Update README, in-app privacy page, landing privacy page, and
deployment docs to reflect the new analytics model. Remove references
to opt-in consent, Settings toggle, and ANALYTICS_ENABLED env var.
Document the SNAPOTTER_ANALYTICS build arg for disabling.
* fix(docker): pin CUDA base to 12.6 so the GPU image starts on R560+ drivers
The amd64 base nvidia/cuda:12.9.2-cudnn-runtime bakes a cuda>=12.9 driver gate enforced by nvidia-container-toolkit at container start, so the image fails to launch on common production drivers (e.g. 570.x / CUDA 12.8). The AI bundles are all cu126 wheels and the image installs libcublas-12-6, so 12.9 was misaligned with the workload. Pin to nvidia/cuda:12.6.3-cudnn-runtime-ubuntu24.04 to match the wheels and lower the driver floor to R560+.
* fix(ai): broaden OOM detection so the rembg lighter-model fallback fires
onnxruntime/CUDA allocation failures surface as 'Failed to allocate memory for requested buffer', CUBLAS_STATUS_ALLOC_FAILED, or bad_alloc, not just 'out of memory'. The background-removal and transparency-fixer fallback-to-lighter-model paths only matched the literal 'out of memory', so the fallback was dead code and transparency-fixer (default birefnet-hr-matting) always failed with an allocation error. Add isMemoryAllocError() and use it in both checks.
* fix(ai): use bundled PaddleOCR models so OCR runs offline
ocr.py passed no model dirs to PaddleOCR, so PaddleX resolved models from ~/.paddlex and downloaded them from HuggingFace at runtime (slow first use, broken air-gapped), ignoring the models the OCR bundle ships in MODELS_PATH; it also pulled doc-orientation/unwarping models that are not bundled. Pin detection, recognition and textline models to the bundled dirs in MODELS_PATH (per language) and disable use_doc_orientation_classify / use_doc_unwarping, with per-component fallback when a model is absent. Verified: OCR runs with zero HuggingFace requests.
* fix(docker): add CAP_KILL so container shutdown is graceful
cap_drop: ALL without re-adding KILL meant tini (PID 1, root) could not forward SIGTERM to the gosu-dropped snapotter process (root minus CAP_KILL cannot signal a different UID). docker stop logged '[FATAL tini] forwarding signal: Operation not permitted', never delivered the signal, and fell back to SIGKILL after the 10s timeout. Add KILL to cap_add in both compose files. Verified: docker stop completes in 0s with SIGTERM delivered (exit 143) and no FATAL tini.
* fix(ai): serialize bundle installs against AI jobs to prevent sidecar segfault
A feature bundle install rewrites the shared Python venv (pip + copytree of site-packages/*.so) as a background subprocess, with no coordination against AI tool jobs that dlopen native libs (torch / onnxruntime CUDA) from the same venv; a job loading a shared object while it is overwritten segfaults the sidecar. Add a process-wide async mutex (venv-lock.ts): bridge.run() acquires it before every AI script and the install route holds it across the installer subprocess. Both run in the same Node process so a module-level lock suffices. Verified: concurrent install + AI job produces zero segfaults and the job serializes behind the install.
* fix(ai): make the venv lock read/write so concurrent AI jobs are not serialized
The first cut used an exclusive mutex, which (a) deferred the dispatcher spawn by a microtask and broke unit tests that synchronously drive the mocked spawn, and (b) serialized AI jobs against each other, removing the dispatcher's by-id request multiplexing. Make it a writer-preferring read/write lock: AI jobs are shared readers (with a synchronous fast path so spawn still happens in-tick) and a bundle install is the exclusive writer. Verified: all 764 AI unit tests pass.
* fix(ai): degrade OCR to Tesseract on CPU-only hosts instead of segfaulting
The amd64 AI bundle ships paddlepaddle-gpu, whose native libs dlopen
libcuda.so.1 at import and segfault on a host without a GPU (libcuda is the
driver lib, injected only by nvidia-container-toolkit on GPU hosts). The
segfault crashed the shared long-lived AI dispatcher and, after a few attempts,
tripped the bridge crash-recovery permanent-disable, wedging all AI until a
container restart. The standalone ocr tool defaults to quality=balanced
(PaddleOCR), so it hit this on every CPU-only deployment; ocr-pdf already
hardcoded Tesseract and was unaffected.
ocr.py now gates the PaddleOCR tiers on gpu_available(): balanced/best
transparently fall back to fast (Tesseract, CPU-capable) when no usable GPU is
present, and run_paddleocr_v5/run_paddleocr_vl refuse before importing paddle so
the GPU build is never dlopen'd on CPU. GPU hosts are unchanged.
