Website owners fuel the ecosystem of ideas, news, and interesting tidbits, but they face the increasingly complex challenge of managing traffic to their websites and being paid for their content. While some bot traffic is clearly malicious, it isn’t always obvious when a particular AI crawler is helping or harming your business. To answer this, site owners need granular, reliable data to differentiate between traffic that provides value, and traffic that strains resources while eroding the foundation of their business model: actual humans consuming their content. 

At Cloudflare, we hold a core belief: website owners have the right to control access to their content. We want to help website owners maintain their high-quality content and regulate AI traffic.

To provide much-needed clarity and help website owners take control, we’re excited to announce the new Attribution Business Insights dashboard — designed with business decision-makers and publishers in mind.

For decades, the business model of the Internet relied on a straightforward, unspoken agreement: website owners allowed search engines to crawl their content and, in return, search engines sent readers back to their pages. This symbiotic relationship, where traditional search engines operated with a balanced "crawl-to-referral" ratio, generated the pageviews needed to sustain advertising, affiliate revenue, and subscriptions. Search index crawlers would scan your content a couple of times for each referral sent, so making your website available to crawlers had a clear pipeline to additional revenue. We can think of this as the SEO (Search Engine Optimization) era.

Today, the explosive rise of AI crawlers and agents has broken this contract, plunging the digital publishing industry into an unprecedented crisis. The Internet is risking a transition into a "zero-click" ecosystem where AI chatbots scrape original content to synthesize instant answers — completely bypassing the original sources. We’ve already seen a marked shift from the SEO-only world into an AEO (Answer Engine Optimization) world, and now conversations around GEO (Generative Engine Optimization) are taking center stage.

The imbalance of this new reality is made clear by the crawl-to-referral ratios we see across the Internet today. While traditional search engines had a more balanced ratio of crawls to legitimate visitors referred, major AI crawlers operate on a drastically different, extractive scale. Bots from leading AI companies have been observed with a range of crawl-to-referral ratios: we noted ratios of 118:1 up to nearly 50,000:1 around the time of our Content Independence Day in 2025. In other words, an AI crawler might have crawled your premium content tens of thousands of times just to send back a single visitor. This ratio is fundamentally unfair.

For publishers, this creates a double hit: first, they’re losing out on the crucial referral traffic, ad impressions, and direct audience relationships that fund content creation and journalism. Second, they’re forced to bear the rising infrastructure costs of hosting and serving content to automated bots that offer no commercial value in return. The era in which it makes sense to allow all crawlers in the hopes of being discovered is over.

We want website owners to have the facts — the cold, hard numbers to understand which bots are helping their business and which bots are harming it. We also want to make this analysis easier than ever, which is why we’ve designed Attribution Business Insights to cut the noise, focusing on the details that our customers have told us are most important. 

Today, the Attribution Business Insights dashboard is available to all Cloudflare Bot Management customers. The new dashboard is designed to deliver a targeted view of bot traffic flowing to your website; unlike traditional analytics tools that may require extensive manual filtering, this dashboard provides you with key insights right away.

We set out to answer the most pressing questions for site owners today: How should you think about AI traffic on your websites? What is the value of different audiences — including humans, non-AI bots, and AI bots? And most importantly, what is your data being used for? 

^{The new Attribution Business Insights dashboard view, which includes insights about bot traffic overall, a site-wide crawl-to-referral ratio, and the distribution of AI bot traffic vs. organic traffic.} 

To answer these questions, the dashboard displays a powerful array of data and insights:

• Bot traffic to content pages: View your overall bot vs. human traffic, as well as the volume of all bots successfully accessing content.

• Crawl-to-referral ratios: See your site-wide crawl-to-referral ratio on the scale of 24 hours, seven days, or 30 days. You can also see crawl-to-referral ratios per bot operator (per company that owns one or more bots).

• Top bots breakdown: A list of top bots by volume, including their country of origin, bandwidth they take up on your website, and whether you’re currently blocking or allowing them.

