Files
SnapOtter/apps/api/src/routes/pipeline.ts
T
SnapOtter ff8dcf63c7 fix: resolve 14 security, correctness, and robustness issues found during QA sweep
Security fixes:
- Add auth + ownership check to thumbnail endpoint (was unauthenticated)
- Validate ExifTool fieldsToRemove against safe tag name pattern
- Add SVG sanitization to pipeline execute and batch endpoints
- Replace basename() with sanitizeFilename() in 16 tool routes
- Escape SQL LIKE wildcards in file search to prevent pattern injection
- Improve settings HTML tag validation pattern

Bug fixes:
- Skip autoOrient for SVG inputs in pipeline (prevents misinterpretation)
- Remove double-encode in compress targetSize (was degrading quality)
- Fix bg-effects alpha value from 255 to 1.0 (Sharp expects float)
- Guard download stream error handler against headers-already-sent race
- Use O_EXCL atomic file creation for install lock (fixes TOCTOU race)
- Truncate collage file array to template image count

UX fixes:
- Accept empty JSON bodies on POST endpoints (install/uninstall)
- Custom JSON content type parser that treats empty body as {}
2026-05-01 18:11:49 +08:00

738 lines
25 KiB
TypeScript

/**
* Pipeline execution, save, list, and delete routes.
*
* POST /api/v1/pipeline/execute — Execute a pipeline (array of tool steps)
* POST /api/v1/pipeline/save — Save a pipeline definition
* GET /api/v1/pipeline/list — List saved pipelines
* DELETE /api/v1/pipeline/:id — Delete a saved pipeline
*/
import { randomUUID } from "node:crypto";
import { writeFile } from "node:fs/promises";
import { join } from "node:path";
import { ANALYTICS_EVENTS, getBundleForTool, TOOL_BUNDLE_MAP } from "@snapotter/shared";
import archiver from "archiver";
import { eq } from "drizzle-orm";
import type { FastifyInstance, FastifyReply, FastifyRequest } from "fastify";
import PQueue from "p-queue";
import { z } from "zod";
import { env } from "../config.js";
import { db, schema } from "../db/index.js";
import { trackEvent } from "../lib/analytics.js";
import { autoOrient } from "../lib/auto-orient.js";
import { resolveConcurrency } from "../lib/env.js";
import { formatZodErrors } from "../lib/errors.js";
import { isToolInstalled } from "../lib/feature-status.js";
import { validateImageBuffer } from "../lib/file-validation.js";
import { sanitizeFilename } from "../lib/filename.js";
import { decodeToSharpCompat, needsCliDecode } from "../lib/format-decoders.js";
import { decodeHeic } from "../lib/heic-converter.js";
import { isSvgBuffer, sanitizeSvg } from "../lib/svg-sanitize.js";
import { createWorkspace } from "../lib/workspace.js";
import { hasEffectivePermission } from "../permissions.js";
import { requireAuth } from "../plugins/auth.js";
import { type JobProgress, updateJobProgress } from "./progress.js";
import { getRegisteredToolIds, getToolConfig } from "./tool-factory.js";
/** Schema for a single pipeline step. */
const pipelineStepSchema = z.object({
toolId: z.string(),
settings: z.record(z.unknown()).default({}),
});
/** Schema for a full pipeline definition. */
const stepsSchema =
env.MAX_PIPELINE_STEPS > 0
? z
.array(pipelineStepSchema)
.min(1, "Pipeline must have at least one step")
.max(env.MAX_PIPELINE_STEPS, "Pipeline exceeds maximum steps")
: z.array(pipelineStepSchema).min(1, "Pipeline must have at least one step");
const pipelineDefinitionSchema = z.object({
steps: stepsSchema,
});
/** Schema for saving a pipeline. */
const savePipelineSchema = z.object({
name: z.string().min(1, "Pipeline name is required").max(100),
description: z.string().max(500).optional(),
steps: stepsSchema,
});
export async function registerPipelineRoutes(app: FastifyInstance): Promise<void> {
/**
* POST /api/v1/pipeline/execute
*
* Accepts multipart with:
* - A file part (the image to process)
* - A "pipeline" field containing JSON: { steps: [{ toolId, settings }, ...] }
*
* Processes the image through each step sequentially.
