CVE-2025-62610

Oct. 22, 2025, 9:12 p.m.

8.1
High

Description

Hono is a Web application framework that provides support for any JavaScript runtime. In versions from 1.1.0 to before 4.10.2, Hono’s JWT Auth Middleware does not provide a built-in aud (Audience) verification option, which can cause confused-deputy / token-mix-up issues: an API may accept a valid token that was issued for a different audience (e.g., another service) when multiple services share the same issuer/keys. This can lead to unintended cross-service access. Hono’s docs list verification options for iss/nbf/iat/exp only, with no aud support; RFC 7519 requires that when an aud claim is present, tokens MUST be rejected unless the processing party identifies itself in that claim. This issue has been patched in version 4.10.2.

Product(s) Impacted

Vendor Product Versions
Hono
  • Hono
  • 1.1.0-*, *, 4.10.2

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-285
Improper Authorization
The product does not perform or incorrectly performs an authorization check when an actor attempts to access a resource or perform an action.

*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 hono hono 1.1.0-* / / / / / / /
a hono hono / / / / / / / /
a hono hono 4.10.2 / / / / / / /

CVSS Score

8.1 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: Oct. 22, 2025, 8:15 p.m.
Last Modified: Oct. 22, 2025, 9:12 p.m.

Status : Awaiting Analysis

CVE has been marked for Analysis. Normally once in this state the CVE will be analyzed by NVD staff within 24 hours.

More info

Source

security-advisories@github.com

*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.