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T Yashwanth Raj

T Yashwanth Raj

Computer Science graduate

Hyderabad, Telangana

I am a Computer Science graduate with hands-on training and lab experience in cybersecurity, security monitoring, SIEM, EDR/XDR, alert triage, log analysis, threat detection, and incident investigation. I designed a rule set to bucket simulated security events into low/medium/high priority using log evidence alone, aimed at cutting analyst time spent on noise and surfacing the handful of events that actually mattered. My current focus is on applying my technical knowledge in a real-world security environment.

Skills

IBM QRadarSplunk EnterpriseMicrosoft SentinelCortex XDRMicrosoft Defender for EndpointCrowdStrike FalconSentinelOneSecurity MonitoringAlert TriageIncident Investigation & ResponseIOC AnalysisRoot Cause AnalysisFalse Positive AnalysisThreat HuntingWindows/Linux/AD/Firewall/VPN/DNS/Proxy/Endpoint LogsTCP/IPOSI ModelDNSDHCPHTTP/HTTPSVPN FundamentalsProofpointMicrosoft Defender for O365Phishing & Email Header AnalysisMITRE ATT&CK FrameworkCyber Kill ChainOSINTFirewallsIDS/IPSWeb Application FirewallProxyVPNAntivirusEndpoint ProtectionCIA TriadDefense in DepthZero TrustEncryptionHashingVulnerability AssessmentCVE AnalysisServiceNowJiraPowerShellPythonKQLSplunk SPLAzure

Projects

SIEM Alert Triage Simulation

Designed a rule set to bucket simulated security events into low/medium/high priority using log evidence alone, aimed at cutting analyst time spent on noise and surfacing the handful of events that actually mattered.

Phishing Email Forensics

Broke down suspicious emails at the header, domain, and payload level — sender spoofing, lookalike domains, malicious attachments — and turned the findings into a repeatable triage checklist.

Windows Event Log Investigation

Worked through Windows Security event data to isolate failed logons, lockout patterns, and privileged-account activity, mapping how that evidence supports a real incident narrative.

Network Traffic Fundamentals for Detection

Studied TCP, UDP, DNS, DHCP, and ARP behavior specifically to build a 'what does normal look like' baseline, then used that baseline to spot deviations worth flagging.

Threat Intel IOC Correlation

Cross-referenced sample IPs, domains, and file hashes against log data to practice deciding, with limited context, whether an indicator needs escalation or just monitoring.

Education

Keshav Memorial Institute of Technology

Bachelor of Computer Science • 2021-2025

7.3

Sri Chaitanya Junior Kalasala

Intermediate • 2019-2021

90.4

DAV Public School

SSC • 2019

91.2

Get in Touch

Interested in collaboration or just want to say hello? Feel free to reach out!

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