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Eiger

Codebase for Halcyon — a deliberately-vulnerable, single-app teaching lab for a 2-day Black Hat course on adversarial AI. One fictional AI-first neobank ("Halcyon") whose assistant ("Halo") is attacked across six layers that grow module by module:

L0 chatbot → L1 RAG → L2 agent → L3 MCP servers → L4 multi-agent → L5 production

Participants Build / Break / Secure each layer. Named for the Eiger's north face — the hard, exposed climb.

Naming: the repo/codebase is Eiger. The in-fiction target org stays Halcyon and the assistant stays Halo (baked into the courseware narrative).

Doctrine (load-bearing)

  1. Validate the mechanism, not the model's words — pass/fail is a query against an append-only audit log.
  2. One build + SEC_* flagsvulnerable vs secure is a config flag; the diff is the lesson.
  3. Local floor, BYOK ceiling — Ollama (keyless, default) or the participant's own key, selectable at runtime. Both online.
  4. Deterministic + resettable + self-service/validate/{module}, /reset/{module}, reach-test on screen 1.

Deployment: hosted, container-per-participant app instances, a shared Ollama backend, and an external progress store; the same images dual-deploy to cloud (primary) and a local-LAN server (fallback).

Status

M1 · M2 · M3 · M4 (all of Day 1) + M5 (first Day-2 module) built and merged — 112 tests, each proven live end-to-end. Next: M6 (MCP security).

👉 docs/STATUS.md is the single source of truth for build status and how to resume. It covers the architecture, the per-module summary, how to run/test/deploy, the M6 starting point, and deferred cleanups.

Planning workspace / full course context lives in the Blackhat workspace (halcyon-lab-spec.md, HANDOFF.md, CLAUDE.md).

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Eiger — deliberately-vulnerable adversarial-AI teaching lab (Halcyon/Halo) for a Black Hat course. Intentionally insecure BY DESIGN for training; not for production use.

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