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Ahmed Mahmoud
Ahmed Mahmoud Cairo · Egypt
Open to Work

Ahmed
Mahmoud

Jr. Penetration Tester Building systems that think like attackers
and detect threats before they land.

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9+Projects
3+Internships
4Certs
01

About Me

I'm Ahmed Mahmoud, a penetration tester focused on offensive security, vulnerability research, and security engineering.

My work spans web, API, and network penetration testing, with a strong interest in identifying exploitable weaknesses, analyzing attack paths, and understanding how real-world systems can be broken and defended. I'm also active in bug bounty hunting, with a focus on vulnerabilities such as IDOR, SSRF, authentication bypass, broken access control, and business logic flaws.

Alongside offensive security, I build cybersecurity projects that apply AI, machine learning, and deep learning to network traffic analysis, anomaly detection, and threat monitoring, including detection and response workflows for enterprise and industrial environments.

I'm currently studying Network & Cybersecurity at Elsewedy University of Technology, while continuously sharpening my skills through hands-on labs, applied security research, technical writing, and real-world cybersecurity projects.

Web Penetration TestingAPI Security Network Penetration TestingDigital Forensics ML-Based Threat DetectionBug Bounty Hunting Vulnerability ResearchICS/OT Security
Download CV
whoami.json
name"Ahmed Mahmoud"
role"Penetration Tester"
focus"Offensive Sec + AI"
edu"SUT — Egypt"
status"open_to_work"
02

Where I've Worked

Dec 2024 – Present ● Active
Bug Hunter
HackerOne

Hunting vulnerabilities across public and private programs — IDOR, XSS, SSRF, auth bypass, and business logic flaws. Chaining attack paths to demonstrate real-world impact beyond surface-level findings.

Burp SuiteffufnucleiSQLMapOWASP ZAP
Nov 2025 – Present ● Active
Machine Learning Intern
DEPI — Digital Egypt Pioneers

Training ML models for cybersecurity — classification, anomaly detection, and sequence models applied to network traffic analysis. Building real-time threat scoring pipelines.

TensorFlowPyTorchscikit-learnSHAPPandas
Oct 2025 – Mar 2026 Internship
Information Security Intern
Cyberthos · Remote

Gained hands-on experience in digital forensics, SOC operations, and penetration testing. Analyzed network traffic and system logs to detect malicious activity using Wireshark and Splunk. Performed vulnerability assessments and basic exploitation with Metasploit Framework, and worked on network security simulations using GNS3 while applying security best practices aligned with NIST frameworks.

SplunkWiresharkMetasploitGNS3NIST
Sep – Nov 2025 Internship
Microsoft Summer Camp
Sprints

Microsoft-backed program on cloud security and DevSecOps — Azure security services, cloud-native threat monitoring, and secure pipeline practices.

AzureDevSecOpsSentinel
Aug – Sep 2025 Training
Cybersecurity Training
NTI

Hands-on training covering vulnerability scanning, web app security, cloud security, and SIEM operations with enterprise-grade tooling at Smart Village.

NessusOpenVASSplunkELKWPScan
03

Technical Stack

Offensive Security
Web App PentestingNetwork PentestingAPI Security Testing Bug Bounty HuntingVulnerability AssessmentIDOR & Logic Flaws SQL Injection (SQLi)Cross-Site Scripting (XSS)SSRF
AI / ML Security
Anomaly DetectionTraffic ClassificationThreat Detection Systems Network Traffic AnalysisSHAP ExplainabilityTensorFlow PyTorchscikit-learnLightGBMXGBoost Random ForestAutoencodersPandasNumPy MatplotlibStreamlit
Recon & Tooling
Burp SuiteNucleiffufKatana AmassSubfinderhttpxNaabu SQLMapMetasploitNmapWiresharkSuricata
Languages & Dev
PythonBashJavaScriptPHP JavaHTML5CSS3Flask LaravelNode.js
Infrastructure & Cloud
DockerAWSGoogle Cloud ApacheNginxKali Linux
04

What I've Built

ot-sentinel-ai.app
OT Sentinel AI dashboard — real-time ICS/OT network monitoring
01 — Featured

AI-powered Network Detection & Response platform for Industrial Control Systems (ICS/OT) — real-time traffic monitoring with centralized threat visibility.