* The output of step N becomes the input of step N+1.
* Returns the final processed image for download.
*/
app.post("/api/v1/pipeline/execute", async (request: FastifyRequest, reply: FastifyReply) => {
let fileBuffer: Buffer | null = null;
let filename = "image";
let pipelineRaw: string | null = null;
// Parse multipart
try {
const parts = request.parts();
for await (const part of parts) {
if (part.type === "file") {
const chunks: Buffer[] = [];
for await (const chunk of part.file) {
chunks.push(chunk);
}
fileBuffer = Buffer.concat(chunks);
filename = sanitizeFilename(part.filename ?? "image");
} else if (part.fieldname === "pipeline") {
pipelineRaw = part.value as string;
}
}
} catch (err) {
return reply.status(400).send({
error: "Failed to parse multipart request",
details: err instanceof Error ? err.message : String(err),
});
}
if (!fileBuffer || fileBuffer.length === 0) {
return reply.status(400).send({ error: "No image file provided" });
}
// Validate the initial image
const validation = await validateImageBuffer(fileBuffer, filename);
if (!validation.valid) {
return reply.status(400).send({
error: `Invalid image: ${validation.reason}`,
});
}
// Decode HEIC/HEIF input via system heif-dec
if (validation.format === "heif") {
try {
fileBuffer = await decodeHeic(fileBuffer);
// Update filename extension to match the decoded format
const ext = filename.match(/\.[^.]+$/)?.[0];
if (ext) filename = `${filename.slice(0, -ext.length)}.png`;
} catch (err) {
return reply.status(422).send({
error: "Failed to decode HEIC file. Ensure libheif-examples is installed.",
details: err instanceof Error ? err.message : String(err),
});
}
}
// Decode CLI-decoded formats (RAW, TGA, PSD, EXR, HDR)
if (needsCliDecode(validation.format)) {
try {
fileBuffer = await decodeToSharpCompat(fileBuffer, validation.format);
const ext = filename.match(/\.[^.]+$/)?.[0];
if (ext) filename = `${filename.slice(0, -ext.length)}.png`;
} catch (err) {
return reply.status(422).send({
error: `Failed to decode ${validation.format} file`,
details: err instanceof Error ? err.message : String(err),
});
}
}
// Sanitize SVG input and normalize EXIF orientation
const isSvg = isSvgBuffer(fileBuffer);
if (isSvg) {
fileBuffer = sanitizeSvg(fileBuffer);
} else {
fileBuffer = await autoOrient(fileBuffer);
}
// Parse and validate the pipeline definition
if (!pipelineRaw) {
return reply.status(400).send({ error: "No pipeline definition provided" });
}
let pipeline: z.infer<typeof pipelineDefinitionSchema>;
try {
const parsed = JSON.parse(pipelineRaw);
const result = pipelineDefinitionSchema.safeParse(parsed);
if (!result.success) {
return reply.status(400).send({
error: "Invalid pipeline definition",
details: formatZodErrors(result.error.issues),
});
}
pipeline = result.data;
} catch {
return reply.status(400).send({ error: "Pipeline must be valid JSON" });
}
// Validate all tool IDs exist before starting
for (let i = 0; i < pipeline.steps.length; i++) {
const step = pipeline.steps[i];
// Route content-aware resize to its dedicated tool
const resolvedToolId =
step.toolId === "resize" && step.settings?.contentAware
? "content-aware-resize"
: step.toolId;
const toolConfig = getToolConfig(resolvedToolId);
if (!toolConfig) {
return reply.status(400).send({
error: `Step ${i + 1} (${step.toolId}): Tool not found or not available`,
});
}
// Guard: check if the tool's AI feature bundle is installed
if (!isToolInstalled(resolvedToolId)) {
const bundle = getBundleForTool(resolvedToolId);
return reply.status(501).send({
error: `Step ${i + 1} (${step.toolId}): Feature "${bundle?.name}" is not installed`,
code: "FEATURE_NOT_INSTALLED",
feature: TOOL_BUNDLE_MAP[resolvedToolId],
featureName: bundle?.name ?? resolvedToolId,
});
}
// Validate the settings for this tool
const settingsResult = toolConfig.settingsSchema.safeParse(step.settings);
if (!settingsResult.success) {
