CVE-2026-40173

April 16, 2026, 1:16 p.m.

9.4
Critical

Description

Dgraph is an open source distributed GraphQL database. Versions 25.3.1 and prior contain an unauthenticated credential disclosure vulnerability where the /debug/pprof/cmdline endpoint is registered on the default mux and reachable without authentication, exposing the full process command line including the admin token configured via the --security "token=..." startup flag. An attacker can retrieve the leaked token and reuse it in the X-Dgraph-AuthToken header to gain unauthorized access to admin-only endpoints such as /admin/config/cache_mb, bypassing the adminAuthHandler token validation. This enables unauthorized privileged administrative access including configuration changes and operational control actions in any deployment where the Alpha HTTP port is reachable by untrusted parties. This issue has been fixed in version 25.3.2.

Product(s) Impacted

Vendor Product Versions
Dgraph
  • Dgraph
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-200
Exposure of Sensitive Information to an Unauthorized Actor
The product exposes sensitive information to an actor that is not explicitly authorized to have access to that information.

*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 dgraph dgraph / / / / / / / /

CVSS Score

9.4 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: NONE
  • Scope: UNCHANGED
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: LOW
  • CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:L

    View Vector String

Timeline

Published: April 15, 2026, 9:17 p.m.
Last Modified: April 16, 2026, 1:16 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.