• Updated classification based on crawler behavior: We go beyond a generic label of “AI Crawler” by classifying crawlers with our updated taxonomy, whether it’s Training (i.e., training the next version of an LLM chatbot), Search (i.e., refreshing databases for Retrieval-Augmented Generation), or Agent (i.e., used in agentic interaction to return answers to an end user).  

You shouldn’t have to be a security expert to understand how AI crawlers affect your business. If website owners want to spend just a few minutes ingesting the high-level insights, they can walk away with a clear temperature check of the effectiveness of their content security policy.

For those who want to do a little more digging to understand how AI companies are making use of their content — or collect information to guide how they want their relationships with AI companies to develop — we show a more granular view organized by bot operator.

^{Breakdown of bot activity on a website, with important details for each bot such as type, crawl-to-referral ratio, and current action.} 

By having a consolidated view of companies seeking to access content on your website, you can develop a better baseline of crawler activity. We want this data to equip our customers to step into any business conversation with the facts on their side. Tell Company1 that their crawl volume is twenty times that of Company4’s, and that Company4 is already compensating you for content. Revisit the way that Company2 licenses your content based on their recent activity. This new dashboard propels business conversations to move forward. 

How does this new layer of visibility tie into the existing tools you have to protect your website from abuse? In line with other features of Bot Management, the action step still happens in Security rules. To avoid adding noise to the control plane, Attribution Business Insights is intended to be a hub for thoughtful, filtered analytics, rather than another place to take action. This dashboard serves as a central source of information, allowing you to investigate before then taking an action in the same rule engine that governs other abuse mitigations. We also want to be loud and clear about inviting business decision-makers into this dashboard, acknowledging that conversations around AI traffic have a wider set of stakeholders than only security-specialized users.

The Attribution Business Insights dashboard is the next critical step in providing website owners with the transparency and control they need to manage evolving AI bot threats, and more broadly, shape the new dynamics of the Internet. We’re already investigating the next iteration with close publishing partners to create a visibility plane that covers security from the perspective of the website owner with valuable, original content to share. 

A sneak preview below includes a new view to dissect crawler activity per-article to reveal the appetite that AI companies have for different pieces of content, different campaigns, and so on.

^{Breakdown of most popular articles, according to traffic volume. Shows key metrics such as AI bot traffic vs. other bot traffic vs. human traffic, both direct and from a referral.}  

Visibility is the first piece, and there’s more to come to empower website owners to take control of their content in this new age. We encourage all customers of Cloudflare Bot Management — especially those driving business conversations — to access this today for a fresh take on analytics. 

With this per-customer approach, we’re giving every bot management customer hyper-personalized security capabilities to stop even the sneakiest bots. We’re doing this by not only making a first-request judgement call, but also by tracking behavior of bots who play the long-game and continuously execute unwanted behavior on our customers’ websites. We want to share how this service works, and where we’re focused. Our new platform has the power to fuel hundreds of thousands of unique detection suites, and we’ve heard our first target loud and clear from site owners: protect websites from the explosion of sophisticated, AI-driven web scraping.

The battle against malicious bots used to be a simpler affair. Attackers used scripts that were fairly easy to identify through static, predictable signals: a request with a missing User-Agent header, a malformed method name, or traffic from a non-standard port was a clear indicator of malicious intent. However, the Internet is always evolving. As websites became more dynamic to create rich user experiences, attackers evolved their tools in response. The simple scripts of yesterday were replaced by headless browsers and automation frameworks, capable of rendering pages and mimicking human interaction with far greater fidelity.

AI has made this even trickier. The rise of Generative AI has fundamentally changed the capabilities and the motivations of attackers. The web scraping of today isn’t limited to competitive price intelligence or content aggregation, but driven by the voracious appetite of Large Language Models (LLMs) for training data.

Cloudflare’s data shows this shift in stark terms. In mid-2025, crawling for the purpose of AI model training accounted for nearly 80% of all AI bot activity on our network, a significant increase from the year prior. Modern scraping tools are now AI-powered themselves. They leverage LLMs for semantic understanding of page content, use computer vision to solve visual challenges, and employ reinforcement learning to navigate complex websites they’ve never seen before. The evolution of these bots exposes critical vulnerability in the traditional, one-size-fits-all approach to security. While global threat intelligence is immensely powerful for stopping widespread attacks, these new AI-powered scrapers are designed to blend in. They can rotate IP addresses through residential proxies, generate human-like user agents, and mimic plausible browsing patterns. A request from one of these bots might not look anomalous when compared to the trillions of requests we see across the Cloudflare network, but would appear anomalous when compared to the established patterns of legitimate users on a specific website. This means we need to build defenses against these bots from every angle we have — from the global view to specific behavior on a single application.

