What problem it solves

Legacy SASE platforms combine connectivity and security in heavyweight, closed, cloud-locked stacks assembled from years of patchwork. Administrators need an open, self-hostable platform that unifies networking and security while remaining straightforward to deploy and operate.

Key features

• Connect remote networks — Site connectors use outbound tunnels and intelligent NAT traversal to make resources behind restrictive firewalls available to authorized users without public IPs or open ports.

  Source: README, cli

• Access resources through the browser — Context-aware tunneled reverse proxies provide browser access to HTTPS applications, VNC, RDP, and SSH with authentication and granular access control.

  Source: README

• Reach private resources with clients — Clients provide access to private servers, databases, remote desktops, and network ranges while supporting NAT traversal, DNS aliases, and redundant connector routes.

  Source: README, src

• Control access with identity and roles — Built-in identities or external identity providers support role-based access control, resource-specific grants, network audit logs, and access logs.

  Source: README

• Front AI workloads with an identity-aware gateway — The gateway places a shared identity-aware proxy in front of public and self-hosted model services, with personal API keys or keyless authentication, budgets, session history, and usage analytics.

  Source: README

Who it may suit

Inference: may suit administrators and security teams seeking a self-hostable, identity-aware platform for connecting remote users to networks, applications, and AI workloads.

Topics to discuss

• Which deployment model best fits different infrastructure and operational constraints?

• How should self-hosted organizations structure identities, roles, and resource policies?

• Which integrations and client experiences should receive priority for future development?

Written by ReadmeX AI from the project's README, source and public GitHub data; it may contain mistakes.

Read the original README https://github.com/fosrl/pangolin#readme

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