pranavc.me

security engineer · oscp-track

Pranav Chaturvedi

I build things, then try to break them - offensive security tooling, ML-based detection, and infrastructure-as-code, practiced on a homelab I run and defend myself.

zsh - pranav@coldcoffee
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0security internships
0projects shipped
0place, Cyber Conclave CTF · ~300 competitors
OSCPcertification track, in progress

01 · about

I break things on purpose, then build the tooling to catch it happening again.

Cybersecurity & Digital Forensics degree candidate at VIT Bhopal (conferral Oct 2026), focused on web application security, exploit development, and system hardening. Two internships - CSI Cyber Secured India and Unified Mentor - doing vulnerability assessment and security audits against real client systems. I build offensive security tooling and ML-based detection systems from the ground up in Python, currently working toward OSCP.

Most recently, I designed and built a two-node cybersecurity homelab from bare metal: an isolated pentest range, a scaled-down detection stack, and full observability - all defined as code and reproducible from a clean install. It's documented publicly as proof of how I actually work, not just what I know.

I'd rather ship something small and honest - including the parts that aren't finished yet - than polish a demo that doesn't reflect the real state of the work. A few projects below are still mid-build; I've labeled them as such.

status.sh online
  • Offensive SecurityBurp Suite · Nmap · sqlmap · hydra
  • Detection & MLSuricata · CrowdSec · scikit-learn
  • Infrastructure as CodeAnsible · Docker · KVM/libvirt
  • NetworkingTailscale · Cloudflare Tunnel

02 · projects

Selected work

Aug 2024 – Present
WebGuardian scan pipeline A target passes through a YAML-driven check registry running concurrently across 11 checks covering ports, TLS, WAF, headers, and DNS, producing a severity report. orchestrates 6 security tools target url YAML registry 11 checks report port/TLS scan · WAF · headers · DNS

WebGuardian

A Python framework orchestrating 6 security tools (nmap, wafw00f, curl, dnsrecon, theHarvester, nikto) into 11 automated checks - port/TLS scanning, WAF detection, header disclosure, DNS zone transfer, and web misconfiguration - via a YAML-driven check registry with concurrent execution and an 18-test pytest suite.

PythonWeb AppSecpytest
Jan – Apr 2025
IDS model comparison pipeline The KDD Cup 1999 dataset feeds five classification algorithms, whose predictions are compared for attack detection across DoS, R2L, U2R, and probing categories. KDD Cup 1999 5 classifiers Random Forest · Linear SVM · DT Naive Bayes · Logistic Reg. compared for accuracy attack detection DoS · R2L · U2R · Probing

Intrusion Detection System (ML)

Trained and compared 5 classifiers - Random Forest, Linear SVM, Decision Tree, Naive Bayes, Logistic Regression - on KDD Cup 1999, with a stratified split and per-class precision/recall given how imbalanced the data is. The real finding: even 99.97%-accurate Random Forest is worst specifically at catching u2r (privilege escalation) - the rarest, most severe category.

Pythonscikit-learnML detection
Feb 2026
Zero-trust Nextcloud network diagram Admin access reaches Nextcloud over Tailscale; the public internet reaches it over a Cloudflare Tunnel. MariaDB and Redis sit in an isolated group with no exposed ports. admin tailscale public https cloudflare tunnel nextcloud no exposed ports mariadb redis

Zero-Trust Self-Hosted Infra

A production-style Nextcloud/MariaDB/Redis stack on Docker Compose with zero exposed inbound ports - admin access via Tailscale, public HTTPS via Cloudflare Tunnel, version-pinned images, an isolated DB container, and automated volume-level backups.

DockerTailscaleCloudflare Tunnel
ongoing log
PortSwigger lab workflow Each academy lab is paired with a Python exploit script, optionally routed through Burp as a proxy, run against the target application, and logged as solved with notes. one folder per vulnerability class academy lab exploit script.py burp proxy (opt.) target app solved

PortSwigger Labs

9 SQL injection labs solved and documented on the PortSwigger Web Security Academy - WHERE-clause SQLi, login bypass, UNION attacks, database fingerprinting, and blind SQLi via conditional responses (binary-search extraction, not a linear scan). Each pairs a runnable exploit script with a write-up of the flaw and the reasoning that found it.

PythonWeb AppSecBurp Suite
actively building
Sentinel architecture - shell built, engine in progress The landing page, auth, and Razorpay billing shell are built and feed a gated dashboard. The log analysis engine is a separate, still-unwired, work-in-progress component. shell - built landing auth razorpay billing dashboard (gated) analysis engine - coming soon FastAPI · SQLAlchemy · Razorpay

Sentinel - Log Analyzer

A security-analyst-in-a-box for small teams: upload auth/Apache/Nginx/firewall logs and get plain-English findings on brute-force attempts, suspicious IPs, and scanning activity. The FastAPI shell - auth, Razorpay billing (test mode; a prepaid-charge stopgap until Subscriptions clears KYC), gated dashboard - is built; the analysis engine is being rebuilt. Shipping it honestly, mid-build.

FastAPIRazorpaySQLAlchemyin progress
2026 · private repo
ClauseCheck analysis pipeline An uploaded contract or lease is sent through Claude's tool-use API to produce a structured risk breakdown, stored per-user behind Supabase Row-Level Security. structured output via tool-use upload contract Claude tool-use risk report Supabase RLS · magic-link auth · Razorpay

ClauseCheck

A SaaS tool that ingests contracts, leases, and ToS documents and returns a structured risk breakdown - overall risk level, plain-English summary, and clause-level flags with rationale - using Claude's tool-use for reliable structured output. Supabase Postgres with Row-Level Security, magic-link auth, and Razorpay subscriptions behind signature-verified webhooks (test mode; live billing gated on pending KYC).

Next.jsClaude APISupabase
coursework project
CyberShield page structure A static vanilla HTML/CSS frontend with three sections: an incident report form, a threat database, and incident search - no backend wired up. static frontend · no backend wired report form threat database search incidents

CyberShield

A front-end concept for a community cybersecurity-incident reporting tool - an incident report form, a browsable threat database, and incident search, built in vanilla HTML/CSS as a UI exercise.

HTML/CSSUI/UX
university capstone · team
Deepfake detector data flow Uploaded media is passed to a computer-vision classifier backend, which returns a real-or-fake prediction to the web frontend. upload media CV / CNN classifier real / fake Python backend · web frontend

Deepfake Detector

Group capstone project for my B.Tech - a deepfake-detection web application pairing a computer-vision classification backend with a web frontend for uploading and screening media.

PythonComputer VisionGroup project

03 · experience & education

Timeline

04 · certifications & awards

Proof of work, on paper

certification Google Cybersecurity Professional Certificate Coursera · issued
certification The Bits and Bytes of Computer Networking Google via Coursera · issued Dec 2023
certification MongoDB Associate Database Administrator FACE Prep · issued Apr 2025
certification EC-Council CEH in progress
award 1st Prize, Cybersecurity Reverse Engineering Cranes Varsity
award 1st Prize, Cyber Conclave CTF ~300 competitors

05 · contact

Let's talk

Open to opportunities in offensive security, detection engineering, and infrastructure roles.

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