Access control
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X @Sui
Sui· 2025-11-05 18:21
Today’s Web2 cloud-based “access systems” still think it’s 2010.They guard APIs, not data - they don’t understand time, context, or ownership, only endpoints.Builders use third-party infra for app-level access control, adding complexity and fragility.Seal fixes that. https://t.co/l1bQugGSuh ...
X @Sui
Sui· 2025-09-03 17:21
RT MystenLabs.sui (@Mysten_Labs)Seal just launched on Sui Mainnet, and builders are already putting it to work.From token-gated content to confidential AI data, here’s how top teams are using Seal to add programmable privacy and access control to their apps 👇 https://t.co/azNIy56zk8 ...
X @Sui 「🦑」
Sui· 2025-07-28 20:22
Blockchain Technology Innovation - Blockchain wallets are traditionally static keys tied to users, but Sui introduces programmable, transferable wallets [1] - @ikadotxyz enables this innovation on Sui, transforming wallets into programmable objects [1] - DWalletCap unlocks new design patterns for asset ownership and access control within the blockchain ecosystem [1]
What does Enterprise Ready MCP mean? — Tobin South, WorkOS
AI Engineer· 2025-06-27 09:31
MCP and AI Agent Development - MCP is presented as a way of interfacing between AI and external resources, enabling functionalities like database access and complex computations [3] - The industry is currently focused on building internal demos and connecting them to APIs, but needs to move towards robust authentication and authorization [9][10] - The industry needs to adapt existing tooling for MCP due to its dynamic client registration, which can flood developer dashboards [12] Enterprise Readiness and Security - Scaling MCP servers requires addressing free credit abuse, bot blocking, and robust access controls [12] - Selling MCP solutions to enterprises necessitates SSO, lifecycle management, provisioning, fine-grained access controls, audit logs, and data loss prevention [12] - Regulations like GDPR impose specific logging requirements for AI workloads, which are not widely supported [12] Challenges and Future Development - Passing scope and access control between different AI workloads remains a significant challenge [13] - The MCP spec is actively developing, with features like elicitation (AI asking humans for input) still unstable [13] - Cloud vendors are solving cloud hosting, but authorization and access control are the hardest parts of enterprise deployment [13]