Veltech University, B.Tech in Computer Science
July. 2022 - June. 2025
Developed a machine learning model to detect malware by analyzing API calls, improving detection
Analyzing Zeus Trojan malware, identifying key signatures and enhancing threat detection methods.
CGPA: 8.4/10.0
Govt Polytechnic college proddatur, Diploma in Computer Engineering
July. 2019 - May. 2022
Studied about various programming languages like C, .Net, Java, and web technologies
Completed comprehensive coursework in networking principles, including IP addressing, subnetting, routing protocols, and network security.
CGPA: 8.4/10.0
Sri bhasyam public school, Secondary school education
Mar. 2018 - april. 2019
CGPA: 10.0/10.0
Letsdefend SIEM lab
sep. 2023 - Ongoing
Incident investigation and responder
Gained practical experience in investigating and responding to security incidents using asimulated Security Information and Event Management (SIEM) platform.
Analyzed and triaged security alerts, performed root cause analysis, and execute appropriate response actions. Developed a solid understanding of incident detection, analysis, and mitigation techniques
Detection of Malware using ML Based on API Calls (detection-malware-ml)
Developed a machine learning model for detecting malware using API calls
Improved analysis by reducing false positives in malware detection
Technology Used:Python, Scikit-learn, Assembly
Zeus Trojan Analysis (zeus-trojan-analyzer)
Investigated Zeus Trojan by dissecting its communication patterns and command-and-control infrastructure
Utilized memory analysis and debugging tools to trace malware execution flow and data exfiltration methods
Technology Used:Processmon, PEtools, Hexeditor, Anyrun sanbox, Wireshark, GNU assembler
Documenting a Security Audit and Compliance Check (security-audit-compliance)
Conducted a comprehensive security audit to ensure adherence to compliance standards
Created detailed documentation of vulnerabilities and recommended mitigation strategies
Technology Used:Python, Linux, Security Compliance Tools
Linux Fundamentals Project Series (linux-fundamentals)
Explored Linux essentials such as file systems, shell scripting, and process management
Designed interactive exercises to demonstrate core Linux administration tasks
Technology Used:Bash, Linux
SQL Fundamentals Project Series (sql-fundamentals)
Implemented key SQL concepts such as querying, joins, and data manipulation
Built hands-on projects for database design and optimization
Technology Used:SQL, MySQL
Network Traffic Analysis using tcpdump and Wireshark (network-traffic-analysis)
Analyzed network traffic to detect anomalies and potential security breaches
Utilized tcpdump and Wireshark to monitor and dissect packet-level data
Technology Used:Wireshark, tcpdump
Phishing Email Investigation and Incident Response (phishing-email-investigation)
Investigated phishing emails to identify malicious payloads and attack vectors
Applied incident response procedures to contain and mitigate phishing attempts
Technology Used:Python, Email Headers, Incident Response Tools
Importing and Parsing Security Logs using Python (security-log-parser)
Developed a Python script to import and parse security logs for threat detection
Automated log analysis to streamline detection of suspicious activity
Technology Used:Python, Log Analysis
Identifying Security Issues in a Mail Server using Splunk Cloud (mail-server-security-issues)
Monitored mail server logs to detect security issues using Splunk Cloud
Implemented alerts for suspicious email activity and server misconfigurations
Technology Used:Splunk Cloud, Python
Programming Languages
Frameworks & Technologies
Cybersecurity Skills
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Cyberchallenge 24
Apr. 2024
Secured 2nd place by effectively solving complex cybersecurity problem statements.
Demonstrated strong analytical skills and quick problem-solving abilities in a competitive environment.
Idea Contest for a Secure Cyber Space 24
Mar. 2024
3rd prize in Idea contest
Awarded for the innovative idea “Detection of Anomalies with Behavioral Analysis Using Machine Learning.”
Developed a concept focused on leveraging machine learning to identify unusual behavior patterns for enhanced cybersecurity.