To target specific well-known bots or bot actors, we leverage the Cloudflare network to fingerprint bots that we see behave similarly across millions of websites. Since June, Cloudflare’s bot detection security analysts have written 50 heuristics to catch bots using a variety of signals, including but not limited to HTTP/2 fingerprints and Client Hello extensions. By observing traffic on millions of websites, we establish a baseline of legitimate fingerprints of common browsers and benign devices. When a new, unique fingerprint suddenly appears across many different sites, it's a tell-tale sign of a distributed botnet or a new automation tool, allowing our analysts to block the bot's signature itself and neutralize the entire campaign, regardless of the thousands of different IP addresses it might use.

Recently, we also introduced detection improvements to tackle residential proxy networks and similar commercial proxies, which are used by attackers to make their bots appear as thousands of distinct real visitors, allowing them to bypass traditional security measures. The superpower of this detection improvement? Combining the vast amount of network data we see with particular client-side fingerprints obtained through the millions of challenge solves that happen across the Internet daily. Challenges have always served as an ideal mitigation action for customers who want to protect their applications without compromising real-user experience, but now they also serve as a gift that keeps on giving: in this case, feeding the Cloudflare threat detection teams a constant stream of client-side information that allows us to pattern match to determine IP addresses that are used by residential proxy networks.

This detection improvement is already ingesting data from the entire Cloudflare network, automatically catching more malicious traffic for all customers using Super Bot Fight Mode (bot protection included for Pro, Business, and all Enterprise customers) and Enterprise Bot Management. Examining 7 days of data from the time of authoring this post, we’ve observed 11 billion requests from millions of unique IP addresses that we’ve identified as connected to residential or commercial proxy networks. This is just one piece of the global detection puzzle; the existing residential proxy detection features in our ML already catch tens of millions of requests every hour. 

The new arms race against AI-powered bots necessitates a closer look — something more precise. For instance, a script that systematically scrapes every user profile on a social media site, or every product listing on an e-commerce platform, is exhibiting behavior that is fundamentally abnormal for that application, even if a standalone request appears benign. This realization is at the heart of our new strategy: to win this new arms race, defenses must become as bespoke and adaptive as the attacks they face.

To meet this challenge, we built a new, foundational platform engineered to deploy custom machine learning models for every bot management customer. We’re creating a unique defense for every application. Because each website has different traffic, the traffic that we flag as anomalous will, of course, be different for each zone — for this system, we want to be clear that data from one customer’s zone won’t be used to train the model for another customer’s use.

Announcing this as a new platform capability, rather than a single feature, is a deliberate choice. It aligns with how we’ve approached our most significant innovations, from Cloudflare Workers changing how developers build applications, to AI Gateway creating a single control plane for AI observability and security. By focusing on the platform, we tackle the scraping problems our customers are seeing today and power future detections as bot attacks become increasingly sophisticated.

Our new generation of per-customer anomaly detection is a three-step process, designed to identify malicious behavior by first understanding what constitutes legitimate traffic for each individual website and API.

For each customer zone, our behavioral detections ingest traffic data to build a baseline of normal activity. Rather than taking a static snapshot, our new platform ingests data to make living, continuously updated calculations of what “normal” looks like on a specific website. This approach understands seasonality, recognizes traffic spikes from legitimate marketing campaigns, and maps the typical pathways users take through a site. This approach evolves the concept of Anomaly Detection already present in our Enterprise Bot Management suite, but applies it at a far more granular and dynamic per-customer level.