  • Hybrid detection pipeline: XGBoost for known attacks + Autoencoder for zero-day anomalies
  • Fusion engine with risk scoring to prioritize alerts and cut analyst noise
  • Validated on a realistic ICS lab (GRFICSv3 + Modbus TCP) — not just a synthetic dataset
  • Owned the full AI detection pipeline: feature engineering → model dev → inference API integration

Designed to solve a core OT security challenge — limited visibility into industrial traffic and the difficulty of detecting both signature-based attacks and unknown threats — the system combines a hybrid detection pipeline using XGBoost for known attack classification and an Autoencoder for zero-day anomaly detection, with a Fusion Engine and risk scoring layer to prioritize alerts and improve response accuracy.

Built and validated in a realistic ICS lab environment based on GRFICSv3 and Modbus TCP traffic, supporting real-time monitoring, threat analysis, alerting, asset visibility, and operator-focused security monitoring for industrial networks. My contribution focused on the AI Detection Pipeline — feature engineering, XGBoost and Autoencoder model development, fusion and risk scoring logic, and integrating the AI inference workflow into the platform's detection API.

ReactTypeScriptFastAPIDockerPostgreSQLTensorFlowAutoencoderXGBoostOpenPLCGRFICSv3Modbus TCP
🤖 AI/ML · Network
Botnet Detection — Furssah AI

Hybrid ensemble (LightGBM + XGBoost + Isolation Forest + DBSCAN) with BiLSTM + GRU + Attention for sequential analysis and SHAP explainability.

LightGBMXGBoostBiLSTMSHAP
Network Traffic Forensics IDS

Real-time IDS combining Suricata + XGBoost on CIC-IDS datasets, Zeek enrichment, and a live Streamlit alert dashboard.

XGBoostSuricataZeekStreamlit
Custom Firewall + Rules Manager

Linux iptables firewall with dynamic IP/port/protocol blocking, persistent SQLite logging, real-time stats, and an interactive CLI.

BashPythoniptablesSQLite
IoT Wi-Fi Honeypot — Evil Twin

ESP32 honeypot studying real IoT behaviour under Evil Twin attacks, with Flask logging server and Chart.js analytics dashboard.

ESP32CFlaskChart.js
SecureMerge — M&A Cyber Risk GRC

End-to-end GRC framework for M&A cyber risk: due diligence → quantitative scoring → integration decision → post-merger governance tracking.

GRCRisk ScoringGovernance
Campus Net Compiler — Infrastructure-as-Code Network Automation Platform

Infrastructure-as-Code platform that transforms YAML campus blueprints into automated enterprise network deployments, including topology generation, router and switch configurations, security policy enforcement, validation workflows, and fully orchestrated GNS3 environments.

PythonGNS3NetmikoFlaskJinja2NetworkX
AI-Powered Deepfake & Image Forensics

Hybrid AI and digital forensics platform designed to detect deepfakes, AI-generated images, and manipulated media using ensemble machine learning models, forensic signal analysis, and evidence-driven reporting. Combines deepfake detection, tampering analysis, compression artifact inspection, and authenticity scoring into a unified forensic workflow with real-time dashboard visualization and automated report generation.

PythonOpenCVStreamlit
ReconBrain

Adaptive reconnaissance orchestration platform that correlates recon data into prioritised attack chains, automated risk scoring, and intelligent exploitation paths for web security assessments.

PythonSQLiteAsyncIONucleiGraphQLscikit-learnSHAPReportLab
05

Education

Elsewedy University of Technology — Polytechnic of Egypt
Bachelor of Engineering Technology, Network and Cybersecurity
Oct 2023 — 2027
07

Let's Connect

Looking to collaborate on security research, or AI-driven detection? Open to internships, freelance work, and research partnerships.

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