return reply.status(400).send({
error: `Step ${i + 1} (${step.toolId}): Invalid settings`,
details: settingsResult.error.issues.map(
(iss: { path: (string | number)[]; message: string }) => ({
path: iss.path.join("."),
message: iss.message,
}),
),
});
}
}
// Execute the pipeline: pass the buffer through each step sequentially
const startTime = Date.now();
let currentBuffer = fileBuffer;
let currentFilename = filename;
const stepResults: Array<{ step: number; toolId: string; size: number }> = [];
try {
for (let i = 0; i < pipeline.steps.length; i++) {
const step = pipeline.steps[i];
// Route content-aware resize to its dedicated tool
const resolvedToolId =
step.toolId === "resize" && step.settings?.contentAware
? "content-aware-resize"
: step.toolId;
const toolConfig = getToolConfig(resolvedToolId);
if (!toolConfig) {
return reply.status(400).send({
error: `Step ${i + 1} (${step.toolId}): Tool not found or not available`,
});
}
try {
const settings = toolConfig.settingsSchema.parse(step.settings);
const result = await toolConfig.process(currentBuffer, settings, currentFilename);
stepResults.push({
step: i + 1,
toolId: step.toolId,
size: result.buffer.length,
});
currentBuffer = result.buffer;
currentFilename = result.filename;
} catch (stepErr) {
const msg = stepErr instanceof Error ? stepErr.message : "Processing failed";
throw new Error(`Step ${i + 1} (${step.toolId}): ${msg}`);
}
}
} catch (err) {
const message = err instanceof Error ? err.message : "Pipeline processing failed";
trackEvent(request, ANALYTICS_EVENTS.PIPELINE_EXECUTED, {
step_count: pipeline.steps.length,
tool_ids: pipeline.steps.map((s: { toolId: string }) => s.toolId),
is_batch: false,
duration_ms: Date.now() - startTime,
status: "failed",
});
return reply.status(422).send({
error: message,
completedSteps: stepResults,
});
}
// Save the final output to workspace
const jobId = randomUUID();
const workspacePath = await createWorkspace(jobId);
const outputPath = join(workspacePath, "output", currentFilename);
await writeFile(outputPath, currentBuffer);
// Also save the original input for reference
const inputPath = join(workspacePath, "input", filename);
await writeFile(inputPath, fileBuffer);
trackEvent(request, ANALYTICS_EVENTS.PIPELINE_EXECUTED, {
step_count: pipeline.steps.length,
tool_ids: pipeline.steps.map((s: { toolId: string }) => s.toolId),
is_batch: false,
duration_ms: Date.now() - startTime,
status: "completed",
});
return reply.send({
jobId,
downloadUrl: `/api/v1/download/${jobId}/${encodeURIComponent(currentFilename)}`,
originalSize: fileBuffer.length,
processedSize: currentBuffer.length,
stepsCompleted: stepResults.length,
steps: stepResults,
});
});
/**
* POST /api/v1/pipeline/save
*
* Save a named pipeline definition for later reuse.
*/
app.post("/api/v1/pipeline/save", async (request: FastifyRequest, reply: FastifyReply) => {
const user = requireAuth(request, reply);
if (!user) return;
const body = request.body as unknown;
const result = savePipelineSchema.safeParse(body);
if (!result.success) {
return reply.status(400).send({
error: "Invalid pipeline definition",
details: result.error.issues.map((i) => ({
path: i.path.join("."),
message: i.message,
})),
});
}
const { name, description, steps } = result.data;
// Validate all tool IDs exist
for (let i = 0; i < steps.length; i++) {
const toolConfig = getToolConfig(steps[i].toolId);
if (!toolConfig) {
return reply.status(400).send({
error: `Step ${i + 1}: Tool "${steps[i].toolId}" not found`,
});
}
}
const id = randomUUID();
db.insert(schema.pipelines)
.values({
id,
userId: user.id,
name,
description: description ?? null,
steps: JSON.stringify(steps),
})
.run();
return reply.status(201).send({
id,
name,
description: description ?? null,
steps,
createdAt: new Date().toISOString(),
});
});
/**
* GET /api/v1/pipeline/list
*
* List all saved pipelines.