Once the baseline of "normal" is established, we begin the true work — identifying deviations. Because the baseline is specific to each website, the anomalies detected are highly contextual, perhaps even invisible to a global system. We can examine a few different types of websites to unpack this:

• For a gaming company: A normal traffic baseline might show millions of users making frequent, rapid API calls to a matchmaking service or an in-game inventory system. A behavioral detection model trained on this baseline would immediately flag a single user making slow, methodical, sequential API calls to scrape the entire player leaderboard. This behavior, while low in volume, is a clear anomaly against the backdrop of normal gameplay patterns.

• For a retail website: The normal baseline is a complex funnel of users browsing categories, viewing products, adding items to a cart, and proceeding to checkout. These detections would identify an actor that systematically visits every single product page in alphabetical order at a machine-like pace, without ever interacting with the cart or session cookies, as a significant anomaly indicative of content scraping.

• For a media publisher: Normal user behavior involves reading a few articles, following internal links, and spending a measurable amount of time on each page. An anomaly would be a script that hits thousands of article URLs per minute, spending less than a second on each, purely to extract the text content for AI model training.

In each case, the malicious activity is defined not by a universal signature, but by its deviation from the application's unique, established norm.

Detecting an anomaly is only half the battle. The power of bot management comes from its seamless integration into the Cloudflare security ecosystem you already use, turning detection into immediate, actionable findings. Customers can benefit from these behavioral detection improvements in two ways:

1. New Bot Detection IDs: For our Enterprise customers, we’re introducing a new set of Bot Detection IDs. Website owners and security teams can write WAF security rules to challenge, rate-limit, or block traffic based on the specific anomalies flagged by these detections. Since each detection type is tied to a unique ID, customers can see exactly what kind of behavior caused a request to be flagged as anomalous, offering a detailed, per-request view into stealthy malicious traffic. And for a wider view, customers can filter by Detection ID from their Security Analytics, to see the bigger picture of all traffic captured by that detection type.

2. Improving Bot Score: Another key output from these new, per-customer models will be to directly influence the Bot Score of a request. A request flagged as anomalous will have its score lowered, moving it into the "Likely Automated" (scores 2-29) or "Automated" (score 1) categories. This means that existing WAF custom rules based on Bot Score will automatically see impact and become more effective against bespoke attacks, with no changes required. This functionality update is available today for our latest account takeover detection, residential proxy detections and our recent enhancements, and will be implemented in the future for our behavioral scraping detection. 

This three-step process is already in action with our behavioral detections to catch account takeover attacks. Taking bot detection ID 201326598 as an example: it (1) establishes a zone-level baseline that understands what normal traffic patterns look like for a specific website, (2) examines anomalous login failures to identify brute force and credential stuffing attacks, then (3) allows customers to mitigate these attacks by automatically influencing bot score and offering more visibility with the detection ID’s analytics. 

This integration strategy creates a flywheel effect: the new intelligence from these improved detections immediately enhances the value of existing products like Super Bot Fight Mode, Bot Management, and the WAF, making the entire Cloudflare platform stronger for you.

The first challenge we’re tackling is sophisticated scraping. AI-driven scraping is one of the most pressing and rapidly evolving threats facing website owners today, and its adaptive nature makes it an ideal adversary for a system designed to fight an enemy that constantly changes its tactics.

The first generation of our improved behavioral detections are tuned specifically to detect scraping by analyzing signals that go beyond simple request headers. These include:

• Behavioral Analysis: Looking at session traversal paths, the sequence of requests, and interaction (or lack thereof) with dynamic page elements.

• Client Fingerprinting: Analyzing subtle signals from the client to identify signs of automation such as JA4 fingerprints in the context of the customer's specific traffic baseline.

• Content-Agnostic Detection: These models do not need to understand the content of a page, only the patterns of how it is being accessed. This makes them highly scalable and efficient, without actually using the unique content on a website to make judgement calls.

How do these scraping detections look, in practice? We validated our logic for detecting scraping with early adopters in a closed beta, in order to receive ground-truth feedback and tune our detections. As with any ideal detection, our goal is to capture as much malicious traffic as possible, without compromising the experience of legitimate website visitors. Looking at just a 24-hour period, our new scraping detections have caught hundreds of millions of requests, flagging 138 million scraping requests on just 5 of our early beta zones.

