Introducing Clairic, a new System One class of extraction models
Clairic is a new model from Cloudflare that is a System One extraction modeI, capable of extracting, computing, estimating, and forecasting data from unstructured inputs.
TAG
Machine Learning
Introducing Clef-omni with full multimodality, plus a faster Clef and a cheaper Clef-flash
We are expanding the Clef decision model family with Clef-omni, natively processing audio, video, images, and text in a single pipeline. We’ve also lowered Clef-flash pricing and boosted Clef inference speeds by up to 2.0x.
Introducing Clef: our open-source decision models, and new RL fine-tuning platform
We are introducing Clef and Clef-flash, open-source decision models hosted on Workers AI for high-speed classification and agentic workflows. Also launching: a new reinforcement learning platform that allows developers to fine-tune decision models using their own data.
We tested our own WAF with frontier AI models. Here’s what we found
We built a WAF tester that adapted each request based on what the WAF blocked or passed. This helped us explore variations that a fixed test might miss. We ran it across six attack categories on an authorized staging environment and discovered detection gaps worth fixing. Here’s how the loop worked, what got through, and what we did about it.
When scanners miss the attack: how Cloudflare Client-Side Security protects storefronts
A modern storefront can look healthy while malicious JavaScript quietly siphons revenue, hijacks clicks, or rewrites analytics. See how Cloudflare's machine learning models surface evasive client-side attacks for analyst investigation.
Introducing Adaptive Intelligence: Undermining the economics of every bot attack
Bot operators have historically had the economic advantage, bypassing static, deterministic detection rules with cheap proxies and retooling. Cloudflare's new Adaptive Intelligence engine flips this dynamic by autonomously learning from the meta-signals of live traffic and deploying disposable rules, making automated attacks too expensive to sustain.
Cloudflare Client-Side Security: smarter detection, now open to everyone
We are opening our advanced Client-Side Security tools to all users, featuring a new cascading AI detection system. By combining graph neural networks and LLMs, we've reduced false positives by up to 200x while catching sophisticated zero-day exploits.
Improved Bot Management flexibility and visibility with new high-precision heuristics
By building and integrating a new heuristics framework into the Cloudflare Ruleset Engine, we now have a more flexible system to write rules and deploy new releases rapidly.
How we train AI to uncover malicious JavaScript intent and make web surfing safer
Learn more about how Cloudflare developed an AI model to uncover malicious JavaScript intent using a Graph Neural Network, from pre-processing data to inferencing at scale.
Trapping misbehaving bots in an AI Labyrinth
How Cloudflare uses generative AI to slow down, confuse, and waste the resources of AI Crawlers and other bots that don’t respect “no crawl” directives.
Training a million models per day to save customers of all sizes from DDoS attacks
In this post we will describe how we use anomaly detection to watch for novel DDoS attacks. We’ll provide an overview of how we build models which flag unusual traffic and keep our customers safe.
AI Everywhere with the WAF Rule Builder Assistant, Cloudflare Radar AI Insights, and updated AI bot protection
This year for Cloudflare’s birthday, we’ve extended our AI Assistant capabilities to help you build new WAF rules, added new AI bot & crawler traffic insights to Radar, and given customers new AI bot
Making WAF ML models go brrr: saving decades of processing time
In this post, we discuss performance optimizations we've implemented for our WAF ML product. We'll guide you through code examples, benchmarks, and we'll share the impressive latency reduction numbers
Declare your AIndependence: block AI bots, scrapers and crawlers with a single click
To help preserve a safe Internet for content creators, we’ve just launched a brand new “easy button” to block all AI bots. It’s available for all customers, including those on our free tier
Using machine learning to detect bot attacks that leverage residential proxies
Cloudflare's Bot Management team has released a new Machine Learning model for bot detection (v8), focusing on bots and abuse from residential proxies
Defensive AI: Cloudflare’s framework for defending against next-gen threats
From identifying phishing attempts to protect applications and APIs, Cloudflare uses AI to improve the effectiveness of its security solutions to fight against new and more sophisticated attacks
Navigating the maze of Magecart: a cautionary tale of a Magecart impacted website
E-commerce websites were targeted by a sophisticated Magecart attack, involving a hidden JavaScript code designed to secretly steal Personally Identifiable Information (PII) and credit card details from users
Monitoring machine learning models for bot detection
We recently shared an introduction to Cloudflare’s approach to MLOps, which provides a holistic overview of model training and deployment processes at Cloudflare. In this post, we will dig deeper into monitoring, and how we continuously evaluate the models that power Bot Management