Verified on a CPU-only Windows/WSL2 box: ocr returns Tesseract text across
repeated runs with the dispatcher staying healthy (no wedge).
* fix(passport-photo): require the face-detection bundle, not just background-removal
Passport Photo runs face-landmark detection (face_landmarks.py, gated to the
face-detection bundle) before background removal (background-removal bundle),
but it was only declared under and guarded against background-removal. A user
who installed only Background Removal passed every JS-side check, then hit a
late "feature_not_installed" from the Python dispatcher gate when the analyze
step ran face landmarks, and the UI never told them Face Detection was needed.
- shared: add TOOL_EXTRA_BUNDLES + getRequiredBundlesForTool so a tool can
declare more than one required bundle (passport-photo needs background-removal
and face-detection). enablesTools is untouched, so the one-tool-per-bundle
invariant still holds.
- api: isToolInstalled() now checks every required bundle; add
getFirstMissingBundleForTool() so the analyze and base routes, pipeline (both
guards) and batch report the bundle the user actually still needs.
- web: the proactive install prompt (tool-page) and features-store treat a tool
as installed only when all required bundles are present, and point the prompt
at the first missing one (sequential install, no new UI).
Refs #327
* test(passport-photo): deterministic integration coverage for the two-bundle guard
Boots the real API with an isolated DATA_DIR and controls installed.json to
prove the HTTP route behavior end-to-end:
- nothing installed -> 501 naming background-removal
- only background-removal installed -> 501 naming face-detection (issue #327)
- both installed -> guard passes (not 501)
- base route reports face-detection too
Refs #327
Three production crashes from the snapotter/node Sentry project.
feature-status (NODE-12): a valid-JSON-but-wrong-shape installed.json
crashed boot via Object.keys(data.bundles). readInstalled() now
normalizes any unusable shape to { bundles: {} }, and the boot recovery
call is wrapped so cleanup can never fatal startup.
image-viewer (NODE-15/17/18): drag-to-pan read .x off an undefined
use-gesture memo on pointerUp or a pinch-into-pan. A guarded pure helper
(resolvePanStart) now falls back to the live pan offset.
Fastify (NODE-14): raised pluginTimeout to 60s so slow self-hosted boots
do not fatal at @fastify/static.
The docs.snapotter.com hero command wrapped onto two lines. Switch the
command from pre-wrap to nowrap with internal horizontal scroll, widen the
box, and nudge the font down so it sits on one line on desktop and scrolls
inside its box on mobile without the page overflowing.
Move the copy action onto the whole command box (pointer cursor + hover
affordance) so clicking anywhere copies, while keeping the real Copy button
(now click.stop so it does not double-fire, with a min-width to avoid layout
shift between the Copy and Copied states).
* feat(web): add pure zoom/pan math module with unit tests
* feat(i18n): add a11y.pan key across all locales (English, matching adjacent zoom labels)
* feat(web): add useZoomPan hook (state + gestures over pure math)
* feat(web): add ZoomToolbar component
* feat(web): zoom & pan in the object eraser canvas
* feat(web): zoom & pan in the split tool preview
* fix(web): synchronous pan-mode refs so drag-pan is race-free under fast input
* test(e2e): zoom & pan acceptance (split always-on, eraser bundle-gated)
- Recolor banner/wordmark SVGs to the Otter Orange palette with brand fonts
- Rebuild social-preview.png as a hero-style OG card (trust badges, headline, five modality cards with section counts), synced to apps/landing + apps/web og-image.png
- Replace static dashboard PNGs with dashboard.gif: a guided tab tour of all 157 tools across the five modalities
- Update branding/README.md (Otter Palette, brand fonts, asset list); add scripts/branding generator + sync helpers
The entrypoint only fixed volume permissions when started as root (chown +
gosu-drop to snapotter). Launched under a non-root/foreign UID (TrueNAS app
user, Kubernetes runAsUser, OpenShift) it did no permission setup, so /data and
/tmp/workspace -- owned by uid 999 from the image -- were not writable by the
running user. Uploads and processing then failed with a cryptic EACCES
("workspace folder is not writable") and AI bundle installs failed the same way,
while health checks still reported the container healthy.
