Ridge Security’s RidgeOne keeps autonomous penetration testing data inside customer environments

Ridge Security has announced RidgeOne, a self-contained solution that brings autonomous AI-powered penetration testing and agentic red teaming to mid-sized organizations.

Combining Ridge Security’s RidgeGen agentic security validation platform with an open-weight AI model running on NVIDIA DGX Spark, RidgeOne enables organizations to perform deep security testing within their own environment without sending sensitive testing data to an external AI provider or incurring ongoing AI token costs.

For organizations with limited AI or security resources, accessing advanced security testing capabilities can be a challenge. RidgeOne is designed to make autonomous security testing easier to deploy and more accessible, giving organizations a way to use AI-driven offensive security without having to build their own AI infrastructure or maintain a separate AI environment.

“AI is changing the way security teams can approach offensive security, but organizations shouldn’t need a larger AI team or a complicated infrastructure project to take advantage of it,” said George Duo, VP of Product Management, Ridge Security. “We built RidgeOne to make autonomous security testing practical for organizations that want access to this technology while keeping control of their data, infrastructure and testing process.”

RidgeOne is designed to provide several practical advantages:

The solution is built around a validated reference configuration based on the NVIDIA DGX Spark compact AI system, with 128 GB of unified memory shared between the AI model and RidgeGen. RidgeOne can be deployed in a VMware environment and brought online in five steps, without requiring customers to build separate AI infrastructure.

In testing, Ridge Security ran RidgeOne against OWASP Juice Shop and completed a full autonomous penetration test without operator involvement. The assessment produced 32 verified findings, including 19 critical and high-severity findings, over approximately 10 hours, without making any external AI calls. The system also connected separate findings into a multi-step attack path.

That ability to connect the dots is central to RidgeGen. Rather than stopping at individual vulnerabilities, the platform can reason across findings, test whether weaknesses can be chained together and provide evidence that security teams can use to prioritize fixes.

As attackers increasingly use AI to automate and accelerate their operations, organizations need ways to put the same technology to work on the defensive side. RidgeOne gives security teams a portable way to bring autonomous testing capabilities into their own environments, whether they are testing a corporate network, a restricted segment or a different environment altogether.

“Autonomous security testing is changing what security teams can do, but autonomy has to come with control,” said Lydia Zhang , President of Ridge Security. “RidgeOne gives organizations a practical way to bring AI-powered offensive security into their own environments while maintaining control over the data, the infrastructure and the testing process.”