Naturally, we see an overlap with our existing system of bot scoring, but the numbers here show us concretely that our new method of behavioral detections have a completely new value add: 34% of the requests flagged by our new scraping detections would not have been detected by our existing bot score system, making us all the more eager to use these novel detections to inform the way we score automation.

Our mission to help build a better Internet means that when we develop powerful new defenses, we believe in democratizing access to them. Protecting the entire Internet from new and evolving threats requires raising the baseline of security for everyone.

In that spirit, we’re excited to announce that our enhanced behavioral detections will not only roll out to bot management customers, but will also benefit Cloudflare customers using our global Super Bot Fight Mode system. For our Enterprise Bot Management customers, we automatically tune our detections based on the exact traffic for each zone. Because these advanced models are trained on your zone’s specific traffic, they detect even the most evasive attacks: from account takeovers to web scraping to other attacks executed through residential proxy networks — and we consider this only the tip of the iceberg of behavioral bot profiling. 

Our initial focus on scraping is just the beginning of a new wave of behavioral bot detections. The infrastructure we’ve built is a flexible, powerful foundation for tackling a wide range of malicious behavior on your websites; the same principles of establishing a per-customer baseline and detecting anomalies can be applied to other critical threats that are unique to an application's logic, such as credential stuffing, inventory hoarding, carding attacks, and API abuse.

We are moving into an era where generic defenses are no longer enough. As threats become more personal, so must the defenses against them, and paving this path of behavioral detections is our latest gift to the Internet. Our first offering of scraping behavioral detections is just around the corner: customers will be able to turn on this new detection from the Security Overview page in their dashboard. 

(We’re always looking for enthusiastic humans to help us in our mission against bots! If you’re interested in helping us build a better Internet, check out our open positions.)

Browser developers can apply to join here. 

At Cloudflare, we aim to help build a better Internet. One way we achieve this is by providing website owners with the tools to detect and block unwanted traffic from bots through Cloudflare Challenges or Turnstile. As both bots and our detection systems become more sophisticated, the security checks required to validate human traffic become more complicated. While we aim to strike the right balance, we recognize these security measures can sometimes cause issues for legitimate browsers and their users.

A core objective of the program is to provide a space for intentional collaboration where we can work directly with browser developers to ensure that both accessibility and security can co-exist. We aim to support the evolving browser landscape, while upholding our responsibility to our customers to deliver the best security products. This program provides a dedicated channel for browser teams to share feedback, report issues, and help ensure that Cloudflare’s Challenges and Turnstile work seamlessly with all browsers.

Browser developers in the program will benefit from:

• A two-way communication channel to Cloudflare’s team dedicated to addressing browser-specific concerns, feedback, and issues.

• Best practices for building and testing against Cloudflare Challenges and Turnstile.

• A private community forum for updates, questions, and discussion between browser developers and Cloudflare engineers. 

• Early visibility into updates or changes to that may impact how your browser handles Cloudflare Challenges.

• (If applicable) Testing integration where we will incorporate your browser into our testing pipeline and monitor its performance with our releases.

This program is designed as a partnership where Cloudflare will, with our best effort, ensure our security products work properly with all browsers, while giving browser developers a voice in how these systems evolve. As an output of this program, we expect to publish clear browser requirements to run Cloudflare Challenges while striking the balance between openness and security. 

For end users browsing the web, we continue to support a wide range of browsers. We will continue to update this list based on the insights and collaborations from the Browser Developer Program. We are also committed to ensuring our Challenge interstitial pages and Turnstile provide clear, actionable UI/UX for any error or failed states, making it easier for you to understand and resolve issues you may encounter. 

If you are working on a browser and want to ensure your users have a seamless experience with Cloudflare-protected websites, we encourage you to apply here. 

We’ll ask for basic information about your project and ask you to sign our Browser Developer Program Agreement. In addition, we expect participants to adhere to our Community Code of Conduct and commit to constructive engagement.

Once you’re accepted, you’ll be invited to a private space in the Cloudflare Community where you can engage directly with our team. 