- entrypoint: source new entrypoint-lib.sh; verify writability up front when
non-root, and as snapotter after chown when root (catches root-squashed
mounts), failing fast with an actionable message (which dir, uid/gid, how to
fix) instead of a late, cryptic EACCES
- Dockerfile: own /data and /tmp/workspace as snapotter:0, group-writable with
setgid, so an arbitrary UID with the root supplementary group (OpenShift /
Kubernetes fsGroup) can write; keep /opt/venv world-readable for the AI venv
bootstrap under arbitrary UIDs
- api: assert storage writability at boot (lib/storage-writable.ts), failing
fast with the same guidance even when the entrypoint is bypassed
- docs: add a Storage permissions section (named volumes, bind mounts, TrueNAS,
Kubernetes/OpenShift) and cross-link it from the security guide
Fixes#230
Fetch landing stars + image pulls at build time via a shared stats lib, refreshed by a daily cron + authenticated GITHUB_TOKEN. Image Pulls totals live Docker Hub pull_count + a maintained GHCR estimate (ghcr.io has no public pull-count API).
RAW (DNG) processing crashed on ImageMagick's deprecated ufraw-batch
delegate, which fails on modern formats such as iPhone ProRAW DNG.
Root cause: the dcraw_emu (LibRaw) decode tier read the wrong output path.
dcraw_emu APPENDS the output extension (raw-in-X.dng -> raw-in-X.dng.tiff)
but the code looked for raw-in-X.tiff (replaced extension), so readFile threw
on every RAW, the tier silently fell through to ufraw, and the 24MB TIFF
leaked into the temp dir on each attempt.
- Repair the dcraw_emu output path; clean it up in finally (fixes the leak)
- Prefer LibRaw full decode over embedded-preview extraction so a
full-resolution RAW is never silently returned as a reduced-size preview
(sample DNG: was 1024x683 preview, now 3474x2314 full)
- Add RAW decode regression tests (DNG full-resolution + all 6 RAW formats);
these were absent, which let the bug ship
- Install libraw-bin on CI test runners so dcraw_emu is actually exercised
Tool endpoints (/api/v1/tools/*) now honor the RATE_LIMIT_PER_MIN env var instead of a hardcoded 60/min: `0` disables per-tool limiting, `>0` uses the configured value, and unset falls back to 60. Merged on top of the section-based route refactor (#280).
Fixes#271.
The csv-json integration test intermittently timed out at 30000ms on
the first worker-backed job in a fork. Root cause: waitForJob() creates
the BullMQ QueueEvents consumer lazily on first use, and a fresh consumer
reads the Redis events stream from "$" (the tail at the moment its run
loop starts). A trivial tool can publish its completed:<id> event before
the brand-new consumer positions itself, so waitUntilFinished() never
sees the event and blocks for the full sync-wait window. In tests
SYNC_WAIT_MS is floored at 30000ms, exactly the vitest per-test budget,
so the stall surfaces as an opaque timeout instead of a 202 fallback.
This is also a latent production latency bug: the first synchronous tool
request after each boot could hang up to the 8s prod window.
Fix: warmQueueEvents() eagerly constructs and connects every pool's
consumer at spine startup, before any job is enqueued, so each consumer
is positioned at the stream tail up front and never misses a completion.
Awaited in the test spine (deterministic for the first request) and fired
non-blocking at prod boot (a slow Redis must not stall startup).
Adds a regression guard in job-spine.test.ts that drops the cached
consumers, warms explicitly, and asserts a fast job's completion is
captured on the first sync-wait.
Verified: 3 parallel stress runs (276 file-runs across all pools), zero
timeouts; targeted job-spine + csv-json suites green; typecheck clean.
Replace textual prefix matching in isPrivateIPv6() with numeric bit-prefix matching via ipaddr.js. Closes reachable classifier bypasses for IPv4-compatible IPv6 (::a.b.c.d), site-local fec0::/10, and the full fe80::/10 link-local span, on top of the IPv4-mapped forms. Embedded IPv4 (mapped and compatible) is run through the full isPrivateIPv4 classifier; unparseable input fails closed.
Follow-up hardening to f64cbdda.
Reported-by: tonghuaroot
The resolve()+startsWith containment check was correct but CodeQL did not
recognize it. Apply path.basename() to the name in resolveWithinPreviewDir -- a
sanitizer CodeQL recognizes -- so every id-derived preview path is provably a
single filename inside the preview dir. Behaviour is unchanged for valid ids
(already charset-validated); containment check kept as a backstop.
- svg-sanitize.ts: strip each dangerous element repeatedly until stable with
whitespace-tolerant end tags, defeating nested/overlapping tags (closes 5
incomplete-multi-character-sanitization + 1 bad-tag-filter; the prior
single-pass regex could leave a residual <script>/<iframe>).
- file-preview.ts: add a resolve()+containment barrier (the path-traversal
guard CodeQL recognizes) on top of the id charset check (closes 9
path-injection).
