SOC-ready engineer for modern products

B. Santhosh Goud Full-Stack Developer and Cybersecurity Expert

I build secure web experiences and practical security workflows for teams that need both growth and defense. My focus combines application engineering, penetration testing, and SOC-style detection analysis.

Official GitHub Web Page Read SOC and Project Analysis Email Direct

Location: Hyderabad, Telangana
Phone: +91 7036958163
Exam target: CEH (EC-Council) scheduled

99.99%

DDoS model classification accuracy

99.55%

Web attack detection model accuracy

99.25%

Malware detection model accuracy

Hands-on cybersecurity projects

Professional Summary

Security-first builder with execution depth

Entry-level cybersecurity professional with hands-on implementation in penetration testing, network reconnaissance, and machine learning based threat detection. I design secure workflows, validate tools, and explain technical risk in business language.

My target roles include SOC analyst, penetration testing intern, and security operations support. I also work on full-stack web product delivery where secure architecture is a core requirement.

Value Proposition

What I can deliver for teams

Full-Stack Product Development

Responsive frontend, practical backend integration, and clean deployment pipelines with secure defaults.

Penetration Testing Support

Reconnaissance planning, vulnerability validation, risk write-ups, and ethical testing workflows.

SOC Analysis and Triage

Threat signal prioritization, severity scoring, and incident response handoff with operational clarity.

Top-Level SOC Analysis

Operational security view for modern environments

Threat Surface

Web applications, APIs, and identity flows
Network reconnaissance and lateral movement vectors
Phishing and social engineering entry points

Detection Strategy

Behavior-based anomaly features from traffic and logs
Signature checks for known exploit and malware patterns
ML-assisted signal ranking to reduce alert fatigue

Response Model

Immediate containment for high severity incidents
Root-cause validation before recovery actions
Post-incident lessons mapped to policy updates

Incident triage SLA matrix
Severity	Example Trigger	First Response	Escalation Path
Critical	Confirmed active exploitation or data exposure	Within 15 minutes	SOC lead and infra owner immediately
High	Credential abuse, repeated brute-force, suspicious beaconing	Within 30 minutes	Security operations and application owner
Medium	Policy violations, unusual scan activity, weak indicators	Within 2 hours	Queue for analyst validation
Low	Noise alerts and low-confidence single events	Within 1 business day	Monitor trend and tune detection

Project Evidence

Hands-on cybersecurity and detection builds

Nmap Command Builder - Knowledge-Driven Scan Mentor

Web-based command generation tool for ethical reconnaissance with structured scan workflows and risk warnings.

Live: jobless-hacker.github.io/nmap-command-builder

Machine Learning Malware Detection

Built classifiers using API call patterns with feature engineering and tuning across Random Forest, KNN, and Naive Bayes.

Best accuracy: 99.25%

Web Attack Detection Model

Decision Tree model for SQL injection, XSS, and brute-force detection on labeled web traffic datasets.

Accuracy: 99.55%

DDoS Detection Pipeline

Random Forest model trained on 225,000+ network flow records with production-style evaluation metrics.

Accuracy: 99.99%

Technical Stack

Tools, platforms, and frameworks

Python SQL Bash Kali Linux Nmap Metasploit Wireshark Burp Suite Aircrack-ng Sqlmap SET Scikit-learn NumPy Pandas Matplotlib Seaborn Random Forest KNN Decision Trees Logistic Regression Naive Bayes NIST CSF (familiar) ISO 27001 (basic)

Training and Certifications