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SnapOtter/apps/docs/guide/security.md
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SnapOtterandGitHub 60d01ab2dd fix: release-acceptance QA follow-ups (upload crash, scipy ABI conflict, rate limit, OCR fallback) (#458)
* fix(api): prevent a crash when an over-limit upload stream has no consumer yet

busboy's "limit" handler destroyed the file stream with an error but never
attached its own error listener, relying entirely on whatever consumes
part.file downstream to do so. On a fast enough connection (or a fully
buffered body, e.g. Fastify inject()), busboy can process enough bytes to
hit the size limit before the route handler's receiveUpload() call has
attached its own stream listener, leaving the resulting "error" event with
zero listeners -- which crashes the whole process by default in Node.

Surfaced by tonight's FULL_MATRIX+FUZZ integration run (880 uncaught
exceptions, all the same root cause). Reproduces deterministically in
isolation; unrelated to this release's actual code delta (file untouched
since PR #413, well before the baseline QA pass).

Fix: attach a baseline no-op error listener the moment the stream is
created, guaranteeing at least one listener always exists. EventEmitter
delivers "error" to every registered listener, so the real consumer's own
error handling is unaffected.

* fix(ai-bundles): rebuild upscale-enhance and photo-restoration to reconcile scipy ABI

upscale-enhance and photo-restoration both depend on codeformer-pip, whose
transitive closure (basicsr -> realesrgan -> gfpgan) pulls in an unpinned
scipy. Both bundles were last built ~June 18-19, before PR #437 added the
manifest's `constraints` array (numpy==1.26.4, scipy==1.12.0, etc.) to pin
exactly this kind of dependency during bundle builds. Only the ocr bundle
was rebuilt after that fix landed.

install_feature.py has no pip install step -- it's a raw tarfile extraction
with no cross-bundle conflict resolution, so installing OCR alongside either
stale bundle left three incompatible scipy versions' files mixed in the same
site-packages directory (a compiled _rotation.*.so from one release next to
Python files expecting a different release's API), breaking the `upscale`
tool and OCR's higher-quality tiers with an ImportError.

Rebuilt both bundles for amd64-gpu and arm64-cpu from the current manifest,
verified scipy/scikit-learn/scikit-image/pandas all resolve to the pinned
versions in the tarballs themselves, then verified end-to-end on real
hardware (Mac arm64 CPU and ubuntu_gpu .248 RTX 4070): installing all
affected bundles together now yields exactly one version of each constrained
package, `upscale` produces correct output, and OCR's balanced/best tiers
correctly use PaddleOCR-GPU instead of erroring out.

Published the rebuilt tarballs to the public deepsafe/feature-bundles
HuggingFace repo and updated this manifest's sha256/sizes to match.

Also adds verify-bundle-compatibility.sh: verify-bundle.sh checks each
bundle in isolation (a fresh venv per bundle), which is exactly why this
shipped twice -- nothing ever checked that bundles built at different times
agree once layered into the one shared venv real installs use. The new
script installs every bundle for an arch into one venv and asserts each
constrained package has exactly one, correct version.

Known follow-up (not fixed here, needs separate discussion): uninstalling a
bundle only removes its downloaded model weights, never the site-packages
it added, so existing installations that already hit this bug have no clean
self-service fix via uninstall+reinstall -- they need a full AI-venv wipe.

* fix(docker): bake a real rate limit default for the all-in-one one-liner

The documented single-container `docker run` install had RATE_LIMIT_PER_MIN=0
(effectively unlimited, ~50k/min) baked in, since only docker-compose.yml
carried a hardened override. A self-hoster following the one-liner path got
no meaningful throttling anywhere, including auth-adjacent routes with no
dedicated per-route limit. Bakes a generous-but-real 1000/min default into
the Dockerfile, raises both compose files' fallback to match so the two
documented install paths converge on the same posture, and updates the Zod
schema default plus docs that quoted the old value.

* fix(api): boot log undercounted tool routes by the conversion-preset total

The "Tool routes: N active" line logged before registerConversionPresets(app)
ran, so it only ever reported the base 158 tools, 83 short of the real
241-tool total. Presets have to register after the base loop (they delegate
to each base tool's own processV2), so the fix moves the log line to after
that call and has registerConversionPresets return its count instead of
reordering the dependency.

