- fix(db): migration 0012 column order mismatch causing NOT NULL
constraint failure on existing databases; use explicit column
mapping instead of SELECT *
- fix(db): disable FK checks during migrations to allow SQLite
table-recreation pattern (DROP + RENAME)
- fix(security): filter cookie_secret and instance_id from settings
API response for non-admin users
- fix(lint): resolve all 7 API lint warnings (noParameterAssign,
noImplicitAnyLet) in compose, image-enhancement, and workspace
- fix(docs): correct permission count from 16 to 14 in CLAUDE.md
- fix(e2e): resolve 44 Playwright test failures across 8 spec files
including locator specificity, compress mode defaults, format count,
restore-photo UI drift, stitch image count, GIF animated fixtures,
submit button timing, and processing timeouts
Add complete i18n infrastructure with 21 supported languages:
English, Simplified Chinese, Traditional Chinese, Japanese, Korean,
Spanish, French, Italian, Brazilian Portuguese, German, Dutch, Swedish,
Russian, Polish, Ukrainian, Arabic (RTL), Turkish, Hindi, Vietnamese,
Indonesian, and Thai.
- I18nProvider context with three-tier locale detection
(user preference > navigator.languages > instance default > English)
- ~1500 translation keys per locale with TypeScript-enforced completeness
- Dynamic code-splitting: only the active locale is loaded at runtime
- Language selectors in footer, login page, settings, and mobile sidebar
- Arabic RTL support with CSS logical properties across all components
- Tool names, descriptions, and categories translated via i18n helpers
- Public API endpoint GET /api/v1/config/locale for instance default
- Multi-script font stack (CJK, Arabic, Devanagari, Thai, Cyrillic)
- format() and plural() helpers for interpolation and pluralization
- API error translation mapping (translateApiError)
- 36 Playwright e2e tests verifying all 21 locales load correctly
- 25 unit tests for format, plural, locale detection, and completeness
- Updated translations.md docs and CLAUDE.md conventions
- LOGIN_ATTEMPT_LIMIT: 500 -> 30 in Dockerfile (matching code default)
- RATE_LIMIT_PER_MIN=0 now means no global limit (50K ceiling) instead
of 1 req/min, preserving backward compatibility with existing deploys
while keeping per-route limits (login brute-force) active
archiver v8 changed its default export, breaking all ZIP-producing
tools (pdf-to-image, split, batch, favicon, bulk-rename, svg-to-raster).
Reverted to v7 -- the lodash vulnerability via archiver is _.template
which is never called directly.
@fastify/static v9 has breaking changes incompatible with the current
static file serving setup. Reverted to v8 -- the path traversal CVEs
in v8 are mitigated by the existing path traversal guards in files.ts.
Updated edge-cases test to expect 400 for >64KB settings payloads
(new security limit).
Tests expected 422 for corrupted image data, but the API correctly
returns 400 since corruption is caught during validation (unrecognized
format), not during processing. Also fix watermark-image route passing
a hardcoded "watermark" string instead of the actual uploaded filename
to validateImageBuffer, which broke SVGZ detection.
validateImageBuffer catches corrupt image data before processing
reaches the tool handler, so the correct status code is 400 (bad
request) rather than 422 (processing failure). Also fix SVGZ
watermark validation by returning early for compressed SVG (Sharp
cannot read gzip-compressed SVGZ directly) and passing the actual
watermark filename to validateImageBuffer for correct format
detection.
Auth: login rate limit 30/min (was 500), global rate limit 1000/min (was
unlimited), password/username max lengths on all Zod schemas, session
invalidation on role change, API key legacy scan bounded to 100 keys.
SVG: hardened regex sanitizer with CDATA stripping, XML entity decoding,
set/animate/iframe/embed blocking, comprehensive data: URI blocking,
use element external href blocking. 11 attack payload fixtures added.
SSRF: fixed DNS rebinding TOCTOU by pinning resolved IPs via custom
HTTP/HTTPS agents. Added 6to4 and NAT64 to blocked IPv6 ranges.
Docker: capability dropping (cap_drop ALL + minimal cap_add), resource
limits (4g/8g mem, 512/1024 pids), healthcheck timeout, password
removed from startup banner, default password warning comments.
Network: CSP and HSTS applied in all environments (not just production),
stack traces removed from all error responses, internal paths stripped
from error details, per-route rate limits on uploads (60/min) and URL
fetches (200/hour).
Files: exclusive temp file creation (O_EXCL), disk space circuit
breaker, per-user storage quotas, settings payload 64KB size guard.
Python sidecar: script name allowlist in dispatcher, minimal environment
for subprocess spawns.
Dependencies: fixed 6 production CVEs (drizzle-orm, fastify, fast-uri,
@fastify/static, next, archiver/lodash). Pinned all GitHub Actions to
SHA hashes.