*/
app.get("/api/v1/pipeline/list", async (request: FastifyRequest, reply: FastifyReply) => {
const user = requireAuth(request, reply);
if (!user) return;
// Admins see all pipelines; regular users see their own + legacy (no owner)
const allRows = db.select().from(schema.pipelines).all();
const rows = hasEffectivePermission(user, "pipelines:all")
? allRows
: allRows.filter((row) => !row.userId || row.userId === user.id);
const pipelines = rows.map((row) => ({
id: row.id,
name: row.name,
description: row.description,
steps: JSON.parse(row.steps),
createdAt: row.createdAt.toISOString(),
}));
return reply.send({ pipelines });
});
/**
* DELETE /api/v1/pipeline/:id
*
* Delete a saved pipeline by its ID.
*/
app.delete(
"/api/v1/pipeline/:id",
async (request: FastifyRequest<{ Params: { id: string } }>, reply: FastifyReply) => {
const user = requireAuth(request, reply);
if (!user) return;
const { id } = request.params;
const existing = db.select().from(schema.pipelines).where(eq(schema.pipelines.id, id)).get();
if (!existing) {
return reply.status(404).send({ error: "Pipeline not found" });
}
// Only the owner (or admin) can delete; legacy pipelines (no owner) can be deleted by anyone
if (
existing.userId &&
existing.userId !== user.id &&
!hasEffectivePermission(user, "pipelines:all")
) {
return reply.status(403).send({ error: "Not authorized to delete this pipeline" });
}
db.delete(schema.pipelines).where(eq(schema.pipelines.id, id)).run();
return reply.send({ ok: true });
},
);
/**
* GET /api/v1/pipeline/tools
*
* Returns the IDs of tools that can be used as pipeline steps.
* Only tools registered via createToolRoute() support pipeline execution.
*/
app.get("/api/v1/pipeline/tools", async (_request: FastifyRequest, reply: FastifyReply) => {
return reply.send({ toolIds: getRegisteredToolIds() });
});
/**
* POST /api/v1/pipeline/batch
*
* Accepts multipart with multiple files + a "pipeline" JSON field.
* Runs the full pipeline on each file with concurrency control via p-queue.
* Returns a ZIP containing all processed results.
*/
app.post("/api/v1/pipeline/batch", async (request: FastifyRequest, reply: FastifyReply) => {
// ── Parse multipart ──────────────────────────────────────────────
interface ParsedFile {
buffer: Buffer;
filename: string;
}
const files: ParsedFile[] = [];
let pipelineRaw: string | null = null;
let clientJobId: string | null = null;
try {
const parts = request.parts();
for await (const part of parts) {
if (part.type === "file") {
const chunks: Buffer[] = [];
for await (const chunk of part.file) {
chunks.push(chunk);
}
const buffer = Buffer.concat(chunks);
if (buffer.length > 0) {
files.push({
buffer,
filename: sanitizeFilename(part.filename ?? "image"),
});
}
} else if (part.fieldname === "pipeline") {
pipelineRaw = part.value as string;
} else if (part.fieldname === "clientJobId") {
clientJobId = part.value as string;
}
}
} catch (err) {
return reply.status(400).send({
error: "Failed to parse multipart request",
details: err instanceof Error ? err.message : String(err),
});
}
if (files.length === 0) {
return reply.status(400).send({ error: "No image files provided" });
}
// Enforce batch size limit
if (env.MAX_BATCH_SIZE > 0 && files.length > env.MAX_BATCH_SIZE) {
return reply.status(400).send({
error: `Too many files. Maximum batch size is ${env.MAX_BATCH_SIZE}`,
});
}
// ── Parse and validate pipeline definition ───────────────────────
if (!pipelineRaw) {
return reply.status(400).send({ error: "No pipeline definition provided" });
}
let pipeline: z.infer<typeof pipelineDefinitionSchema>;
try {
