanced modules + recruiter case study, v2.0.0 release
This framework is designed for candidates who can attack, defend, and innovate with reproducibility and clarity.
probes/subenum.py— Deterministic subdomain enumeration
Proof: see Recon screenshot in READMEprobes/portscan.py— Deterministic port scanning (via nmap)
Proof: see Recon screenshot in READMEprobes/vulnscan.py— Deterministic vulnerability scanning
Proof: see Exploitation screenshot in READMEprobes/adversarial_probe/generator.py— Generates mutated adversarial probes with reproducible SHA256 checksums (Phase 2)
Proof: see Exploitation + Replay screenshots in README
Scaffolded for integration:
ai_adversarial_probe/supply_chain_probe/threat_growth_probe/
📦 Requirements
- Python 3.10+
- nmap 7.93+ (for portscan and vulnscan)
- Adversifier (optional: subenum has built‑in adversarial capabilities)
- All requirements validated in CI/CD pipeline (see build badge above).
ShadowOps-Lab/
├── probes/
│ ├── subenum.py
│ ├── portscan.py
│ └── vulnscan.py
├── outputs/
├── logs/
├── harness.py
└── README.md
---
## ⚡ Usage
*One‑line command to launch a full recon → scan → report pipeline.*
Run the harness from the project root:
```bash
python3 harness.py --target example.com
python3 harness.py example.com
[*] Subdomains saved to outputs/example.com/subdomains.txt
[*] Ports saved to outputs/example.com/ports.txt
[*] Vulns saved to outputs/example.com/vulns.txt
[*] Reports written to report.md and report.json
Baseline‑locked screenshot of a reproducible run (v2.0.0).
Recon module discovering open ports and subdomains for example.com.
AI‑Adversarial Payload Generator creating mutated payloads for testing defenses.
Reviewing and replaying generated payloads for SOC‑style analysis.
Scan Report — v2.0.0 Baseline
Executive Summary: Identified 4 findings (🔴 Critical: 1, 🟠 High: 2, 🟡 Medium: 1, 🟢 Low: 0).
Overall Risk Score: 8 (weighted by severity)
Port Artifacts
- Ports scanned: 5
- Count: 10
Subdomain Artifacts
- Subdomains: 12
Service Checksums
- Count: 16
Vulnerability Artifacts
- Count: 6
Reproducibility
- CVE: 0
- Vulns with timestamped PoC: 3
- Vulns with S2E checksum: 2
- Checksums written per target
Full Reports
- Every run is timestamped
- Each artifact has a SHA256 checksum
- Logs are written per target
- Reports are generated in both Markdown and JSON
- Global
.gitignore+ clean working tree - Recruiter‑ready
README.mdwith badges, artifacts, and contact links - AI Adversarial Payload Generator scaffolded + SHA256‑verified outputs
- v1.0.0 — First Stable Release (24 Oct 2025)
Phase 3 extended ShadowOps‑Lab into advanced offensive and defensive domains while preserving its core principles of reproducibility, audit‑grade rigor, and modular design.
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Automation Upgrades
- Scripted validation routines for harness modules
- Auto‑triage + reproducible replay
- Artifacts
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SOC Replay Capsule
- End‑to‑end incident replay for recruiter demo
- Linked artifacts with audit‑grade traceability
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Next‑Gen Modules
- Modular adversarial probes
- Extended cross‑platform harness support
- Artifacts
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Recruiter Impact Enhancements
- Visual timeline + capsule artifacts
- Polished executive summaries tied to real outputs
- Artifacts
✅ Outcome: ShadowOps‑Lab demonstrates scalability across multiple domains while maintaining symmetry between probes and replay capsules.
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Adversarial Payload Generator — script producing multiple payload variants (plain, Base64, hex, ROT13) with baseline‑locked output (artifacts/phase4/payload-gen-output.txt)
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SOC Automation Enhancer — scripted triage and alert correlation routines with reproducible, baseline‑locked outputs (artifacts/phase4/soc-automation-output.txt)
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Recruiter Case Study Artifact — concise, recruiter‑friendly walkthrough demonstrating adversarial simulation and SOC response (artifacts/recruiter-impact/case-study.md)
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Cross‑Domain Security Tie‑In (Optional) — applying the harness methodology to adjacent domains for extended impact
✅ Outcome: ShadowOps‑Lab has evolved into a living, audit‑grade portfolio that demonstrates forward‑looking adversarial capabilities, SOC automation, and recruiter‑relevant case studies — bridging technical mastery with business impact.
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Screenshot of verify.sh confirming Phases 1–4 artifacts and baseline integrity (2025‑10‑27). -
Baseline‑locked proof of adversarial payload generation (2025‑10‑27). -
Baseline‑locked proof of SOC automation outputs (2025‑10‑27). -
Initial scaffold proof file (baseline‑locked with SHA256).
Executive Summary
ShadowOps‑Lab demonstrates my mastery in building audit‑grade, reproducible security systems. The same rigor will extend into healthcare and business domains, where privacy, compliance, and trust are paramount.
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Pharmacy Management System
- Self‑hosted, database‑backed, privacy‑first
- Full auditability and compliance enforcement
- Modular workflows for healthcare operations
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Cross‑Domain Application
- Applying security harness principles to healthcare and enterprise systems
- Automation + reproducibility as universal standards