Rewrite README with change log and full requirements
Replace README.md with a single comprehensive doc. Add a "What Changed" section mapping each improvement to its commit (DRBG fix, health checks, cleanup, HTTP service, auth, tests, docs). Expand Requirements into software, system libraries, hardware, kernel-RNG, and container subsections. Keep the existing usage, HTTP service, container, remote consumption, and tests sections. Generated by Mistral Vibe. Co-Authored-By: Mistral Vibe <vibe@mistral.ai>
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# Entropy-RNG: Camera-Based Random Number Generator
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This project uses a live video feed from a network camera (e.g. an **Axis M1013**) to generate cryptographically secure random numbers. The camera is pointed at a high-contrast, ever-changing scene (e.g. ceiling and lamps) so the pixel data carries genuine entropy.
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This project uses a live video feed from a network camera (e.g. an **Axis M1013**) to generate cryptographically secure random numbers. The camera is pointed at a high-contrast, ever-changing scene (e.g. ceiling and lamps) so the pixel data carries genuine entropy. The output can be used locally (feeding the kernel RNG via `rngd`) or served over HTTP so remote systems can pull entropy to seed their own pools.
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---
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## What Changed
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This section records the rewrite from the original scripts to the current pipeline. Each bullet maps to a commit in `git log`.
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### Core RNG fix (the important one)
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The original code computed a SHA-256 of the camera frame into a variable named `entropy` and then **discarded it**, drawing instead from the OS CSPRNG via `secrets.randbits()`. The camera contributed nothing — the output was just relabeled `/dev/urandom`.
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- Replaced with a **NIST SP 800-90A HMAC-DRBG** (SHA-256) seeded from the frame hash. The camera now genuinely contributes entropy.
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- The DRBG is reseeded every frame, so output changes even when camera noise is modest.
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- Added `--interval` for loop rate control, `--out` for writing raw bytes to a FIFO, mutual exclusion of `--loop`/`--single`, and bit-multiple validation.
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### Health checks
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- Added `health.py` with **FIPS 140-2 continuous tests** (monobit, runs, long-run) on the raw JPEG bytes before hashing.
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- A frozen, all-identical, or degraded frame is rejected and never seeds the DRBG.
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- Runs thresholds are doubled because we count 0-runs and 1-runs together.
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- `--no-health` disables the checks for debugging.
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### Cleanup
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- Removed `entropy-rng-cam.py` and `entropy-rng-opencv.py`, which were superseded by `entropy.py` and carried the same unused-entropy bug.
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- Removed the empty 0-byte `file`.
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- Added `requirements.txt` with pinned dependencies.
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### HTTP service + container deployment
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- Added `api.py` — a FastAPI app that runs the camera producer in a background thread and serves the latest entropy blob over HTTP.
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- Added `Dockerfile` for container builds, with a healthcheck against `/healthz`.
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- All config is via environment variables for containers.
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### Auth (simple by design)
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- Single shared secret via `X-API-Key` header, controlled by `ENTROPY_API_KEY`.
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- Empty key means no auth, so you can start open and lock down by setting one env var.
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- The API layer is where HMAC-signed blobs or mTLS plug in later — no architecture change needed.
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### Tests
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- Added `test_entropy.py` — 16 tests covering the DRBG, health checks, a bit-balance smoke test, and API auth gating. All pass without a camera (the producer is stubbed).
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### Docs
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- Rewrote this README and `notes.md` to match the new pipeline and commands.
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---
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@@ -16,14 +56,32 @@ This project uses a live video feed from a network camera (e.g. an **Axis M1013*
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## Requirements
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### Software
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- Python 3.10+
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- `opencv-python`, `fastapi`, `uvicorn`, `pytest`
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- Python packages: `opencv-python`, `fastapi`, `uvicorn`, `pytest`
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### System libraries (Debian/Ubuntu)
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OpenCV needs runtime libraries that are not pip-installed:
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```bash
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sudo apt-get install libgl1 libglib2.0-0
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```
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### Install Python dependencies
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```bash
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pip install -r requirements.txt
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```
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On Debian/Ubuntu you also need OpenCV runtime libs: `apt-get install libgl1 libglib2.0-0`.
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### Hardware
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- An IP webcam serving an MJPEG stream over HTTP (e.g. Axis M1013 at `http://192.168.0.200/mjpg/video.mjpg`).
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- The camera must be pointed at a dynamic, high-contrast scene. A static frame will fail health checks and be rejected.
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### For the kernel-RNG flow
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- Linux with `rngd` installed (`rng-tools` package).
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- `sudo` privileges to run `rngd`.
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### For container deployment
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- Docker (or any OCI-compatible runtime) for local containers.
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- Kubernetes for orchestrated deployment (optional).
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---
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@@ -142,3 +200,4 @@ Covers the HMAC-DRBG (determinism, reseed, length, reseed limit), health checks
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- Point the camera at a dynamic scene. A static frame will fail health checks and be rejected.
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- The DRBG is reseeded from each frame, so output changes even if the camera noise is modest.
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- Auth is a single shared secret for now. When you need per-client keys, rotate to HMAC-signed blobs or mTLS — the API layer is where that plugs in.
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- The 256-bits-per-frame entropy credit is conservative. If you want a defensible number for your specific camera, run `ent` or `rngtest` on a captured sample.
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