Take control of public AI application security with Cloudflare’s Firewall for AI

Imagine building an LLM-powered assistant trained on your developer documentation and some internal guides to quickly help customers, reduce support workload, and improve user experience. Sounds great, right? But what if sensitive data, such as employee details or internal discussions, is included in the data used to train the LLM? Attackers could manipulate the assistant into exposing sensitive data or exploit it for social engineering attacks, where they deceive individuals or systems into revealing confidential details, or use it for targeted phishing attacks. Suddenly, your helpful AI tool turns into a serious security liability. 

Introducing Firewall for AI: the easiest way to discover and protect LLM-powered apps

Today, as part of Security Week 2025, we’re announcing the open beta of Firewall for AI, first introduced during Security Week 2024. After talking with customers interested in protecting their LLM apps, this first beta release is focused on discovery and PII detection, and more features will follow in the future.

If you are already using Cloudflare application security, your LLM-powered applications are automatically discovered and protected, with no complex setup, no maintenance, and no extra integration needed.

Firewall for AI is an inline security solution that protects user-facing LLM-powered applications from Continue reading

Cloudflare for AI: supporting AI adoption at scale with a security-first approach

AI is transforming businesses — from automated agents performing background workflows, to improved search, to easier access and summarization of knowledge. 

While we are still early in what is likely going to be a substantial shift in how the world operates, two things are clear: the Internet, and how we interact with it, will change, and the boundaries of security and data privacy have never been more difficult to trace, making security an important topic in this shift.

At Cloudflare, we have a mission to help build a better Internet. And while we can only speculate on what AI will bring in the future, its success will rely on it being reliable and safe to use.

Today, we are introducing Cloudflare for AI: a suite of tools aimed at helping businesses, developers, and content creators adopt, deploy, and secure AI technologies at scale safely.

Cloudflare for AI is not just a grouping of tools and features, some of which are new, but also a commitment to focus our future development work with AI in mind.

Let’s jump in to see what Cloudflare for AI can deliver for developers, security teams, and content creators…

For developers

If you Continue reading

Trapping misbehaving bots in an AI Labyrinth

Today, we’re excited to announce AI Labyrinth, a new mitigation approach that uses AI-generated content to slow down, confuse, and waste the resources of AI Crawlers and other bots that don’t respect “no crawl” directives. When you opt in, Cloudflare will automatically deploy an AI-generated set of linked pages when we detect inappropriate bot activity, without the need for customers to create any custom rules.

AI Labyrinth is available on an opt-in basis to all customers, including the Free plan.

Using Generative AI as a defensive weapon

AI-generated content has exploded, reportedly accounting for four of the top 20 Facebook posts last fall. Additionally, Medium estimates that 47% of all content on their platform is AI-generated. Like any newer tool it has both wonderful and malicious uses.

At the same time, we’ve also seen an explosion of new crawlers used by AI companies to scrape data for model training. AI Crawlers generate more than 50 billion requests to the Cloudflare network every day, or just under 1% of all web requests we see. While Cloudflare has several tools for identifying and blocking unauthorized AI crawling, we have found that blocking malicious bots can alert the attacker that you are Continue reading

An early look at cryptographic watermarks for AI-generated content

Generative AI is reshaping many aspects of our lives, from how we work and learn, to how we play and interact. Given that it's Security Week, it's a good time to think about some of the unintended consequences of this information revolution and the role that we play in bringing them about.

Today's web is full of AI-generated content: text, code, images, audio, and video can all be generated by machines, normally based on a prompt from a human. Some models have become so sophisticated that distinguishing their artifacts — that is, the text, audio, and video they generate — from everything else can be quite difficult, even for machines themselves. This difficulty creates a number of challenges. On the one hand, those who train and deploy generative AI need to be able to identify AI-created artifacts they scrape from websites in order to avoid polluting their training data. On the other hand, the origin of these artifacts may be intentionally misrepresented, creating myriad problems for society writ large.

Part of the solution to this problem might be watermarking. The basic idea of watermarking is to modify the training process, the inference process, or both so that an artifact of Continue reading

How we train AI to uncover malicious JavaScript intent and make web surfing safer

Modern websites rely heavily on JavaScript. Leveraging third-party scripts accelerates web app development, enabling organizations to deploy new features faster without building everything from scratch. However, supply chain attacks targeting third-party JavaScript are no longer just a theoretical concern — they have become a reality, as recent incidents have shown. Given the vast number of scripts and the rapid pace of updates, manually reviewing each one is not a scalable security strategy.

