Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The GitHub Outage: How AI-Native SASE Visibility Turns Disruption into Decision

On August 17, 2026 at 13:40 UTC, GitHub first publicly logged that it was investigating elevated errors and latency issues, later reporting broad impact across web and API traffic, Git operations, Actions, Pull Requests, Issues, Pages, Webhooks, and identity-related services. The outage had significant implications for development teams. When GitHub degrades, developer workflows can stop quickly.

Agentic Attacks Require Agentic Threat Prevention

AI-powered attacks are moving faster, adapting in seconds, and overwhelming traditional defenses with machine-speed activity. In this video, Jason Wright explains why security teams need Agentic Threat Defense built on customized predictions, automatic adaptation, and cloud-native scale. Watch how Cato Agentic Threat Prevention helps reduce the risk of AI-powered threats, stop adaptive attacks earlier, and scale prevention to stop agentic attacks.

Defending at machine speed: Predict, Adapt, Stop Agentic Attacks

AI-powered adversaries are accelerating vulnerability discovery and automating attacks. For security teams, the challenge is adaptive attack chains, machine-speed execution, and attack volumes beyond manual workflows. Cato is redefining prevention in the AI era—predicting enterprise-specific attack paths, adapting protections at machine speed, and scaling defense with cloud-native scale. This means enterprises can do more than just react to attacks, they can prevent them.