* fix(ai): forward {info}/{warning} stderr JSON instead of dropping it

The dispatcher stderr parser only recognized {ready} and {progress,stage}
shaped JSON lines; anything else that parsed as valid JSON (like ocr.py's
GPU-to-tesseract downgrade notice, an {"info": ...} line) matched neither
branch and fell through silently, never reaching docker logs. Adds explicit
{info}/{warning} handling that forwards to console.log/console.warn, same as
the existing [prefix]-tagged non-JSON path.

* fix(api): fall back to a lower OCR tier when PaddleOCR itself is unusable

ocr.ts already retries lower quality tiers on a crashed dispatcher, but the
condition only matched crash-style messages (segfault, exited unexpectedly).
ocr.py's own ImportError/exception handlers already produce messages telling
the caller to use a lower tier (e.g. on the scipy ABI conflict class of bug),
but nothing ever acted on them, so a broken PaddleOCR hard-failed with 422
instead of degrading to Tesseract like ocr-pdf effectively does. Broadens the
retry condition to also catch PaddleOCR-engine-unusable messages.

Note: ocr-pdf's tesseract-only behavior turned out to be an unrelated,
pre-existing, deliberate design choice (PaddleOCR segfaults on rasterized PDF
pages on arm64), not a graceful-fallback mechanism to copy -- the two tools
weren't actually solving the same problem, so this fixes ocr.ts's own gap
rather than trying to mirror ocr-pdf.
2026-07-07 12:18:28 +08:00

12 KiB

description
description
Security hardening guide for SnapOtter. Container security, network isolation, Docker secrets, Kubernetes deployment, and compliance artifacts.

Security & Hardening

SnapOtter processes files entirely on your infrastructure. It sends anonymous, content-free product analytics and crash reports by default to help improve the project. It never sends your files, file names, file contents, OCR output, image metadata, or document text. Optional feedback is sent only after a user submits it, only when analytics is enabled, and contact fields are included only with explicit contact consent. An administrator can turn analytics and feedback capture off in one click under Settings > System > Privacy, no rebuild required. File processing always stays inside your container.

The container runs as a dedicated non-root user (snapotter) with all Linux capabilities dropped except the minimum required set. For the full vulnerability disclosure policy and security architecture, see SECURITY.md on GitHub.

Container Hardening

The default docker-compose.yml includes production security hardening. Here is a breakdown of each option and why it matters:

services:
  SnapOtter:
    image: snapotter/snapotter:latest
    ports:
      # Bind to localhost only for internet-facing deployments:
      - "127.0.0.1:1349:1349"
    volumes:
      - SnapOtter-data:/data
      - SnapOtter-workspace:/tmp/workspace
    environment:
      - AUTH_ENABLED=true
      - DEFAULT_PASSWORD=change-me-immediately
      - RATE_LIMIT_PER_MIN=1000
      - DATABASE_URL=postgres://snapotter:snapotter@postgres:5432/snapotter
      - REDIS_URL=redis://redis:6379
    depends_on:
      postgres:
        condition: service_healthy
      redis:
        condition: service_healthy

    # --- Resource limits ---
    mem_limit: 6g            # Prevents runaway memory from crashing the host
    memswap_limit: 6g        # No swap - fail fast instead of degrading the host
    cpus: 4                  # Cap CPU usage to 4 cores
    pids_limit: 512          # Prevents fork bombs

    # --- Capability restrictions ---
    cap_drop:
      - ALL                  # Drop ALL Linux capabilities first
    cap_add:
      - CHOWN                # Needed for volume permission setup
      - SETUID               # Needed for gosu privilege drop (root -> snapotter)
      - SETGID               # Needed for gosu privilege drop
      - DAC_OVERRIDE         # Needed for volume permission setup
      - FOWNER               # Needed for volume permission setup

    # --- Logging ---
    logging:
      driver: json-file
      options:
        max-size: "50m"      # Rotate logs at 50 MB
        max-file: "5"        # Keep 5 rotated log files