const parsed = JSON.parse(pipelineRaw);
const result = pipelineDefinitionSchema.safeParse(parsed);
if (!result.success) {
return reply.status(400).send({
error: "Invalid pipeline definition",
details: formatZodErrors(result.error.issues),
});
}
pipeline = result.data;
} catch {
return reply.status(400).send({ error: "Pipeline must be valid JSON" });
}
// Validate all tool IDs exist and settings are valid before processing
for (let i = 0; i < pipeline.steps.length; i++) {
const step = pipeline.steps[i];
const toolConfig = getToolConfig(step.toolId);
if (!toolConfig) {
return reply.status(400).send({
error: `Step ${i + 1}: Tool "${step.toolId}" not found`,
});
}
// Guard: check if the tool's AI feature bundle is installed
if (!isToolInstalled(step.toolId)) {
const bundle = getBundleForTool(step.toolId);
return reply.status(501).send({
error: `Step ${i + 1} (${step.toolId}): Feature "${bundle?.name}" is not installed`,
code: "FEATURE_NOT_INSTALLED",
feature: TOOL_BUNDLE_MAP[step.toolId],
featureName: bundle?.name ?? step.toolId,
});
}
const settingsResult = toolConfig.settingsSchema.safeParse(step.settings);
if (!settingsResult.success) {
return reply.status(400).send({
error: `Step ${i + 1} (${step.toolId}): Invalid settings`,
details: settingsResult.error.issues.map(
(iss: { path: (string | number)[]; message: string }) => ({
path: iss.path.join("."),
message: iss.message,
}),
),
});
}
}
// ── Progress tracking ────────────────────────────────────────────
const batchStartTime = Date.now();
const jobId = clientJobId || randomUUID();
const progress: JobProgress = {
jobId,
status: "processing",
totalFiles: files.length,
completedFiles: 0,
failedFiles: 0,
errors: [],
};
updateJobProgress({ ...progress });
// ── Process files through the pipeline with concurrency control ──
const queue = new PQueue({ concurrency: resolveConcurrency(env) });
const results: ({ buffer: Buffer; filename: string } | null)[] = new Array(files.length).fill(
null,
);
try {
const tasks = files.map((file, index) =>
queue.add(async () => {
progress.currentFile = file.filename;
updateJobProgress({ ...progress });
// Validate the image
const validation = await validateImageBuffer(file.buffer, file.filename);
if (!validation.valid) {
progress.failedFiles++;
progress.errors.push({
filename: file.filename,
error: `Invalid image: ${validation.reason}`,
});
progress.completedFiles++;
updateJobProgress({ ...progress });
return;
}
try {
let currentBuffer = file.buffer;
let currentFilename = file.filename;
// Decode HEIC/HEIF if needed
if (validation.format === "heif") {
currentBuffer = await decodeHeic(currentBuffer);
const ext = currentFilename.match(/\.[^.]+$/)?.[0];
if (ext) currentFilename = `${currentFilename.slice(0, -ext.length)}.png`;
}
// Decode CLI-decoded formats (RAW, TGA, PSD, EXR, HDR)
if (needsCliDecode(validation.format)) {
currentBuffer = await decodeToSharpCompat(currentBuffer, validation.format);
const ext = currentFilename.match(/\.[^.]+$/)?.[0];
if (ext) currentFilename = `${currentFilename.slice(0, -ext.length)}.png`;
}
// Sanitize SVG or normalize EXIF orientation
if (isSvgBuffer(currentBuffer)) {
currentBuffer = sanitizeSvg(currentBuffer);
} else {
currentBuffer = await autoOrient(currentBuffer);
}
// Run through all pipeline steps sequentially
for (let i = 0; i < pipeline.steps.length; i++) {
const step = pipeline.steps[i];
// Route content-aware resize to its dedicated tool
const resolvedToolId =
step.toolId === "resize" && step.settings?.contentAware
? "content-aware-resize"
: step.toolId;
const toolConfig = getToolConfig(resolvedToolId);
