LLMs
BlindChat - Our Confidential AI Assistant
Introducing BlindChat, a confidential AI assistant prioritizing user privacy through secure enclaves. Learn how it addresses data security concerns in AI applications.
Privacy Risks of LLM Fine-Tuning
This article explores privacy risks in using large language models (LLMs) for AI applications. It focuses on the dangers of data exposure to third-party providers during fine-tuning and the potential disclosure of private information through LLM responses.
Introducing BlindChat Local: Full In-Browser Confidential AI Assistant
Discover BlindChat, an open-source privacy-focused conversational AI that runs in your web browser, safeguarding your data while offering a seamless AI experience. Explore how it empowers users to enjoy both privacy and convenience in this transformative AI solution.
Introducing BlindLlama, Zero-Trust AI APIs With Privacy Guarantees & Traceability
Introducing BlindLlama: An open-source Zero-trust AI API. Learn how BlindLlama ensures confidentiality and transparency in AI deployment.
The Enterprise Guide to Adopting GenAI: Use Cases, Tools, and Limitations
Generative AI is revolutionizing enterprises with enhanced efficiency and customer satisfaction. The article explores real-world applications and deployment options like SaaS, on-VPC commercial FMs, and on-VPC open-source FMs, emphasizing the need for data protection.
Attacks on AI Models: Prompt Injection vs. Supply Chain Poisoning
Comparison of prompt injection & supply chain poisoning attacks on AI models, with a focus on a bank assistant. Prompt injection has a limited impact on individual sessions, while supply chain poisoning affects the entire supply chain, posing severe risks.
Open Source Is Crucial for AI Transparency but Needs More Tooling
AI model traceability is crucial, but open-source practices alone are inadequate. Combining new software and hardware-based tools with open sourcing offers potential solutions for a secure AI supply chain.
Ai-Assisted Code Generation With Privacy Guarantees: Securely Deploy SantaCoder With BlindBox on Azure
In this article, we'll demonstrate how you can efficiently analyze code at scale while maintaining privacy. We'll use BlindBox, our open-source secure enclave tooling, to serve StarCoder with privacy guarantees on Azure.
Mithril X Tramscribe: Confidential LLMs for Medical Voice Notes Analysis
How we partnered with Tramscribe to leverage LLMs deal with Medical voice notes analysis
Mithril Security Raised €1.2 Million to Protect LLM Users' Data
With BlindBox, you can use Large Language Models without any intermediary or model owner seeing the data sent to the models. This type of solution is critical today, as the newfound ease-of-use of generative AI (GPT4, MidJourney, GitHub Copilot…) is already revolutionizing the tech industry.
Announcing Blindbox, a Secure Infrastructure Tooling to Deploy LLMs, Available on Confidential Containers on Azure Container Instances
We are excited to introduce BlindBox, our latest open-source solution designed to enhance SaaS deployment security. Our tooling enables developers to wrap any Docker image with isolation layers and deploy them inside Confidential Containers.