    # --- Health check ---
    healthcheck:
      test: ["CMD", "curl", "-sf", "--max-time", "5", "http://localhost:1349/api/v1/health"]
      interval: 30s
      timeout: 5s
      start_period: 60s
      retries: 3

    shm_size: "2gb"          # Required for Python ML shared memory
    restart: unless-stopped

  postgres:
    image: postgres:17-alpine
    environment:
      POSTGRES_USER: snapotter
      POSTGRES_PASSWORD: snapotter
      POSTGRES_DB: snapotter
    volumes:
      - SnapOtter-pgdata:/var/lib/postgresql/data
    restart: unless-stopped
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U snapotter"]
      interval: 10s
      timeout: 5s
      retries: 12
      start_period: 15s

  redis:
    image: redis:8-alpine
    command: ["redis-server", "--maxmemory-policy", "noeviction", "--appendonly", "yes"]
    volumes:
      - SnapOtter-redisdata:/data
    restart: unless-stopped
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 10s
      timeout: 5s
      retries: 12
      start_period: 10s

volumes:
  SnapOtter-data:
  SnapOtter-workspace:
  SnapOtter-pgdata:
  SnapOtter-redisdata:

Why no-new-privileges Is Not Set

security_opt: [no-new-privileges:true] is intentionally omitted. The entrypoint starts as root to fix volume ownership, then drops to the snapotter user via gosu, which requires setuid. Once the privilege drop completes, the process runs as snapotter with all capabilities except the five listed above removed.

If you use Kubernetes or Docker's --user flag to run as non-root directly (bypassing gosu), no-new-privileges is safe to enable.

Why read_only Is Not Set

read_only: true is not set because PUID/PGID remapping writes to /etc/passwd and /etc/group at startup. If you use Docker's --user flag or Kubernetes runAsUser instead of PUID/PGID, you can safely enable a read-only root filesystem.

Network Isolation

During normal operation, the container makes zero outbound network connections. All file processing happens locally using bundled libraries.

Browser  -->  Reverse Proxy (TLS)  -->  SnapOtter container  -->  (nothing)

The only exception is AI model downloads: when a user installs an AI feature bundle through the UI, the container downloads model files from GitHub Releases and PyPI. These downloads happen once per bundle and are stored in the /data volume.

Firewall recommendations:

Scenario Outbound rule
Air-gapped (no AI) Block all outbound traffic from the container
AI bundles needed Allow HTTPS to github.com, objects.githubusercontent.com, pypi.org, files.pythonhosted.org during install, then block
After AI install Block all outbound traffic - models are cached locally

For reverse proxy configuration (Nginx, Traefik, Caddy, Cloudflare Tunnels), see the Deployment guide.

Docker Secrets

For production deployments, avoid passing secrets as plain-text environment variables. The entrypoint supports Docker's _FILE convention: mount a secret as a file and set the corresponding _FILE variable to its path.

Supported secrets:

Variable _FILE equivalent
DEFAULT_PASSWORD DEFAULT_PASSWORD_FILE
COOKIE_SECRET COOKIE_SECRET_FILE
OIDC_CLIENT_SECRET OIDC_CLIENT_SECRET_FILE
S3_ACCESS_KEY_ID S3_ACCESS_KEY_ID_FILE
S3_SECRET_ACCESS_KEY S3_SECRET_ACCESS_KEY_FILE
SNAPOTTER_LICENSE_KEY SNAPOTTER_LICENSE_KEY_FILE

Example with Docker Compose secrets:

services:
  SnapOtter:
    image: snapotter/snapotter:latest
    environment:
      - AUTH_ENABLED=true
      - DEFAULT_USERNAME=admin
      - DEFAULT_PASSWORD_FILE=/run/secrets/snapotter_password
      - COOKIE_SECRET_FILE=/run/secrets/cookie_secret
    secrets:
      - snapotter_password
      - cookie_secret

secrets:
  snapotter_password:
    file: ./secrets/snapotter_password.txt
  cookie_secret:
    file: ./secrets/cookie_secret.txt

::: tip Docker Compose secrets (without Swarm) require Compose v2.23 or later. :::

Kubernetes Deployment

The entrypoint detects when the container is already running as non-root (e.g., via Kubernetes runAsUser) and skips the gosu privilege drop automatically. In that case it cannot chown the mounted volumes itself, so it verifies they are writable and exits early with actionable guidance if they are not — see Storage permissions for fsGroup and foreign-UID setups (TrueNAS, OpenShift).