if (!toolConfig) {
throw new Error(`Step ${i + 1} (${step.toolId}): Tool not found or not available`);
}
try {
const settings = toolConfig.settingsSchema.parse(step.settings);
const result = await toolConfig.process(currentBuffer, settings, currentFilename);
currentBuffer = result.buffer;
currentFilename = result.filename;
} catch (stepErr) {
const msg = stepErr instanceof Error ? stepErr.message : "Processing failed";
throw new Error(`Step ${i + 1} (${step.toolId}): ${msg}`);
}
}
results[index] = { buffer: currentBuffer, filename: currentFilename };
progress.completedFiles++;
updateJobProgress({ ...progress });
} catch (err) {
progress.failedFiles++;
progress.errors.push({
filename: file.filename,
error: err instanceof Error ? err.message : "Pipeline processing failed",
});
progress.completedFiles++;
updateJobProgress({ ...progress });
}
}),
);
await Promise.all(tasks);
} catch (err) {
request.log.error({ err }, "Unexpected error in pipeline batch queue");
}
// ── Finalize progress ────────────────────────────────────────────
progress.status = progress.failedFiles === progress.totalFiles ? "failed" : "completed";
progress.currentFile = undefined;
updateJobProgress({ ...progress });
// ── Deduplicate output filenames ─────────────────────────────────
const usedNames = new Set<string>();
function getUniqueName(name: string): string {
if (!usedNames.has(name)) {
usedNames.add(name);
return name;
}
const dotIdx = name.lastIndexOf(".");
const base = dotIdx > 0 ? name.slice(0, dotIdx) : name;
const ext = dotIdx > 0 ? name.slice(dotIdx) : "";
let counter = 1;
let candidate = `${base}_${counter}${ext}`;
while (usedNames.has(candidate)) {
counter++;
candidate = `${base}_${counter}${ext}`;
}
usedNames.add(candidate);
return candidate;
}
const fileResultsMap: Record<string, string> = {};
for (let i = 0; i < results.length; i++) {
const entry = results[i];
if (entry) {
const uniqueName = getUniqueName(entry.filename);
entry.filename = uniqueName;
fileResultsMap[String(i)] = uniqueName;
}
}
// If every file failed, return an error instead of an empty ZIP
if (progress.status === "failed") {
trackEvent(request, ANALYTICS_EVENTS.PIPELINE_EXECUTED, {
step_count: pipeline.steps.length,
tool_ids: pipeline.steps.map((s: { toolId: string }) => s.toolId),
is_batch: true,
file_count: files.length,
duration_ms: Date.now() - batchStartTime,
status: "failed",
});
return reply.status(422).send({
error: "All files failed processing",
errors: progress.errors,
});
}
trackEvent(request, ANALYTICS_EVENTS.PIPELINE_EXECUTED, {
step_count: pipeline.steps.length,
tool_ids: pipeline.steps.map((s: { toolId: string }) => s.toolId),
is_batch: true,
file_count: files.length,
duration_ms: Date.now() - batchStartTime,
status: "completed",
});
// ── Stream ZIP response ──────────────────────────────────────────
reply.hijack();
reply.raw.writeHead(200, {
"Content-Type": "application/zip",
"Content-Disposition": `attachment; filename="pipeline-batch-${jobId.slice(0, 8)}.zip"`,
"Transfer-Encoding": "chunked",
"X-Job-Id": jobId,
"X-File-Results": JSON.stringify(fileResultsMap),
});
const archive = archiver("zip", { zlib: { level: 5 } });
archive.on("error", (err) => {
request.log.error({ err }, "Archiver error during pipeline batch processing");
if (!reply.raw.writableEnded) {
reply.raw.end();
}
});
archive.pipe(reply.raw);
// Append results in original upload order
for (const result of results) {
if (result) {
archive.append(result.buffer, { name: result.filename });
}
}
await archive.finalize();
});
app.log.info("Pipeline routes registered");
}