10 stories tagged Data Security
OpenAI parted ways with three safety researchers after an internal investigation found they mishandled sensitive company information, according to a Wall Street Journal report.
A new arXiv study identifies the 'attestation deficit' — a structural gap where 78% of organizations using AI have governance policies but cannot produce auditable, tamper-evident proof of enforcement. Drawing on the Stanford 2026 AI Index Report and IBM/Ponemon 2026 Cost of a Data Breach study, the research shows this leaves companies vulnerable to regulatory penalties and data breaches averaging USD 4.99 million.
Anthropic's Claude AI shared chat and Artifact links may have been indexed by Google, potentially exposing private conversations. Users are advised to check and revoke access to any shared links immediately.
A new study highlights how AI models can accidentally expose sensitive training data. This raises privacy concerns and challenges for AI developers. Researchers propose ways to mitigate these risks.
Apple is revamping Siri with a focus on privacy, including auto-deleting chat history. This move could make Siri more appealing to users concerned about data security.
Thoth is an open-source AI assistant that runs on your own devices, keeping your data private. It's designed to be a simple, powerful alternative to cloud-based AI helpers.
OpenAI has released a new tool to help developers build web apps that protect user privacy. This filter ensures sensitive data isn't exposed in AI interactions.
A new AI usage analytics tool acts as a proxy to enforce budget limits and redact personally identifiable information before requests reach the provider. It offers real-time cost tracking and immediate suspension when thresholds are breached.
OpenAI has released an open-weight model designed to detect and redact personally identifiable information (PII) in text with state-of-the-art accuracy. This tool aims to enhance data privacy across various applications.
Startups are grappling with how to safely provide AI/ML teams with production database access. The challenge differs from traditional BI tools in ways that aren't yet fully understood. The question of where agents should connect—primary, read replica, or warehouse—remains unresolved.