Cloudflare provides automated client-side protection through Page Shield. Until now, Page Shield could scan JavaScript dependencies on a web page, flagging obfuscated script content which also exfiltrates data. However, these are only indirect indicators of compromise or malicious intent. Our original approach didn’t provide clear insights into a script’s specific malicious objectives or the type of attack it was designed to execute.

Taking things a step further, we have developed a new AI model that allows us to detect the exact malicious intent behind each script. This intelligence is now integrated into Page Shield, available to all Page Shield add-on customers. We are starting with three key threat categories: Magecart, crypto mining, and malware.

Screenshot of Page Shield dashboard showing results of three types of analysis.

With Continue reading

Comparing IP and CLNP: Network State Summarization

In the previous blog posts, we discussed how TCP/IP and CLNP reach adjacent nodes and build ARP/ND/ES caches and how they reach off-subnet nodes. Now, let’s move from the network edge into the network core and explore how the two protocol stacks reduce the amount of information they have to propagate in routing protocols.

While I’m not exactly an OSI fan, I must admit they got many things right (and IPv6 copied those ideas), but TCP/IP is a clear winner in this aspect.

Read more …

Nvidia Draws GPU System Roadmap Out To 2028

High tech companies always have roadmaps. Whether or not they show them to the public, they are always showing them to key investors if they are in their early stages, getting ready to sell some shares on Wall Street to make money – literally, going public – or talking to key customers who are interested in buying a platform, not just a point product to solve a problem today. …

Nvidia Draws GPU System Roadmap Out To 2028 was written by Timothy Prickett Morgan at The Next Platform.

PP054: Understanding WireGuard and Overlay VPNs with Tom Lawrence

WireGuard and other overlay VPNs are the focus of today’s podcast with guest Tom Lawrence from Lawrence Systems. We dig into differences between WireGuard and traditional IPSec VPNs, how WireGuard’s opinionated approach to crypto suites helps improve its performance, and how WireGuard compares to OpenVPN. We also look at the broader category of overlay VPNs... Read more »

Extending Cloudflare Radar’s security insights with new DDoS, leaked credentials, and bots datasets

Security and attacks continues to be a very active environment, and the visibility that Cloudflare Radar provides on this dynamic landscape has evolved and expanded over time. To that end, during 2023’s Security Week, we launched our URL Scanner, which enables users to safely scan any URL to determine if it is safe to view or interact with. During 2024’s Security Week, we launched an Email Security page, which provides a unique perspective on the threats posed by malicious emails, spam volume, the adoption of email authentication methods like SPF, DMARC, and DKIM, and the use of IPv4/IPv6 and TLS by email servers. For Security Week 2025, we are adding several new DDoS-focused graphs, new insights into leaked credential trends, and a new Bots page to Cloudflare Radar.  We are also taking this opportunity to refactor Radar’s Security & Attacks page, breaking it out into Application Layer and Network Layer sections.

Below, we review all of these changes and additions to Radar.

Layered security

Since Cloudflare Radar launched in 2020, it has included both network layer (Layers 3 & 4) and application layer (Layer 7) attack traffic insights on a single Security & Attacks page. Over Continue reading

Upgraded Turnstile Analytics enable deeper insights, faster investigations, and improved security

Attackers are increasingly using more sophisticated methods to not just brute force their way into your sites but also simulate real user behavior for targeted harmful activity like account takeovers, credential stuffing, fake account creation, content scraping, and fraudulent transactions. They are no longer trying to simply take your website down or gain access to it, but rather cause actual business harm. There is also the increasing complexity added by attackers rotating IP addresses, routing through proxies, and using VPNs. In this evolving security landscape, meaningful analytics matter. Many traditional CAPTCHA solutions provide simplistic pass or fail trends on challenges without insights into traffic patterns or behavior. Cloudflare Turnstile aims to equip you with more than just basic trends, so you can make informed decisions and stay ahead of the attackers. 

We are excited to introduce a major upgrade to Turnstile Analytics. With these upgraded analytics, you can identify harder-to-detect bots faster, and fine-tune your bot security posture with less manual log analysis than before. Turnstile, our privacy-first CAPTCHA alternative, has been helping you protect your applications from automated abuse while ensuring a seamless experience for legitimate users. Now, using enhanced analytics, you can gain deeper insights into Continue reading

Cloudflare enables native monitoring and forensics with Log Explorer and custom dashboards

In 2024, we announced Log Explorer, giving customers the ability to store and query their HTTP and security event logs natively within the Cloudflare network. Today, we are excited to announce that Log Explorer now supports logs from our Zero Trust product suite. In addition, customers can create custom dashboards to monitor suspicious or unusual activity.

