AI for DevSecOps, WhiteRabbitNeo

The First AI Model Built to Think and Act Like a DevSecOps Engineer

WhiteRabbitNeo V3 is a 7B open-weight LLM fine-tuned for real-world DevSecOps workflows like red teaming, IaC analysis, exploit generation, and threat remediation. Trained on live incident data and taxonomy-informed tasks, V3 goes beyond code parsing to deliver autonomous decision-making and tool use.

It can chain vulnerabilities, fix misconfigurations, and maintain context over long investigations. It outperforms larger models on Cybench and runs locally, even on air-gapped infrastructure. No censors, no hand-holding, just a security-native model built to do the dirty work.

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Open source, uncensored AI for DevSecOps

Used by more than 1400 enterprise companies, each with $100M+ in annual revenue, WhiteRabbitNeo is the leading model to drive Gen AI value for (Dev)SecOps teams. Automate your manual SecOps tedium, so DevSecOps professionals can focus on creating innovative solutions to more complex problems.

About WhiteRabbitNeo

Late-2023, our Founder, Migel Tissera, searched for an uncensored, open source AI model to help him find and remediate security vulnerabilities. After not finding anything, he decided to build it.

We are working to create the largest and best security datasets to train the best coding LLMs and support our community with all of their Red Team, Blue Team, DevSecOps, and security education needs.

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Our Mission

We strive to be the best uncensored Gen AI security model available anywhere.

1. Continually evaluate base models looking for the best coding LLMs available.

2. Maintain the most comprehensive training data-set for cybersecurity that's currently available.

3. Work to avoid model censorship, prompt by prompt.

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Contributors Welcome

We are always happy to meet like-minded devs who are interested in contributing to this open source project. If you have ideas, or would like to discuss ways to help, we invite you to use the Contact form below.

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Features

WhiteRabbitNeo’s newest release, built on Qwen 2.5, which is the leader in several coding benchmarks, is available in the 7B parameter model (on HuggingFace) or the 32B parameter model on WhiteRabbitNeo.com which is available through our sponsor, Kindo AI.

This new Qwen series are trained on 17X more real-world data sources than the previous series, but we’ve ensured the previous models are still available on HuggingFace, (including our previous series, built on the 70B Llama model).

The new data sources include Indicator of Compromise (IoC), threat actor data from open source threat intelligence networks, Common Vulnerabilities and Exposures (CVE), technical vulnerability data from the National Vulnerability Database (NVD), plus a deep (and broad) range of enterprise infrastructure and security tool suite documentation.

Uncensored AI Models

While the foundation AI models (from OpenAI, Anthropic, Google, and Meta) censor their outputs for many security use cases, WhiteRabbitNeo is uncensored and trained to act like a modern adversary. It has a deep knowledge of threat intelligence, software engineering, even infrastructure as code, making it ideally suited for DevSecOps tasks and offloading tedium.

WhiteRabbitNeo’s newest release, built on Qwen 2.5, added real-world data sources from Indicator of Compromise (IoC), threat actor data from open source threat intelligence networks, Common Vulnerabilities and Exposures (CVE), technical vulnerability data from the National Vulnerability Database (NVD), plus a range of enterprise infrastructure and security tool suite documentation.

WhiteRabbitNeo is a project from Kindo AI

WhiteRabbitNeo is an open source project sponsored by Kindo AI, an enterprise security and infrastructure company focused on Gen AI for DevSecOps.

Kindo helps secure and automate enterprise infrastructure with Gen AI. Through their platform, enterprises can construct Agents that automate tedious Runbook tasks within existing systems of record such as IT ticketing systems, CI/CD systems, and modern infrastructure (on-prem,cloud, and hybrid environments).

Through Kindo, you can use WhiteRabbitNeo in enterprise environments to automate Runbook tasks for incident response, reviewing/managing infrastructure as code (IAC), and security vulnerability remediation – all while leveraging your existing SSO, enterprise identity infrastructure, and Digital Loss Prevention (DLP) filters to screen for sensitive data, and more.

If you're interested in joining Kindo as a sponsor, we invite you to request information, using the Contact form below.

Learn more about Kindo