- metadata.ts: bound the XMP namespace:name key segments so parseXmp cannot
backtrack polynomially (closes js/polynomial-redos).
- analytics-disabled.spec.ts: match analytics by URL host, not substring
(closes 4 incomplete-url-substring-sanitization).
typecheck + lint green; svg (119), preview (22), metadata (164) tests pass.
The Astro Dev Toolbar (enabled by default in dev mode) injects h1
elements ("No islands detected", "Audit", "Settings") and a
"Community" link inside its shadow DOM. Playwright CSS selectors
pierce shadow DOM, causing 6 test failures:
- 5 heading-hierarchy tests saw extra h1 elements from the toolbar
- footer "Community" column title resolved to 2 elements (footer h4
plus toolbar's Astro community chat link)
Root-cause fix: set PLAYWRIGHT=1 env var in the Playwright webServer
command; Astro config conditionally disables devToolbar when set.
Normal development retains the toolbar.
All /api/ routes are already covered by the global @fastify/rate-limit
(index.ts:283), but CodeQL doesn't model the global registration and flagged
every route without an explicit per-route limit. Added tuned config.rateLimit
to 45 routes: stricter on auth/credential routes (mfa/saml/oidc/api-keys,
15-30/min), moderate on writes (60/min), generous on reads/polls (300/min =
the global default). Real defense-in-depth on sensitive routes. 3 alerts on
non-route code (a preHandler hook, the rate-limiter's own DB lookup, a test
helper) are documented false-positives covered by the global limiter.
- file-preview.ts: validate the :id URL param against a safe charset and
restrict the original-name extension to alphanumerics before they feed
filesystem paths (closes 9 CodeQL js/path-injection; defense-in-depth on
top of the existing DB lookup).
- media-input.ts: require the SRT/VTT timecode structure to detect a subtitle
rather than a bare '-->' (closes CodeQL js/bad-tag-filter; also rejects
non-subtitle files that merely contain '-->').
- tests/e2e/helpers.ts: build the sharp script path via JSON.stringify
instead of single-quote-only replace (CodeQL js/incomplete-sanitization,
high: backslashes were not escaped). Proper fix, no suppression.
- landing CategoryCards: rename the file-modality marketing card to
"File Tools" (matches the Image/Video/Audio Tools siblings and is
unique vs the 23 "Files" tool pills, which broke the e2e locator).
Modality label stays "Files" everywhere it is the actual modality.
#280 left 10 section-prefixed custom-route files mis-indented and one
unsorted import block in the new landing section-index page. Fixed via
biome formatter (api) and manual import sort (landing). No config change
(biome.json is hook-protected); no suppression. pnpm lint + typecheck
now exit 0.
The fifth user-facing group is now Image, Video, Audio, PDF, Files
(internal modality id stays "file"; section.ts "files" was already
"Files"). Updates modality.ts label + comment, all 21 i18n locales
(categories.data "Data Files"->"Files", modalities.documentsAndFiles
"PDF & Data"->"PDF & Files", dead homePage.data), landing cards/hero
search/tools filter, docs headings, and e2e modality-tab assertions
(/^Data/ -> /^Files/, which had been failing).
Add scoped axe accessibility audit (a11y.spec.ts, device-a11y.spec.ts)
scanning home, one tool per modality, editor, and login across desktop
chromium and mobile-chromium in EN and AR locales. Uses a committed
baseline (a11y-baseline.json) to gate on NEW critical/serious violations
while documenting existing debt.
Add device-visual.spec.ts with curated screenshots (home, resize tool,
settings dialog) on mobile-chromium and tablet-chromium. Six darwin
baselines generated; linux baselines deferred to the existing
update-visual-baselines workflow.
Trivial a11y fixes applied:
- Login page: outer div -> main (fixes landmark-one-main, reduces region)
- Editor page: outer div -> main for both desktop and mobile gate
- AppLayout main: add tabIndex={-1} for skip-link focusability
Updated DEVICE_SPECS regex to route device-visual and device-a11y specs.
Added @axe-core/playwright as a devDependency.
- Lower LOGIN_ATTEMPT_LIMIT default from 30 to 10 (brute-force protection)
- Lower RATE_LIMIT_PER_MIN default from 1000 to 300
- Add Redis authentication (requirepass) with REDIS_PASSWORD env var
- Add Redis maxmemory 512mb cap to prevent unbounded growth
- Add mem_limit: 1g to Postgres and Redis containers
- Strip internal file paths from all error responses (defense-in-depth)
- Add startup warnings for default admin/Postgres/Redis credentials
- Update security test expectations for new defaults
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