Every day, Cloudflare detects and protects customers against billions of threats, including DDoS attacks, bots, web application exploits, and more. SOC analysts, who are charged with keeping their companies safe from the growing spectre of Internet threats, may want to investigate these threats to gain additional insights on attacker behavior and protect against future attacks. Log Explorer, by collecting logs from various Cloudflare products, provides a single starting point for investigations. As a result, analysts can avoid forwarding logs to other tools, maximizing productivity and minimizing costs. Further, analysts can monitor signals specific to their organizations using custom dashboards.

Zero Trust dataset support in Log Explorer

Log Explorer stores your Cloudflare logs for a 30-day retention period so that you can analyze them natively and in a single interface, within the Cloudflare Dashboard. Cloudflare log data is diverse, reflecting the breadth of capabilities Continue reading

One platform to manage your company’s predictive security posture with Cloudflare

In today’s fast-paced digital landscape, companies are managing an increasingly complex mix of environments — from SaaS applications and public cloud platforms to on-prem data centers and hybrid setups. This diverse infrastructure offers flexibility and scalability, but also opens up new attack surfaces.

To support both business continuity and security needs, “security must evolve from being reactive to predictive”. Maintaining a healthy security posture entails monitoring and strengthening your security defenses to identify risks, ensure compliance, and protect against evolving threats. With our newest capabilities, you can now use Cloudflare to achieve a healthy posture across your SaaS and web applications. This addresses any security team’s ultimate (daily) question: How well are our assets and documents protected?

A predictive security posture relies on the following key components:

  • Real-time discovery and inventory of all your assets and documents

  • Continuous asset-aware threat detection and risk assessment

  • Prioritised remediation suggestions to increase your protection

Today, we are sharing how we have built these key components across SaaS and web applications, and how you can use them to manage your business’s security posture.

Your security posture at a glance

Regardless of the applications you have connected to Cloudflare’s global network, Cloudflare actively scans Continue reading

Unleashing improved context for threat actor activity with our Cloudforce One threat events platform

Today, one of the greatest challenges that cyber defenders face is analyzing detection hits from indicator feeds, which provide metadata about specific indicators of compromise (IOCs), like IP addresses, ASNs, domains, URLs, and hashes. While indicator feeds have proliferated across the threat intelligence industry, most feeds contain no contextual information about why an indicator was placed on the feed. Another limitation of most feeds today is that they focus solely on blockable indicators and cannot easily accommodate more complex cases, such as a threat actor exploiting a CVE or an insider threat. Instead, this sort of complex threat intelligence is left for long form reporting. However, long-form reporting comes with its own challenges, such as the time required for writing and editing, which can lead to significant delays in releasing timely threat intelligence.

To help address these challenges, we are excited to launch our threat events platform for Cloudforce One customers. Every day, Cloudflare blocks billions of cyber threats. This new platform contains contextual data about the threats we monitor and mitigate on the Cloudflare network and is designed to empower security practitioners and decision makers with actionable insights from a global perspective. 

On average, we process 71 Continue reading

Worth Reading: Standards for ANSI Escape Codes

I encountered the Escape sequences (named after the first character in the sequence) while programming stuff that would look nicely on the venerable VT100 terminals (not to mention writing one or two VT100 emulators myself).

In the meantime, those sequences got standardized and (par for the course) extended with “proprietary” stuff everyone uses now. Julia Evans did a great job documenting the state of the art. Thanks a million!

Tensor Parallelism

 The previous section described how Pipeline Parallelism distributes entire layers across multiple GPUs. However, Large Language Models (LLMs) based on transformer architectures contain billions of parameters, making this approach insufficient.

For example, GPT-3 has approximately 605 million parameters in a single self-attention layer and about 1.2 billion parameters in a feedforward layer, and these figures apply to just one transformer block. Since GPT-3 has 96 transformer blocks, the total parameter count reaches approximately 173 billion. When adding embedding and normalization parameters, the total increases to roughly 175 billion parameters.

The number of parameters in a single layer alone often exceeds the memory capacity of a single GPU, making Pipeline Parallelism insufficient. Additionally, performing large matrix multiplications on a single GPU would be extremely slow and inefficient. Tensor Parallelism addresses this challenge by splitting computations within individual layers across multiple GPUs rather than assigning whole layers to separate GPUs, as done in Pipeline Parallelism.

Chapter 7 introduces Transformer architecture but for memory refreshing, figure 8-15 illustrates a stack of decoder modules in a transformer architecture. Each decoder module consists of a Self-Attention layer and a Feedforward layer. The figure also shows how an input word, represented by x1, is first Continue reading

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