CYBERSECURITY / SYSTEMS / AUTOMATION

Make systems
easier to trust.

I’m Furkhad Ahmed — a computer science engineering student building security tools, automation workflows, and practical ways to understand how systems behave.

Explore selected work GitHub profile
Open to entry-level cybersecurity and SOC opportunities
BASED INBengaluru, India
EDUCATIONB.E. Computer Science · 2027
CURRENT FOCUSSecurity engineering & detection
WORK STYLEEvidence before assumptions

01 / SELECTED WORK

Tools with a point of view.

A selection of security, automation, and applied-ML projects. Each repository contains implementation details and setup notes.

QSHIELD / SECUREACCESS01—04
CYBER-PHYSICAL SECURITY PROTOTYPE
FLAGSHIP PROJECTRESEARCH / SIMULATION

QShield SecureAccess

A cyber-physical access-control prototype that combines device identity, simulated proximity and post-quantum checks, suspicious-identity detection, trust scoring, and an auditable event stream.

Scope note: proximity and post-quantum paths are software simulations, not production cryptographic or hardware attestations.

PythonFastAPIReactWebSockets
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STREAMSENTINEL / LIVE GUARD02—04
LIVE FRAME ANALYSIS
TEXT SIGNALAPI_KEY_••••
!
Potential exposureReview / stop broadcast
FLAGGED
LOCAL-FIRST MONITORING CONCEPT
COMPUTER VISIONHACKATHON PROJECT

StreamSentinel

A prototype to detect sensitive text appearing during live streams, trigger a protective stream action, and send an incident notification before accidental disclosure spreads.

PythonOpenCVEasyOCRDocker
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AUTO-PENTEST / REPORT PIPELINE03—04
assessment.log● ● ●

$ scan --authorized-target

✓ port inventory collected

✓ findings structured

↳ local model: remediation draft

ASSESSMENT SUMMARY
Findings → evidence → remediation
AUTHORIZED TESTING ONLY
SECURITY AUTOMATIONVAPT REPORTING

Auto-Pentest Reporter

A Python workflow that turns authorized network-scan output into structured findings and an executive-facing summary with remediation suggestions using a local LLM.

PythonNmapOllamaStreamlit
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YOUTUBE FOCUS ML04—04
YF
Focus profileGoal-based feed filtering
ON
MY CURRENT GOALLearn Python and security
PYPython project walkthroughRelevant content✓
∞Random recommendationsLow relevance×
ON-DEVICE CLASSIFICATION
BROWSER EXTENSIONPRIVACY-AWARE ML

YouTube Focus ML

A browser extension that uses a goal-based filter and on-device ML classification to reduce irrelevant YouTube recommendations without sending the user's focus goal to a remote service.

JavaScriptONNXWebAssemblyChrome APIs
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More repositories and experimentsBrowse all projects

02 / HOW I WORK

Curiosity is useful.
Evidence is better.

The goal is not to make a tool look sophisticated. It is to make its behavior understandable, its limits visible, and its results testable.

A / 01

Observe first

Start with system behavior, logs, traffic, and the available evidence before choosing a theory.

A / 02
✓

Verify the result

Prefer reproducible checks, measurable outcomes, and clear limitations over unsupported claims.

A / 03
↗

Build responsibly

Keep scope explicit, respect authorization boundaries, and design for useful human decisions.

03 / BACKGROUND

A systems-minded approach.

Computer science, Linux, security tooling, and automation — with a focus on learning by building and then checking the result.

I’m studying Computer Science Engineering at K. S. Institute of Technology in Bengaluru, with graduation planned for 2027.

I’m working toward roles in cybersecurity and security operations. My projects explore the practical edges between network visibility, vulnerability assessment, automation, computer vision, and applied machine learning.

I value readable implementations, honest threat models, and documentation that lets someone else reproduce what I did.

LinkedIn GitHub

04 / CONTACT

Let’s work on something
that matters.

For entry-level opportunities, internships, technical collaboration, or feedback on a project, use one of the links below.

Email Furkhad Connect on LinkedIn Explore GitHub
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