114 security tests added. Full OWASP Top 10 penetration test matrix
verified against production Docker container (30/30 pass after
hardening).
Covers session response fields, password guards, users list,
config endpoint, login redirect, callback edge cases, and
backward compatibility. Also adds migration to make password_hash
nullable (required for OIDC-only users) and vitest aliases for
@fastify/cookie and openid-client.
The transparency-fixer now directly detects the baked-in checkerboard
pattern using per-pixel chroma analysis instead of BiRefNet AI matting.
Achromatic pixels in the gray range are classified as background
(transparent), chromatic pixels as foreground (opaque), with smooth
transitions at anti-aliased edges.
- No longer requires Python sidecar or background-removal bundle
- Watermark removal uses Sharp median(5) filter pre-processing
- Moved tool from "ai" to "utilities" category
- Removed from PYTHON_SIDECAR_TOOLS and background-removal enablesTools
- Near-instant processing (pure Sharp, no model inference)
The luminance anomaly detection + LaMa inpainting approach failed because
watermark signal on the matted foreground was too weak (10-15 units vs
threshold of 25). Median filter with kernel=5 effectively removes
semi-transparent watermark text while preserving the stamp structure.
Pipeline is now: median filter (if toggle on) -> BiRefNet matting -> defringe.
No longer requires object-eraser-colorize bundle for watermark removal.
Add tier enum (fast/balanced/high) with balanced default to the Zod
settings schema. Pass tier through to outpaint options in both the HTTP
route and the pipeline/batch registry. Fix log message to say
"Starting AI canvas expand" and include tier in structured log fields.
- Fix dispatcher pipe deadlock: drain stdout pipe in a background thread
to prevent blocking when ONNX runtime output exceeds 64KB pipe buffer
- Add 5-minute SSE stall timeout so the UI shows an error instead of
hanging forever when async AI processing stalls
- Guard CPU colorization: skip for images >2MP on CPU and when DDColor
model is not installed, with clear user-facing messages
- Add AVIF decode fallback via ImageMagick for bitstream variants that
Sharp's bundled libheif cannot decode (affects all tools)
EXR: add ffmpeg fallback when ImageMagick lacks the OpenEXR delegate
(common on macOS Homebrew installs). HDR: force 8-bit depth output to
prevent CLAHE crash (hist_local requires VIPS_FORMAT_UCHAR). Batch:
disable socket timeout and increase server requestTimeout to 30 min
so large AI batches don't get killed by Node.js defaults.
HDR and EXR files decoded by ImageMagick can produce 16-bit PNG buffers.
Sharp's CLAHE operation (hist_local) requires VIPS_FORMAT_UCHAR (8-bit).
Check the buffer depth and convert to 8-bit sRGB before processing.
Sharp's TIFF encoder silently strips the alpha channel, flattening
transparency against black. This caused border (corner radius, shadow),
beautify, and replace-color tools to produce wrong output for TIFF
inputs when the operation needs transparency. Remove TIFF from
ALPHA_FORMATS so these tools fall back to PNG output.
The find-duplicates tool failed entirely when any uploaded file couldn't
be processed, returning "Duplicate detection failed" or a format-specific
error that aborted the whole batch. With mixed-format uploads (77 files),
this made the tool unusable.
- Skip unprocessable files instead of aborting; return skippedFiles in response
- Switch from fetch() to XHR with upload progress tracking (Uploading X%)
- Add Vite proxy timeout config (5min) to prevent connection drops on large uploads
- Add "Download Grouped" button: ZIP with each duplicate group in its own folder
- Add collapsible skipped-files section in the results UI
- Add 3 integration tests for skip behavior (43 total)
Custom-route tools (split, compare, collage, find-duplicates, etc.) only
handled HEIC via ensureSharpCompat, failing on BMP, PSD, RAW, TGA, EXR,
HDR, JXL, and other formats Sharp cannot decode natively. Added the full
decode pipeline from createToolRoute to all 16 affected routes: format
validation via validateImageBuffer, HEIC decoding with actionable error
messages, CLI-based exotic format decoding with nested fallback, and SVG
sanitization to prevent XXE/SSRF/script injection.
The vectorize tool had a custom processing flow that bypassed the
standard useToolProcessor hook -- no progress indication, no server-side
batch, and the Download All ZIP relied on a client-side sequential loop.
Backend: extract core logic into vectorizeBuffer(), register via
registerToolProcessFn() so the /batch endpoint works with p-queue
concurrency and SSE progress events.
Frontend: replace custom fetch loop with useToolProcessor hook and
ProgressCard, giving upload progress, per-file batch status, and
automatic Download All ZIP via the existing tool-page infrastructure.
Also set image/svg+xml MIME type on SVG blobs during batch ZIP
extraction to ensure reliable rendering in <img> tags across browsers.
