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PatchSiren cyber security CVE debrief

CVE-2026-92581 WWBN CVE debrief

CVE-2026-92581 is a vulnerability in AVideo that allows authenticated attackers to drive video like counts arbitrarily negative by sending array-typed like parameters followed by ordinary requests. This corruption persists in the denormalized counter until manual repair. The vulnerability affects AVideo instances, specifically impacting the like counter functionality. Defenders should assess exposure and prioritize patching or verifying instances to prevent potential abuse. The vulnerability has a medium severity and is exploitable by authenticated attackers.

Vendor
WWBN
Product
AVideo
CVSS
MEDIUM 5.3
CISA KEV
Not listed in stored evidence
Original CVE published
2026-09-16
Original CVE updated
2026-09-22
Advisory published
2026-09-16
Advisory updated
2026-09-22

Who should care

Defenders responsible for AVideo instances should assess exposure and prioritize patching or verifying instances to prevent potential abuse. This includes reviewing compensating controls for exposed systems while remediation is scheduled and verified. Defenders should also monitor video like counts for unusual activity and consider manual repair of denormalized counters if exploitation is suspected.

Why it matters

CVE-2026-92581 is a medium-severity vulnerability in AVideo that allows authenticated attackers to manipulate video like counts. Defenders should prioritize verifying and patching instances to prevent potential abuse.

  • Potential for attackers to manipulate video like counts
  • Denormalized counter corruption persisting until manual repair
  • Need for verification and patching of AVideo instances
  • Possible impact on video content reputation or analytics

Technical summary

The Like::__construct() method in AVideo performs counter arithmetic on raw request values before validation, allowing array-typed parameters to desynchronize stored votes from counters. This can be exploited by authenticated attackers to drive video like counts arbitrarily negative. The vulnerability affects AVideo instances and has a medium severity. Defenders should prioritize verifying and patching AVideo instances to prevent potential abuse of this vulnerability. The vulnerability can be mitigated by implementing input validation and sanitization for like parameters.

Defensive priority

Defenders should prioritize verifying and patching AVideo instances to prevent potential abuse of this vulnerability.

Recommended defensive actions

  • Verify AVideo instance version and check for patch availability
  • Implement input validation and sanitization for like parameters
  • Monitor video like counts for unusual activity
  • Consider manual repair of denormalized counters if exploitation is suspected
  • Review compensating controls for exposed systems while remediation is scheduled and verified
  • Track exceptions, retest remediated assets, and close the item only after evidence is documented
  • Confirm whether affected product deployments exist in managed environments and assign an owner for follow-up

Evidence notes

The vulnerability was reported through the CVE Program and detailed in the NVD. Additional information was provided by Vulncheck and GitHub. The CVE record was published on 2026-09-16T22:18:28.470Z and has not been modified since then. The vulnerability affects AVideo instances, and defenders should verify instances to prevent potential abuse.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-92581 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-92581

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-92581 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-92581

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.