Shubham bilgi

Cyber Security Intern

Cybersecurity
1roles
20skills
2education
4credentials

About

Cybersecurity practitioner with hands-on experience in web application security assessments, vulnerability analysis, security reporting, and security automation. Experienced with Burp Suite, Wireshark, Nmap, OWASP Top 10 testing methodologies, and Python-based security tools.

Experience

Cyber Security Intern

SpringUp Labs

April 2025 – July 2025 · Pune

Conducted security assessments on 5 production web applications for SQL Injection, Cross-Site Scripting, authentication, and access control vulnerabilities. Used Burp Suite, Nmap, Gobuster, and Wireshark for enumeration, traffic analysis, vulnerability validation, and security testing. Prepared vulnerability assessment reports with proof-of-concept findings, risk ratings, and remediation recommendations.

Education

SPPU University – NBNSTIC

Bachelor of Engineering, Information Technology

Nov 2022 – Jun 2026

CGPA: 6.61

D.A.V Centenary Public School

Higher Secondary Education, Computer Science

Aug 2020 – Jun 2022

Percentage: 64%

Skills

Web Application Security TestingVulnerability Assessment & Penetration TestingSecurity ReportingSQL InjectionCross-Site ScriptingAuthentication & Access Control TestingBurp SuiteNmapWiresharkGobusterKali LinuxPythonSQLJavaLinuxWindowsTCP/IPPacket AnalysisNetwork EnumerationOWASP Top 10

Projects

BreachAware-LAW

Developed a Python-based security monitoring tool that analyzes 10,000+ log entries to detect failed login attempts and suspicious access patterns. Automated PDF incident report generation and implemented log filtering and event correlation.

Web Application Security Testing

Performed security assessments on vulnerable web applications using OWASP Top 10 methodologies. Tested 20+ application endpoints with Burp Suite Proxy and Repeater and identified SQL Injection, Cross-Site Scripting, authentication, and access control vulnerabilities.

Camera-Based Image Segmentation System

Developed a real-time image segmentation system using Python, OpenCV, and deep learning techniques. Processed live camera feeds and implemented image preprocessing and segmentation pipelines for improved object detection accuracy.