CYBER HACKATHON
v4.0
Official Hackathon of Greater Chennai Police in collaboration with Easwari Engineering College.
FINAL EVENT
March 06 - 07, 2026
VENUE
Easwari Engineering College
ORGANIZERS
Greater Chennai Police & Easwari Engineering College
SECURING THE DIGITAL FRONTIER
Cyber Hackathon v4 is a premier hackathon organized by the Greater Chennai Police in collaboration with Easwari Engineering College.
We invite the brightest minds to tackle real-world challenges in cybersecurity, digital forensics, and smart policing. Join us to innovate, collaborate, and build solutions that make a difference.
Innovation
Build cutting-edge solutions for modern problems.
Security
Focus on cybersecurity and digital safety.
Community
Connect with experts and like-minded hackers.
Technology
Leverage the latest tech stacks and tools.
Problem Statements
Select a track below to view the detailed operational requirements.
Background
The rapid advancement of Artificial Intelligence has enabled the creation of highly realistic synthetic media such as deepfake videos, AI-generated images, cloned voices, and manipulated digital content. These technologies are increasingly being misused for misinformation, impersonation, financial fraud, and cybercrime.
Objective
Develop a system capable of detecting AI-generated or manipulated media content and assisting law enforcement agencies in verifying authenticity.
Scope & Evaluation
- Detection of deepfake videos, images, or audio
- Identification of AI-generated content
- Metadata and content analysis
- Confidence scoring for authenticity
- Real-time or near real-time analysis capability
- Detection accuracy - Should able to tell which AI model or Website used
- Scalability
- Ease of use
- Innovation in detection approach
- Practical applicability for investigations
Outcome
A prototype tool that can assist investigators in identifying manipulated or synthetic digital media reliably.
Background
Cryptocurrency transactions are frequently used in cybercrime due to pseudonymity and cross-border transfers. Tracking the flow of illicit funds across wallets and exchanges remains a major challenge for investigators.
Objective
Design a system that helps trace the movement of cryptocurrency funds across blockchain transactions and identify suspicious fund flows.
Scope & Evaluation
- Visualization of transaction flow
- Wallet linkage analysis
- Suspicious pattern detection
- Risk scoring of wallets
- Multi-hop transaction tracking
- Accuracy of tracing
- Clarity of visualization
- Analytical capability
- Usability for investigation teams
- Technical feasibility
Outcome
A visualization and analysis platform that simplifies cryptocurrency investigation and aids in identifying fund movement patterns.
Background
Digital forensic investigations often involve analyzing large volumes of devices and data. Investigators require quick triage tools to prioritize evidence and identify relevant artifacts efficiently.
Objective
Develop a cyber forensic triage software that helps investigators quickly identify critical digital evidence from seized devices.
Scope & Evaluation
- Rapid scanning of storage devices
- Identification of suspicious files or activities
- Extraction of key artifacts (logs, browser history, documents)
- Timeline generation
- Priority-based evidence classification
- Speed and efficiency
- Accuracy of artifact identification
- Practical usability
- Automation capability
- Investigation relevance
Outcome
A lightweight forensic triage tool that reduces investigation time and improves evidence prioritization.
Background
In many investigations—such as cyber-extortion, kidnapping, or anonymous threats—suspects hide behind VPNs, Proxies, or the Tor network. Traditional IP logging at the server level often only reveals the data center's address rather than the criminal's true location or device identity. Investigators need a way to "lure" a suspect into revealing their actual digital footprint.
Objective
Develop a secure "Canary" platform that allows Law Enforcement Officers (LEOs) to generate trackable digital assets (links, documents, or media) which, when accessed by a suspect, bypass common obfuscation techniques to log forensic-grade identification data.
Scope & Evaluation
- Multi-Vector Bait Generation: Ability to create "barbed" assets including shortened URLs, PDF/Word documents with tracking pixels, and images with embedded beacons.
- Advanced Attribution: Techniques to bypass VPNs (e.g., WebRTC leaks) and gather deep device fingerprints (Canvas ID, hardware specs, OS version, and battery status).
- On-Demand Geo-Fencing: A mechanism to request high-precision GPS coordinates from the device, disguised as a "security verification" or "regional access" prompt.
- Real-Time Tactical Alerts: A centralized dashboard that provides instant notifications (SMS/Email) to the officer the moment an asset is triggered.
- Evidence Integrity: An automated, tamper-proof log of the "Chain of Custody" for all captured data to ensure it is admissible in a court of law.
- Stealth & Persistence
- De-anonymization capabilities
- Forensic Integrity
- Operational Security (OpSec)
- Ease of deployment
Outcome
A stealthy, browser-agnostic tracking platform that provides investigators with a suspect’s real-world location and device identity, even when the suspect is attempting to remain anonymous.
Background
Cyber investigations often involve sensitive data that cannot be processed through online AI systems due to privacy and security concerns. Investigators require intelligent tools that can operate in isolated environments.
Objective
Develop an offline Large Language Model (LLM)-based assistant that supports cybercrime investigation without internet connectivity.
Scope & Evaluation
- Offline document analysis
- Log and evidence summarization
- Query-based investigation assistance
- Cyber law or investigation reference support
- Secure local deployment
- Offline capability
- Accuracy of responses
- Security and privacy considerations
- Performance efficiency
- Practical investigation support
Outcome
An offline AI assistant that enhances investigator productivity while ensuring data confidentiality.
Judging Criteria
How your solution will be evaluated.
Innovation and Originality
Creativity of the idea and uniqueness of the approach in solving the problem statement.
Technical Implementation
Quality of development, system architecture, and effective use of technologies.
Completeness of the Solution
The solution should be a complete working prototype, not limited to backend implementation alone. Teams are expected to demonstrate an end-to-end solution.
Scalability and Usability
The solution should be scalable for real-world usage and designed to be simple, practical, and easy for end users or investigators to operate.
Effectiveness and Practical Impact
The effectiveness of the solution in addressing real cybercrime or cybersecurity challenges and its potential for practical adoption.
Presentation and Demonstration
Clarity in explaining the problem, solution workflow, and live demonstration of the working prototype.
WINNING REWARDS
RUNNER UP
Silver Tier
WINNER
Gold Tier
2nd RUNNER UP
Bronze Tier
EVENT TIMELINE
Registration Starts
Call for hackers! Online registration opens for all participants.
Queries Meeting
Online session to clarify doubts regarding problem statements and submissions. Today 6:00 PM to 6:30 PM.
JOIN GOOGLE MEETRegistration Closes
Last chance to submit your team details and abstract.
Finalist Announcement
Shortlisted teams will be announced for the grand finale.
Grand Finale
24-hour hackathon at Easwari Engineering College.
REGISTER NOW
Scan the QR code to access the official registration portal.
REGISTER HEREOpen until February 25, 2026