classifyre/all-in-one repository overview

⁠Classifyre All-in-One

Open-source investigation platform in a single Docker image — connect a source, detect leaked secrets, PII and security risks, and work findings into cases.

Classifyre turns the data scattered across the systems you already run — file shares, Confluence, Jira, SharePoint, S3, Git repositories, databases — into investigations you can act on. Detectors surface the evidence (leaked secrets and API keys, PII, security misconfigurations), and you work the results like an analyst: standing inquiries, duplicate detection, cases and hypotheses, with an AI autopilot doing the legwork in between.

This classifyre/all-in-one image is the fastest way to try Classifyre: the web UI, the API, the background worker, the Python scan workers, and a PostgreSQL database with pgvector — all in one container. One docker run, no dependencies to provision, nothing to connect. Ideal for local scanning, evaluations, and rapid prototyping.

For a team, or for anything that has to survive a machine dying, use the Helm chart⁠ (classifyre/classifyre-core) instead — it runs the same code as separate, independently scalable workloads.

📚 Full documentation: https://docs.classifyre.com⁠ — start with Deployment⁠ · Sources⁠ · Detectors⁠ · Investigations⁠

⁠Quickstart

docker run -d --name classifyre \
  -p 3000:3000 \
  --shm-size=1g \
  -v classifyre-pgdata:/var/lib/postgresql/data \
  -v classifyre-data:/var/lib/classifyre \
  -v classifyre-uv-cache:/cache/uv \
  classifyre/all-in-one:latest

Then open http://localhost:3000⁠.

The first boot initialises the database, applies the migrations and creates a workspace called default. On a laptop that takes a few minutes; watch it with docker logs -f classifyre.

Nothing leaves your machine. There is no account, no signup, and no telemetry you have not opted into.

What to do next: add a source (Sources → New), turn on detectors, run a scan, then work the findings into cases. See How it works⁠ and Flow⁠.

⁠Requirements

• Memory: 4 GB minimum, 8 GB recommended. The container refuses to start below 4 GB.
• CPU: 2 cores minimum (scans are CPU-bound).
• Disk: ~10 GB for the image and database, plus room for what you scan.
• Shared memory: always pass --shm-size=1g (PostgreSQL parallel queries need it).
• On macOS/Windows, raise Docker Desktop to 4+ GB under Settings → Resources → Memory.
• Architectures: linux/amd64 and linux/arm64 (Apple Silicon included).

⁠What is inside

⁠Scanning a folder on your machine

docker run -d --name classifyre \
  -p 3000:3000 --shm-size=1g \
  -v classifyre-pgdata:/var/lib/postgresql/data \
  -v classifyre-data:/var/lib/classifyre \
  -v classifyre-uv-cache:/cache/uv \
  -v "$HOME/Documents/case-files:/data/case-files:ro" \
  classifyre/all-in-one:latest

Then in the UI: Sources → New → Mounted Folder, path /data/case-files.

⁠Configuration

Everything is an environment variable (-e NAME=value or --env-file), and everything has a working default.

⁠Core

⁠Database

Leave these unset to use the PostgreSQL server inside the image.

⁠Object storage (S3, MinIO, R2, …)

Scan logs go to disk by default; set S3_BUCKET to store them in object storage instead.

⁠Embeddings

A small embedding model (Xenova/all-MiniLM-L6-v2, 384 dimensions) ships baked into the image and runs on CPU, so semantic search and duplicate detection work offline out of the box.

⁠Resources

The container sizes itself to the memory/CPU it was given. Override only with reason.

⁠Upgrades & backup

docker pull classifyre/all-in-one:latest
docker rm -f classifyre
# re-run the same docker run as before, with the same volumes

Data lives in the volumes, so it carries over; migrations run automatically. Pin a version tag to decide when to upgrade. Downgrades are not supported.

Back up two things: the database (docker exec classifyre pg_dump -U postgres classifyre > classifyre.sql) and the key (docker exec classifyre cat /var/lib/classifyre/masked-config.key).

⁠Moving to Kubernetes

Nothing here is a dead end: export a workspace from this container and import it into a cluster install — sources, findings, cases and lineage all move. The Helm chart⁠ (classifyre/classifyre-core) runs the same images this one is composed from (classifyre/api, classifyre/web, classifyre/cli).

Classifyre is open source: https://github.com/classifyre/classifyre⁠ · Docs: https://docs.classifyre.com⁠