security: fix SQL injection in semantic search - use parameterized queries with bind params

- Replace string interpolation in $queryRawUnsafe with bind params ($1, $2...)
- Add assertSafeId() validation for userId, notebookId, noteId
- ftsSearch: bind query, userId, notebookId as parameters
- vectorSearch: bind vector string, userId, notebookId, threshold as parameters
- indexNote: already used bind params, added noteId validation
- Fixes CRITICAL security audit finding #1

memento-note/lib/ai/services/semantic-search.service.ts

@@ -7,6 +7,7 @@
  *   3. Reciprocal Rank Fusion (RRF) for final ranking
  *
  * All vector operations happen in the database — no JS cosine-similarity loops.
+ * All SQL uses parameterized queries ($1, $2…) via Prisma $queryRawUnsafe with bind params.
  */
 
 import { embeddingService } from './embedding.service'
@@ -30,6 +31,13 @@ export interface SearchOptions {
   defaultTitle?: string
 }
 
+/** Validate that a value looks like a CUID/UUID (alphanumeric + dashes). */
+function assertSafeId(value: string, label: string): void {
+  if (!/^[a-zA-Z0-9_-]+$/.test(value)) {
+    throw new Error(`Invalid ${label} format`)
+  }
+}
+
 export class SemanticSearchService {
   private readonly RRF_K = 60
   private readonly DEFAULT_LIMIT = 20
@@ -108,35 +116,60 @@ export class SemanticSearchService {
 
   /**
    * PostgreSQL full-text search using tsvector + GIN index.
-   * Returns ranked results using ts_rank.
+   * SECURITY: Uses $queryRawUnsafe with parameterized bind params ($1, $2…).
+   *           All IDs are validated via assertSafeId() before inclusion.
    */
   private async ftsSearch(
     query: string,
     userId: string | null,
     notebookId?: string
   ): Promise<Array<{ noteId: string; rank: number }>> {
-    const safeQuery = query.replace(/'/g, "''")
+    // Validate IDs before any SQL construction
+    if (userId) assertSafeId(userId, 'userId')
+    if (notebookId) assertSafeId(notebookId, 'notebookId')
 
-    const userClause = userId ? `AND "userId" = '${userId}'` : ''
-    const notebookClause = notebookId !== undefined
-      ? `AND "notebookId" ${notebookId ? `= '${notebookId.replace(/'/g, "''")}'` : 'IS NULL'}`
-      : ''
+    const params: any[] = []
+    let paramIdx = 0
 
-    const sql = `
-      SELECT id AS "noteId", ts_rank("tsv", plainto_tsquery('simple', '${safeQuery}')) AS rank
-      FROM "Note"
-      WHERE "tsv" @@ plainto_tsquery('simple', '${safeQuery}')
-        AND "trashedAt" IS NULL
-        AND "isArchived" = false
-        ${userClause}
-        ${notebookClause}
-      ORDER BY rank DESC
-      LIMIT ${this.FTS_CANDIDATES}
-    `
+    // Bind search query (used twice in the query)
+    params.push(query)
+    const queryParam1 = `$${++paramIdx}`
+    const queryParam2 = `$${++paramIdx}`
+    params.push(query) // second usage
 
-    const rows: Array<{ noteId: string; rank: number }> = await prisma.$queryRawUnsafe(sql)
+    // User filter
+    const userClause = userId ? `AND "userId" = $${++paramIdx}` : ''
+    if (userId) params.push(userId)
+
+    // Notebook filter
+    let notebookClause = ''
+    if (notebookId !== undefined) {
+      if (notebookId) {
+        notebookClause = `AND "notebookId" = $${++paramIdx}`
+        params.push(notebookId)
+      } else {
+        notebookClause = `AND "notebookId" IS NULL`
+      }
+    }
+
+    // Limit
+    params.push(this.FTS_CANDIDATES)
+    const limitParam = `$${++paramIdx}`
+
+    const rows: Array<{ noteId: string; rank: number }> = await prisma.$queryRawUnsafe(
+      `SELECT id AS "noteId",
+              ts_rank("tsv", plainto_tsquery('simple', ${queryParam1})) AS rank
+       FROM "Note"
+       WHERE "tsv" @@ plainto_tsquery('simple', ${queryParam2})
+         AND "trashedAt" IS NULL
+         AND "isArchived" = false
+         ${userClause}
+         ${notebookClause}
+       ORDER BY rank DESC
+       LIMIT ${limitParam}`,
+      ...params
+    )
 
-    const maxRank = rows.length > 0 ? rows[0].rank : 1
     return rows.map((r, i) => ({
       noteId: r.noteId,
       rank: i + 1
@@ -145,7 +178,9 @@ export class SemanticSearchService {
 
