![](\"https:\/\/mms.businesswire.com\/media\/20260804897594\/en\/2867255\/5\/Ridge_logo.jpg\"){kind=logo}
<\/a><\/a>\nThe launch comes as artificial intelligence reshapes both software development and cyberattacks. As AI accelerates code generation and enables attackers to discover and weaponize vulnerabilities faster than ever before, traditional vulnerability scanners and periodic penetration tests are struggling to keep pace. Even existing automated penetration testing tools often fall short, providing limited findings that can leave organizations with a false sense of security. Security teams are increasingly overwhelmed with alerts but lack the evidence needed to determine which vulnerabilities represent real business risks and how to implement rapid remediation.<\/p>
\nRidgeGen addresses this challenge by augmenting AI models with Ridge Security\u2019s proprietary security knowledge base, specialized tooling, and enterprise-grade agentic AI framework. It combines AI reasoning with deterministic controls that keep security testing safe, auditable, and explainable. By separating AI reasoning from authority, enforcement, and verification, RidgeGen enables organizations to safely deploy autonomous offensive security while maintaining strict governance over targets, credentials, and testing policies.<\/p>
\n\"AI has fundamentally changed offensive security,\" said Lydia Zhang, President of Ridge Security. \"In today's post-Mythos world, defenders must adopt an offensive mindset. Security teams need to operate with the same level of intelligence and at the same speed as their attackers. RidgeGen delivers what enterprises need: safety, efficiency, explainability, organizational knowledge, and adaptation to each customer's unique environment.\"<\/p>
\nAccording to Jason English, Director and Principal Analyst at Intellyx, organizations face a growing gap between AI adoption and their ability to secure it.<\/p>
\nEnglish says, \"Whether driven by top-line improvement goals for better customer experience and agility, or bottom-line efficiency and productivity metrics, agentic AI is a promising value lever companies are pulling today. Continuous agentic security testing doesn\u2019t just put a 'human in the loop.' Expert offensive agents can give security teams more context, less noise, and better visibility of the most significant risks, so everyone can breathe a little easier with each push to production.\u201d<\/p>
\nUnlike traditional security testing tools that identify potential issues based on signatures or known CVEs, RidgeGen autonomously investigates how attackers could chain together vulnerabilities, business logic flaws and misconfigurations to compromise an environment. Every finding is validated with reproducible evidence before being surfaced, dramatically reducing false positives and false negatives and enabling security teams to prioritize exploitable risk rather than theoretical exposure.<\/p>
\nWhile RidgeGen is designed to be model-agnostic and supports flexible deployment options, including on-premises environments, its development and benchmark testing framework were built on Google Cloud. Throughout the development process, Gemini served as a key baseline model for evaluating performance, reliability, and cost efficiency. Our benchmark testing across multiple leading AI models demonstrated that Gemini delivers a strong balance of performance and cost efficiency, making it a highly effective foundation for enterprise-grade agentic AI security applications.<\/p>
\nKey capabilities include:<\/p>
- \n
- \nAutonomous agentic AI red teaming and offensive security testing<\/li>\n
- \nEvidence-backed verification that eliminates false positives and AI hallucinations<\/li>\n
- \nDiscovery of complex multi-step attack chains and business logic vulnerabilities<\/li>\n
- \nClick-away remediation guidance generated from validated findings<\/li>\n
- \nRuntime guardrails that enforce safe, supervised and authorized testing modes<\/li>\n
- \nSecure credential handling through SafeBox, preventing sensitive data from entering AI model prompts or memory<\/li>\n
- \nModel-agnostic architecture supporting leading commercial and self-hosted AI models<\/li>\n
- \nOn-premises deployment options that keep customer data and evidence within enterprise environments<\/li>\n<\/ul>
\nRidgeGen complements RidgeBot, Ridge Security's AI-powered continuous security validation platform. Together, the two solutions provide organizations with continuous visibility across their attack surface while delivering deep, autonomous validation of high-value targets \u2013 creating a unified \u201cfind, prove and fix\u201d approach to Continuous Threat Exposure Management (CTEM).<\/p>
\nThe platform is available immediately for enterprise organizations and managed security service providers worldwide.<\/p>
\nAbout Ridge Security<\/b><\/p>
\nRidge Security empowers CISOs to build cyber resilience through AI-native continuous offensive security. By helping organizations continuously validate their security posture, focus on proven cyber risks, and accelerate remediation, Ridge Security enables security teams to stay ahead of evolving threats while maximizing the effectiveness of their existing security investments. Recognized by Gartner and Frost & Sullivan, Ridge Security serves enterprises worldwide across financial services, government, telecommunications, and other critical industries.<\/p>
\nFor more information, go to https:\/\/ridgesecurity.ai\/<\/a>.<\/p>
\nMedia Contacts:<\/b>