Recommended Pod SecurityContext:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: snapotter
spec:
  replicas: 1
  selector:
    matchLabels:
      app: snapotter
  template:
    metadata:
      labels:
        app: snapotter
    spec:
      securityContext:
        runAsNonRoot: true
        runAsUser: 999
        runAsGroup: 999
        fsGroup: 999
      containers:
        - name: snapotter
          image: snapotter/snapotter:latest
          ports:
            - containerPort: 1349
          securityContext:
            allowPrivilegeEscalation: false
            capabilities:
              drop: [ALL]
          resources:
            requests:
              cpu: "1"
              memory: 2Gi
            limits:
              cpu: "4"
              memory: 6Gi
          livenessProbe:
            httpGet:
              path: /api/v1/health
              port: 1349
            initialDelaySeconds: 60
            periodSeconds: 30
            timeoutSeconds: 5
          readinessProbe:
            httpGet:
              path: /api/v1/health
              port: 1349
            initialDelaySeconds: 10
            periodSeconds: 10
            timeoutSeconds: 5
          volumeMounts:
            - name: data
              mountPath: /data
            - name: workspace
              mountPath: /tmp/workspace
      volumes:
        - name: data
          persistentVolumeClaim:
            claimName: snapotter-data
        - name: workspace
          emptyDir:
            medium: Memory
            sizeLimit: 2Gi

Since runAsUser: 999 is set at the pod level, the entrypoint skips gosu entirely. This allows allowPrivilegeEscalation: false and drop: [ALL] capabilities without conflict.

For resource sizing, see Hardware Requirements.

Backup and Recovery

Persistent state is split across two volumes:

Volume Contents Critical?
SnapOtter-pgdata PostgreSQL database (users, settings, pipelines, jobs, audit log) Yes
/data (app volume) User-uploaded files, AI models, Python venv Partially (see below)

Within the /data volume:

Path Contents Critical?
/data/uploads/, /data/outputs/ User files and processing results Yes
/data/ai/ Downloaded AI model files No (re-downloadable)
/data/venv/ Python virtual environment No (rebuilt on start)

Database backup

Use pg_dump to back up the database while the stack is running:

# Dump the database
docker exec SnapOtter-postgres pg_dump -U snapotter snapotter > backup.sql

# Restore into a fresh database
cat backup.sql | docker exec -i SnapOtter-postgres psql -U snapotter snapotter

Alternatively, stop the stack and snapshot the SnapOtter-pgdata volume:

docker compose down
docker run --rm -v SnapOtter-pgdata:/data -v $(pwd)/backup:/backup \
  alpine tar czf /backup/snapotter-pgdata.tar.gz -C /data .

User files backup

# Snapshot the app data volume (excluding re-downloadable AI models)
docker run --rm -v SnapOtter-data:/data -v $(pwd)/backup:/backup \
  alpine tar czf /backup/snapotter-files.tar.gz \
    --exclude='ai' --exclude='venv' -C /data .

AI models total up to about 24 GB across all bundles. Since they are re-downloadable, exclude /data/ai/ and /data/venv/ from backups to save space. Only the database and user files are critical.

Compliance Artifacts

Each SnapOtter release includes the following security artifacts:

Artifact Format Where to find it
SBOM (CycloneDX) JSON GitHub Release asset: snapotter-v{version}-sbom.cdx.json
SBOM (SPDX) JSON GitHub Release asset: snapotter-v{version}-sbom.spdx.json
Vulnerability scan Trivy JSON GitHub Release asset: snapotter-v{version}-trivy.json
Vulnerability scan SARIF GitHub Security tab
Static analysis CodeQL (JS/TS + Python) GitHub Security tab, runs weekly + per PR
Dependency review GitHub native Per-PR check, fails on high-severity additions
Python dependency audit pip-audit CI run log on every push
Security policy Markdown SECURITY.md in the repository
Dependency updates Dependabot Automated weekly PRs for npm, pip, Docker, Actions

Running your own scan:

Download the SBOM from the release and scan it with your preferred tool:

# Scan with Grype using the CycloneDX SBOM
grype sbom:snapotter-v1.17.2-sbom.cdx.json

# Scan with Trivy using the SPDX SBOM
trivy sbom snapotter-v1.17.2-sbom.spdx.json

# Scan the Docker image directly
trivy image snapotter/snapotter:1.17.2

::: info The SBOM and vulnerability scan reflect the exact image published for that release. AI model bundles installed after deployment are not included in the SBOM since they are downloaded at runtime. :::