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CVE-2026-86721 – Authentication Bypass / RTMP Stream Hijacking – WWBN AVideo (all versions through c

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Summary

CVE-2026-86721 is an authorization bypass vulnerability in WWBN AVideo that allows an unauthenticated attacker to hijack any user’s live RTMP broadcast. The flaw stems from AVideo’s handling of a session cookie named key, which improperly overrides the $_REQUEST['key'] parameter in saveLive.php and related endpoints. The issue carries a high severity rating and affects all AVideo versions up to commit c3edcc274c389816d434acadac07ee78eaf330c1.

Technical details

  • Root cause: saveLive.php and related live-streaming endpoints trust a session cookie named key; when that cookie is set to the value value, it overrides the $_REQUEST['key'] request parameter used to validate the stream key.
  • Trigger conditions: an attacker sets the key cookie to the known constant value value and submits a request to the live-streaming endpoint, bypassing the intended per-user stream key check.
  • Attack vector: network, no authentication or user interaction required (AV:N/PR:N/UI:N).
  • Impact: an attacker can publish video to any user’s RTMP stream without authentication, effectively hijacking or injecting content into that user’s live broadcast.

Affected software

  • WWBN AVideo — all versions through commit c3edcc274c389816d434acadac07ee78eaf330c1

Severity

  • CVSS Score: 8.7 (High)
  • Vector: CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N

Mitigation and recommended actions

  • Immediate: Upgrade to a version of AVideo that includes the fix committed after c3edcc274c389816d434acadac07ee78eaf330c1; consult the vendor’s GitHub security advisory (GHSA-5664-h9h4-3gwc) for the patched release.
  • If no patch can be applied immediately: restrict or disable public access to live-streaming endpoints (e.g., saveLive.php), block or strip client-supplied key cookies at a reverse proxy/WAF, and rotate/validate stream keys server-side rather than trusting request or cookie values.

How IONIX identifies potentially affected assets

IONIX matches the following signals against data already collected when it crawled the asset; identifying the technology sends no request beyond that crawl.

  • Page title: Sign In - AVideo, AVideo
  • Raw response body: id="avideoModal", avideoAlert(, avideoModalIframe(

References

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1

Map your entire attack surface (continously)

IONIX uses multi-factor discovery methods, including DNS analysis, certificate mapping, metadata inspection, and more, to automatically map every internet-facing asset across your environment. This includes cloud instances, third-party platforms, shadow IT, and even forgotten infrastructure that traditional tools miss.

2

Monitor for new CVEs

Dozens of threat intel feeds using agentic technology are continuously analyzed to detect the appearance of proof-of-concept code, exploit kits, and indicators of active targeting. IONIX goes further by applying AI to proactively evaluate whether emerging vulnerabilities are likely to be exploited, even before PoCs go public.

3

Identify Potential External Exposures

Not all CVEs matter. IONIX filters vulnerabilities by asking attacker-centric questions: Can it be reached from the internet? Does it require authentication? Is it being exploited in the wild? This dramatically reduces noise and focuses teams on threats that can actually be weaponized.

4

Create Safe, Scalable Exploit Validations

IONIX transforms real-world PoCs into safe, non-intrusive test payloads that can be run in production environments without disruption. These simulations are precisely targeted to the systems that are vulnerable, ensuring rapid validation without unnecessary load.

5

Execute Exploit Validations

By combining context about software stack, versioning, exposure status, and reachability, IONIX ensures that only the right payloads are executed against the right assets, maximizing efficiency and minimizing risk.

6

Drive Fast and Actionable Remediation

Results are routed through integrations with ticketing, SOAR, and SIEM tools. Issues are written in plain language, bundled into remediation clusters, and prioritized based on asset criticality, exploitability, and blast radius. This shortens mean time to remediation (MTTR) and empowers teams to act with confidence.

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