   /**
    * pgvector cosine-distance search using the HNSW index.
-   * Returns nearest neighbors above the similarity threshold.
+   * SECURITY: Uses $queryRawUnsafe with parameterized bind params ($1, $2…).
+   *           userId/notebookId validated via assertSafeId().
+   *           vecStr is internally generated from the embedding model output.
    */
   private async vectorSearch(
     query: string,
@@ -162,27 +197,56 @@ export class SemanticSearchService {
       return []
     }
 
+    // Validate IDs
+    if (userId) assertSafeId(userId, 'userId')
+    if (notebookId) assertSafeId(notebookId, 'notebookId')
+
     const vecStr = embeddingService.toVectorString(queryEmbedding)
-    const userClause = userId ? `AND n."userId" = '${userId}'` : ''
-    const notebookClause = notebookId !== undefined
-      ? `AND n."notebookId" ${notebookId ? `= '${notebookId.replace(/'/g, "''")}'` : 'IS NULL'}`
-      : ''
 
-    const sql = `
-      SELECT n.id AS "noteId",
-             1 - (e."embedding" <=> '${vecStr}'::vector) AS similarity
-      FROM "Note" n
-      INNER JOIN "NoteEmbedding" e ON e."noteId" = n.id
-      WHERE n."trashedAt" IS NULL
-        AND n."isArchived" = false
-        ${userClause}
-        ${notebookClause}
-        AND 1 - (e."embedding" <=> '${vecStr}'::vector) >= ${threshold}
-      ORDER BY e."embedding" <=> '${vecStr}'::vector ASC
-      LIMIT ${this.VECTOR_CANDIDATES}
-    `
+    const params: any[] = []
+    let paramIdx = 0
 
-    const rows: Array<{ noteId: string; similarity: number }> = await prisma.$queryRawUnsafe(sql)
+    // Vector parameter (used multiple times in the query)
+    params.push(vecStr)
+    const vecParam = `$${++paramIdx}::vector`
+
+    // User filter
+    const userClause = userId ? `AND n."userId" = $${++paramIdx}` : ''
+    if (userId) params.push(userId)
+
+    // Notebook filter
+    let notebookClause = ''
+    if (notebookId !== undefined) {
+      if (notebookId) {
+        notebookClause = `AND n."notebookId" = $${++paramIdx}`
+        params.push(notebookId)
+      } else {
+        notebookClause = `AND n."notebookId" IS NULL`
+      }
+    }
+
+    // Threshold
+    params.push(threshold)
+    const thresholdParam = `$${++paramIdx}`
+
+    // Limit
+    params.push(this.VECTOR_CANDIDATES)
+    const limitParam = `$${++paramIdx}`
+
+    const rows: Array<{ noteId: string; similarity: number }> = await prisma.$queryRawUnsafe(
+      `SELECT n.id AS "noteId",
+              1 - (e."embedding" <=> ${vecParam}) AS similarity
+       FROM "Note" n
+       INNER JOIN "NoteEmbedding" e ON e."noteId" = n.id
+       WHERE n."trashedAt" IS NULL
+         AND n."isArchived" = false
+         ${userClause}
+         ${notebookClause}
+         AND 1 - (e."embedding" <=> ${vecParam}) >= ${thresholdParam}
+       ORDER BY e."embedding" <=> ${vecParam} ASC
+       LIMIT ${limitParam}`,
+      ...params
+    )
 
     return rows.map((r, i) => ({
       noteId: r.noteId,
@@ -265,9 +329,14 @@ export class SemanticSearchService {
   /**
    * Generate or update embedding for a note.
    * Stores as native pgvector via raw SQL.
+   *
+   * SECURITY: Uses parameterized bind params ($1, $2).
+   *           noteId validated via assertSafeId().
    */
   async indexNote(noteId: string): Promise<void> {
     try {
+      assertSafeId(noteId, 'noteId')
+
       const note = await prisma.note.findUnique({
         where: { id: noteId },
         select: { content: true, lastAiAnalysis: true }
@@ -286,7 +355,7 @@ export class SemanticSearchService {
       const { embedding } = await embeddingService.generateEmbedding(note.content)
       const vecStr = embeddingService.toVectorString(embedding)
 
-      await prisma.$executeRawUnsafe(
+      await prisma.$queryRawUnsafe(
         `INSERT INTO "NoteEmbedding" ("id", "noteId", "embedding", "createdAt", "updatedAt")
          VALUES (gen_random_uuid(), $1, $2::vector, now(), now())
          ON CONFLICT ("noteId")