Ridge Security Released Autonomous Pen-Testing Tool
The new RidgeOne solution moves penetration testing to local hardware to eliminate data exposure and cloud token costs.
Updated on Oct. 13, 2026 in Cybersecurity
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Ridge Security has released RidgeOne, an autonomous penetration testing solution that operates entirely within a customer's local VMware environment. By utilizing local hardware, the system removes the need to transmit sensitive vulnerability data to third-party AI providers.
Why it matters
The solution addresses the dual challenges of data privacy and unpredictable cloud costs by shifting AI-driven security workflows to dedicated infrastructure. This allows organizations to run continuous security audits without incurring ongoing token-based expenses.
The system runs on NVIDIA DGX Spark hardware equipped with 128 GB of unified memory. Testing against the OWASP Juice Shop resulted in 32 verified findings, 19 of which were categorized as critical or high-severity, over a 10-hour period.
The players
Ridge Security
A cybersecurity firm specializing in autonomous penetration testing and vulnerability management software.
NVIDIA
A semiconductor company that designs high-performance computing hardware, including the DGX platforms used for AI workloads.
The details
RidgeOne uses the RidgeGen platform to reason across individual security vulnerabilities, effectively chaining them together to identify multi-step attack paths. The system utilizes open-weight AI models—artificial intelligence models where the internal parameters are publicly accessible—running locally to maintain data sovereignty. By deploying within VMware, the software integrates into existing enterprise virtualization stacks.
Timeline
October 13, 2026: Ridge Security announced the official release of RidgeOne.
The Tech Race
Automated penetration testing is increasingly moving toward locally hosted AI to minimize the risks associated with cloud-based data processing. RidgeOne competes with cloud-native security agents by prioritizing private, hardware-accelerated inference.
Enterprise security teams can now deploy autonomous testing within their own VMware-based private clouds to maintain strict data boundaries. The move to locally-run hardware eliminates per-token costs typically associated with cloud-based AI security platforms.
The takeaway
RidgeOne demonstrates that autonomous penetration testing can be performed effectively without external AI dependencies. Organizations should monitor future benchmark reports to see how the system handles more complex enterprise-grade network environments.
Further reading
For broader insights on how modern security teams are automating risk assessment, visit Cybersecurity.
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Do you trust local, self-contained AI systems more than cloud-based alternatives for handling sensitive security data?