The stitch route only decoded HEIC via ensureSharpCompat, so exotic
formats (DNG, PSD, TGA, BMP, JXL, HDR, QOI, DDS, ICO, JP2, DPX, etc.)
crashed Sharp at metadata read time, causing "Stitch creation failed".
Add the full CLI decode pipeline (decodeToSharpCompat) matching the
tool-factory pattern, plus SVG sanitization with proper error handling
for each format category.
Replace fetch() with XMLHttpRequest in the frontend to surface upload
progress via onprogress events, and add a progress bar that shows upload
percentage then pulses during server-side stitching.
Replace fragile Unicode-range regex with positive ASCII check
(/^[\x20-\x7E]+$/) that also catches emoji and supplementary plane
characters. Update OpenAPI spec to document percent-encoding.
The X-File-Results header contained raw JSON with non-ASCII characters
from filenames (Chinese, Japanese, etc.), violating RFC 7230. Node.js
threw ERR_INVALID_CHAR on writeHead(). Fixed by wrapping the JSON in
encodeURIComponent() on the backend and decodeURIComponent() on the
frontend, ensuring only ASCII goes into the header while preserving
the original filenames after decoding.
Closes#133
The preview endpoint now returns X-Original-Width/Height headers with
dimensions read from Sharp metadata (or ExifTool for RAW files). The
frontend stores these in FileEntry and the ImageViewer prefers them over
the browser's naturalWidth/naturalHeight, which reflects the resized
preview rather than the original sensor dimensions.
Sharp can read TIFF-based RAW files (DNG, CR2, NEF) directly for
metadata without requiring ImageMagick/darktable to fully decode them.
Try Sharp on the raw buffer first; only fall back to the decode pipeline
for formats Sharp cannot open (PSD, ICO, TGA). For RAW files, enrich
with ExifTool to get real sensor dimensions instead of thumbnail size.
Error from a failed image (e.g. DNG) persisted when navigating to a
previously cached image because the cache path skipped setError(null).
Also pass the original file extension to decodeToSharpCompat so RAW
variants get the correct temp file suffix for ExifTool/ImageMagick.
The compose route only decoded HEIC/HEIF via ensureSharpCompat, causing
EPS, PSD, BMP, RAW, and other exotic formats to fail with
"Processing failed". Now uses the same full format pipeline as the
tool-factory for both base and overlay buffers.
Replace mock HTTP server + vi.mock approach with vi.stubGlobal('fetch')
using a public IP (1.2.3.4) that passes real SSRF validation. This
eliminates both the fragile vi.mock (broken under V8 coverage) and the
localhost network dependency (unreliable in CI).
Revert the SSRF_ALLOW_PRIVATE env var that broke ssrf unit tests.
Extend timeout for exotic format error resilience tests to 120s to
accommodate slow JXL + Image enhancement combination in CI.
Install ImageMagick, Ghostscript, libjxl-tools, and libopenjp2-tools in
CI so exotic format decoder tests (PSD, EPS, HDR, ICO, JP2, etc.) can
run. Relax ImageMagick EPS/PS security policy to match the Dockerfile.
Replace fragile vi.mock() of the SSRF module in fetch-urls tests with an
env-var guard (SSRF_ALLOW_PRIVATE) that bypasses private-IP checks in
the test environment. The vi.mock approach broke under V8 coverage
instrumentation in CI.
The favicon route bypassed createToolRoute and only handled HEIC/HEIF
via ensureSharpCompat. Exotic formats (PSD, BMP, JXL, JP2, EXR, HDR,
DNG, ICO, TGA, etc.) passed validation but crashed Sharp after
reply.hijack(), causing the response stream to hang silently until the
5-minute XHR timeout.
Now decodes all formats before hijacking the response, matching the
pipeline used by createToolRoute. Files that fail to decode are skipped
with a skipped-files.txt manifest in the ZIP rather than aborting the
entire batch.
Per-image try-catch with Sharp fallback for CLI-decoded formats (matching
createToolRoute), SVG decompression/sanitization, and filename-specific
error messages so users know which image failed and why.
The image-to-pdf route used ensureSharpCompat (HEIC-only) instead of the
full format decode pipeline from tool-factory. Formats like FITS, PSD,
RAW, EXR, HDR, TGA, etc. passed through undecoded and crashed Sharp.
Replace with validateImageBuffer + decodeToSharpCompat to match the
standard tool pipeline.
- Refactor use-tool-processor and use-pipeline-processor hooks
- Enhance dropzone component with improved UX
- Improve seam carving with better error handling and tests
- Add JXL format encoding support to format-encoders
- Update tool routes for consistent format handling
- Add dropzone unit tests
All URLs in a batch share a single workspace directory. When multiple
URLs resolve to the same filename (e.g. two different domains both
serving photo.jpg), the second writeFile silently overwrites the first.
Track used filenames in a Set and append _1, _2, etc. on collision,
mirroring the existing getUniqueName pattern from batch.ts.
SnapOtter