Cloudflare

Top Builders

Explore the top contributors showcasing the highest number of app submissions within our community.

Cloudflare

Cloudflare is a leading connectivity cloud company that provides web infrastructure and website security services to millions of customers worldwide. The company operates one of the world's largest networks, spanning over 330 cities in more than 120 countries, delivering content delivery network services, DDoS mitigation, Internet security, and distributed domain name server services. With its comprehensive developer platform, Cloudflare empowers developers to build, deploy, and scale applications globally without managing traditional infrastructure.

General
Author	Cloudflare, Inc.
Website	Cloudflare
Documentation	https://developers.cloudflare.com/
Type	Web Infrastructure & Security Platform
Founded	2009
Headquarters	San Francisco, California

Core Services

Content Delivery Network (CDN)

Global network of data centers for faster content delivery
Automatic content optimization and compression
Image optimization and resizing
Static asset caching at edge locations

Security & Protection

DDoS protection and mitigation
Web Application Firewall (WAF)
Bot management and threat detection
SSL/TLS encryption and certificates
Zero Trust security solutions

DNS & Domain Services

Authoritative DNS hosting
DNS over HTTPS (DoH) and DNS over TLS (DoT)
Domain registration and management
DNSSEC support

Developer Platform

Cloudflare Workers (serverless computing)
Pages (static site hosting)
R2 object storage
D1 SQL database
KV key-value storage
Durable Objects for stateful applications

Key Features

Global Scale: Network presence in 330+ cities worldwide
Performance: Automatic optimization for speed and efficiency
Security: Enterprise-grade protection against cyber threats
Reliability: 99.99%+ uptime with built-in redundancy
Developer-Friendly: Comprehensive APIs and tooling
Cost-Effective: Free tier available with scalable pricing

Use Cases

Website acceleration and performance optimization
DDoS protection and security hardening
Serverless application development
API gateway and edge computing
Global content distribution
Zero Trust network access
IoT device connectivity

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Cloudflare AI Technologies Hackathon projects

Discover innovative solutions crafted with Cloudflare AI Technologies, developed by our community members during our engaging hackathons.

GhostAgentNinja

The problem: AI agents need email to interact with the world, but connecting them to Gmail means handing over full mailbox access — creating prompt injection risk, credential theft, and platform lock-in. Existing agent inboxes generate addresses but don't provide ownership, sovereignty, or on-chain identity. GhostAgent.ninja solves this with a new primitive: NFTs that aren't just assets, but autonomous digital entities capable of communication, ownership, and economic activity. With nftmail.box, any NFT holder gets an ENS-linked agent email (agent@nftmail.box), a Gnosis Safe treasury, and Story Protocol IP licensing — all under one sovereign on-chain identity. Emails arrive via Zoho, route through Cloudflare Workers with ECIES encryption, and cleartext is deleted immediately after processing. Zero cleartext footprint by architecture.

Lunar Graph - AI-Powered Fraud Ring Detection

Deriv's compliance teams face 2,100+ fraud alerts weekly, 95% false positives. Each investigation takes 25+ minutes, creating weeks-long backlogs. Meanwhile, fraud rings go undetected because every individual account passes KYC, AML, and risk checks perfectly. The insight: fraud is invisible individually — it's obvious at the network level. LunarGraph maps every entity (partners, sub-affiliates, clients, trades, payments) into a knowledge graph, then deploys three AI agents in parallel: Graph Anomaly Agent — Detects structural patterns like one partner controlling 20+ accounts through layered sub-affiliates sharing IP addresses and device fingerprints. Temporal Intelligence Agent — Identifies coordinated opposite BUY/SELL trades placed within 30-second windows across linked accounts (mirror trading for commission extraction). Behavioral Trajectory Agent — Compares partner behavior against known fraud signatures to predict emerging schemes 2-3 weeks before activation. The platform connects to the real Deriv WebSocket API. Partners invite affiliates via unique referral links, each generating a tracked trading account with a TradingView-style interface. Every trade feeds into the graph engine for real-time correlation analysis. An AI Copilot synthesizes findings into case reports in 28 seconds via natural language queries. Results: 99.86% alert reduction, 28-second case generation (vs 25min manual), 14-day predictive lead time, $178K+ fraud exposure detected across 3 rings and 73 entities.

Secure-AI

LLMs have recently adopted persistent memory to provide models with better user knowledge and personalisation. However, this introduces a new vector for adversarial manipulation. This report investigates Memory Injection, a threat model where adversaries exploit indirect prompt injection within web content to poison an agent's long-term memory. Employing user manipulation scenarios, we show that memory attacks, should they succeed, are effective at changing model behaviour towards the user, often more so than a direct system prompt. Hence, this highlights the need for more robust evaluations of memory updates in agentic memory systems.

AI Trading Coach - Deriv Smart Risk Assistant

AI Trading Coach is an AI-powered trading assistant designed to help traders make better decisions through analytics, risk insights, and coaching. The platform provides a clean dashboard showing portfolio KPIs such as portfolio value, win rate, total trades, and risk score. It also displays recent trades in a structured table and allows users to interact with an AI Coach chat system. The AI Coach provides trading guidance, risk management suggestions, and performance analysis. If the backend becomes unavailable, the system automatically switches into demo mode using mock trade data to ensure uninterrupted user experience. This project is focused on making trading safer, smarter, and more disciplined by combining AI-based insights with real trading metrics. It is built for fast deployment and real-world usability.

RoboGripAI

This project presents a simulation-first robotic system designed to perform structured physical tasks through reliable interaction with objects and its environment. The system focuses on practical task execution rather than complex physics modeling, ensuring repeatability, robustness, and measurable performance across varied simulated conditions. Simulation-first robotic system performing structured physical tasks such as pick-and-place, sorting, and simple assembly. Designed for repeatable execution under varied conditions, with basic failure handling, environmental interaction, and measurable performance metrics. A key emphasis of the system is reliability under dynamic conditions. The simulation introduces variations such as object position changes, minor environmental disturbances, and task sequence modifications. The robot is designed to adapt to these variations while maintaining consistent task success rates. Basic failure handling mechanisms are implemented, including reattempt strategies for failed grasps, collision avoidance corrections, and task state recovery protocols. The framework incorporates structured task sequencing and state-based control logic to ensure deterministic and repeatable behavior. Performance is evaluated using clear metrics such as task completion rate, execution time, grasp accuracy, recovery success rate, and system stability across multiple trials. The modular system design allows scalability for additional tasks or integration with advanced planning algorithms. By prioritizing repeatability, robustness, and measurable outcomes, this solution demonstrates practical robotic task automation in a controlled simulated environment, aligning with real-world industrial and research use cases. Overall, the project showcases a dependable robotic manipulation framework that bridges perception, decision-making, and action in a simulation-first setting, delivering consistent and benchmark-driven task execution.

TradingAnalyst

Aspiring Trade Wise AI is designed as an intelligent, user‑friendly platform that helps individuals understand financial markets and make more informed trading decisions. The idea is to combine clear market insights, simplified explanations, and AI‑powered guidance so beginners and intermediate traders can learn, practice, and grow with confidence. The project focuses on simplifying trading by offering structured learning paths, real‑time insights, and interactive tools that explain trends, risks, and strategies in an accessible way. The goal is to empower users to build long‑term trading skills, improve decision‑making, and navigate markets with greater clarity and discipline.