CVE-2026-45327

June 5, 2026, 7:02 p.m.

8.2
High

Description

TinyIce is a streaming server for audio and video. In versions 0.8.95 through 2.4.1, missing authentication on WebRTC ingest endpoint allows unauthenticated stream injection. Version 2.5.0 fixes the issue by requiring either HTTP Basic auth or a `?password=` query parameter, comparing the supplied password against the per-mount source password (or the `default_source_password` fallback) using bcrypt, hooking into the existing brute-force IP rate-limiter (5 failed attempts per IP within 15 minutes triggers a lockout), and rejecting requests for mounts in `disabled_mounts`. The same release also tightens an adjacent endpoint, `POST /admin/golive/chunk`, which previously required session authentication but did not verify the session user's per-mount access nor check the CSRF token.

Product(s) Impacted

Vendor Product Versions
Tinyice
  • Tinyice
  • 0.8.95-2.4.1, 2.5.0

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-306
Missing Authentication for Critical Function
The product does not perform any authentication for functionality that requires a provable user identity or consumes a significant amount of resources.

*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 tinyice tinyice 0.8.95-2.4.1 / / / / / / /
a tinyice tinyice 2.5.0 / / / / / / /

CVSS Score

8.2 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: June 5, 2026, 6:17 p.m.
Last Modified: June 5, 2026, 7:02 p.m.

Status : Deferred

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.