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.

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.

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.

Cloudflare has been part of a multivendor, industry-wide effort to mitigate two critical DNSSEC vulnerabilities. These vulnerabilities exposed significant risks to critical infrastructures that provide DNS resolution services. Cloudflare provides DNS resolution for anyone to use for free with our public resolver 1.1.1.1 service. Mitigations for Cloudflare’s public resolver 1.1.1.1 service were applied before these vulnerabilities were disclosed publicly.

Cloudflare’s Bot Management is used by organizations around the world to proactively detect and mitigate automated bot traffic. To do this, Cloudflare leverages machine learning models that help predict whether a particular HTTP request is coming from a bot or not, and further distinguishes between benign and malicious bots. Cloudflare serves over 55 million HTTP requests per second — so our machine learning models need to run at Cloudflare scale.

As more organizations collectively progress toward adopting a SASE architecture, it has become clear that the traditional SASE market definition (SSE + SD-WAN) is not enough. It forces some teams to work with multiple vendors to address their specific needs, introducing performance and security tradeoffs. More worrisome, it draws focus more to a checklist of services than a vendor’s underlying architecture.