CVE-2026-47248

June 12, 2026, 7:16 p.m.

6.9
Medium

Description

Parse Server is an open source backend that can be deployed to any infrastructure that can run Node.js. Prior to versions 8.6.78 and 9.9.1-alpha.2, Parse Server's GraphQL endpoint discloses schema metadata to unauthenticated callers through Did you mean ...? suggestions embedded in GraphQL validation-error messages. An unauthenticated caller who knows only the public application id can iteratively send malformed queries to reconstruct class names, field names, argument names, mutation names, and input-object fields. This issue has been patched in versions 8.6.78 and 9.9.1-alpha.2.

Product(s) Impacted

Vendor Product Versions
Parse
  • Parse Server
  • 8.6.78, 9.9.1-alpha.2

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-209
Generation of Error Message Containing Sensitive Information
The product generates an error message that includes sensitive information about its environment, users, or associated data.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a parse parse_server 8.6.78 / / / / / / /
a parse parse_server 9.9.1-alpha.2 / / / / / / /

CVSS Score

6.9 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: LOW
  • Integrity Impact: NONE
  • Availability Impact: NONE
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

    View Vector String

Timeline

Published: June 12, 2026, 7:16 p.m.
Last Modified: June 12, 2026, 7:16 p.m.

Status : Received

CVE has been recently published to the CVE List and has been received by the NVD.

More info

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.