Cloudflare Challenges, a security mechanism to verify whether a visitor is a human or a bot, serve a wide variety of browsers in the world today. Chrome leads with 68.0%, Safari at 8.7%, Firefox at 6.3%, Edge at 4.8%, and Opera at 6.2%. However, the very long tail of browsers that collectively make up the remaining traffic, each representing less than 1% individually but together painting a picture of an incredibly diverse web ecosystem.

_{Browser traffic distribution, with 100+ browsers comprising the 'Other' category}

This diversity spans a wide range of environments, each with unique constraints and capabilities:

• Emerging and experimental browsers pushing the boundaries of web technology

• Privacy-focused browsers such as DuckDuckGo that prioritize user data protection

• Embedded browsers inside social media apps like Facebook, Instagram, and TikTok

• WebViews used by mobile applications

• Gaming and VR browsers such as Oculus for headsets and gaming consoles

• Smart device browsers built into classroom displays and home appliances

Supporting this level of diversity poses real engineering challenges. Many of these browsers deviate from standard assumptions. Some lack full support for modern Web APIs, others operate under more stringent data privacy policies, and some are optimized for environments where our script to verify visitors may be hindered or blocked from running properly. These browsers are not bad or malicious. But their behavior may fall outside the typical patterns observed in mainstream browsers, which can lead to problematic or failed Challenge flows which we would like to avoid.

From an engineering perspective, our job is to strike a difficult balance. If our logic is too rigid that it expects only the behaviors of the majority, we risk excluding legitimate users on less conventional platforms. But if we relax our standards too much, we increase the attack surface for abuse. We cannot overfit to the top 5 browsers, nor can we afford to treat all clients as equal in capability or trustworthiness.

The Browser Developer Program is one way to close this gap. By working directly with browser teams, especially those building for niche or emerging environments, we can better understand the constraints they operate under and collaborate to make each of our systems more compatible and resilient. 

This program is free to join, and is open to any browser developer, no matter the size or the lifecycle stage. Our goal is to listen, learn, and collaborate with browser developers to create a better experience for everyone. 

We believe this program will ultimately benefit end users the most. By joining this program, you will help us build solutions that prioritize both the security needs of businesses as well as the diverse ways people access the Internet. 

We look forward to your participation!

At Cloudflare, we are solving this complexity with Turnstile, our CAPTCHA alternative. And now, we’re taking the next step in advancing security with Ephemeral IDs, a new feature that generates a unique short-lived ID, without relying on any network-level information.

When a website visitor interacts with Turnstile, we now calculate an Ephemeral ID that can link behavior to a specific client instead of an IP address. This means that even when attackers rotate through large pools of IP addresses, we can still identify and block malicious actions. For example, in attacks like credential stuffing or account signups, where fraudsters attempt to disguise themselves using different IP addresses, Ephemeral IDs allow us to detect abuse patterns more accurately beyond just determining whether the visitor is a human or a bot. Multiple fraudulent actions from the same client are grouped together, improving our detection rate while reducing false positives.

Turnstile detects bots by analyzing browser attributes and signals. Using these aggregated client-side signals, we generate a short-lived Ephemeral ID without setting any cookies or using similar client-side storage. These IDs are intentionally not 100% unique and have a brief lifespan, making them highly effective in identifying patterns of fraud and abuse, without compromising user privacy.

When the same visitor interacts with Turnstile widgets from different Cloudflare customers, they receive different Ephemeral IDs for each one. Additionally, because these IDs change frequently, they cannot be used to track a single visitor over multiple days.

_{Blue: A single IP address | Green: A single Ephemeral ID The bigger the node, the more frequently seen that ID or IP address was in our dataset.}

The graphic above illustrates the complex reality of the modern Internet, where the relationship between clients and IP addresses is far from a simple one-to-one mapping. While some straightforward mappings still exist, they are no longer the norm.

During a period where a site or service is under attack, we observe a “nest” of highly correlated Ephemeral IDs. In the example below, the correlation is based on both Ephemeral ID and IP address.

_{Nest in the center of the diagram visualizes thousands of IP addresses (blue) which are correlated by the commonly identified Ephemeral IDs (green). The bigger the node, the more frequently seen that ID or IP address was in our dataset.}

This is real-world data showing fraudulent activity on one of Cloudflare’s public-facing forms. Even with access to a broad range of IP addresses, attackers struggle to completely disguise their requests because Ephemeral IDs are generated based on patterns beyond IP addresses. This means that even if they rotate addresses, the underlying client characteristics are still detected, making it harder for them to evade our security measures. This makes it easier for us to group these requests and apply appropriate business logic, whether that means discarding the requests, requiring further validation, enforcing multi-factor authentication (MFA), or other actions. 

This new client identification technology seamlessly integrates into the broader advancements we’ve made to Turnstile over the past year. Whether you’re protecting login forms, signup pages, or high value transactions, you’ll immediately benefit from this extra layer of abuse detection without needing to change a single line of code. We’ll take care of all the heavy lifting and analysis behind the scenes, and our system will continue to improve its accuracy and effectiveness over time.

What does this mean for you? Starting today, Turnstile will go beyond just identifying bots. All websites protected by Turnstile will automatically benefit from the integration of Ephemeral IDs into our detection logic. This means we can more effectively identify and penalize offending clients without impacting other users on the same network, or IP address, improving security and user experience for everyone.

Everyone benefits from the addition of Ephemeral IDs to the Challenge Platform, but for those who want to use it beyond that, the Ephemeral ID is available through the Turnstile siteverify response. A practical use case for Ephemeral IDs is preventing fraudulent account signups. Imagine a bad actor, a real person using a real device, creating hundreds of fake accounts while rotating IP addresses to avoid detection. By ingesting Ephemeral IDs and logging them alongside your account creation logs, you can set up alerts based on account creation thresholds in real-time or retroactively investigate suspicious activity. Even though Ephemeral IDs are short-lived and may have changed by the time an investigation begins, they still provide valuable insights through aggregate analysis, and provide an extra dimension to identify fraud and abuse.

For our Turnstile Enterprise and Bot Management Enterprise customers, you now have the option to access Ephemeral IDs directly through the Turnstile siteverify response. Get in touch with your Account Executive to enable it on your account.

Below is an example of siteverify response for those who have enabled Ephemeral IDs.

curl 'https://challenges.cloudflare.com/turnstile/v0/siteverify' --data 'secret=verysecret&response=<RESPONSE>'

{
    "success": true,
    "error-codes": [],
    "challenge_ts": "2024-09-10T17:29:00.463Z",
    "hostname": "example.com",
    "metadata": {
        "ephemeral_id": "x:9f78e0ed210960d7693b167e"
    }
}

We launched Turnstile with a bold mission: to redefine CAPTCHAs with a frictionless, privacy-first solution that eliminates the annoyance of picking puzzles, selecting stoplights, and clicking crosswalks to prove our humanity. It’s incredible to think that Turnstile has been generally available for a whole year now! During this time, it has blocked over one trillion bots, and is actively protecting more than 350,000 domains worldwide.

As we celebrate Turnstile’s second birthday, we’re proud of the progress we’ve made and thrilled to introduce our latest innovations. While Ephemeral IDs represent the newest evolution of Turnstile, they’re part of our ongoing commitment to continuous improvement. Over the past year, we’ve also introduced a Cloudflare Pages Plugin and partnered with Google Firebase, ensuring that developers have easy access to Turnstile.

Earlier this year, we also launched Pre-Clearance for Turnstile, integrating it with Cloudflare WAF’s Challenge action, making it easier for customers to use Cloudflare’s Application Security products together. If you want to learn more about how to use Turnstile with Cloudflare’s Bot Management and WAF in more detail, check it out here!

We’re incredibly excited about what’s ahead. The introduction of Ephemeral IDs is just one of many innovations on the horizon. We’re committed to making the Internet a safer, more private place for everyone, eliminating the need for frustrating CAPTCHA puzzles while keeping security our top priority. And with our free tier remaining open and unlimited for all, there’s no barrier to getting started with Turnstile today.

Join us in revolutionizing online security – get started with Turnstile now or dive straight into our how-to guides. Let’s help make the Internet a better place, together!