CVE-2026-92581 in AVideo
Summary
by MITRE • 09/17/2026
In AVideo through 29.0, Like::__construct() performs counter arithmetic on raw request values before validation, allowing array-typed parameters to desynchronize stored votes from counters. Authenticated attackers can send array-typed like parameters followed by ordinary requests to drive video like counts arbitrarily negative, with the corruption persisting in the denormalized counter until manual repair.
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Analysis
by VulDB Data Team • 09/17/2026
The vulnerability identified in AVideo versions through 29.0 represents a critical logic flaw within the application's interaction handling mechanism, specifically located in the Like::__construct() method. This function is responsible for processing user interactions with video content, particularly the tracking of likes and dislikes which are fundamental to social engagement metrics on the platform. The core technical deficiency lies in the order of operations performed by this constructor. It executes counter arithmetic using raw values directly extracted from HTTP request parameters before applying any form of validation or sanitization checks. This architectural decision creates a window where malformed input can manipulate internal state variables without triggering standard security controls designed to reject invalid data structures.
The specific nature of the flaw involves improper handling of array-typed parameters. When an authenticated user submits a request containing an array for the like parameter rather than a single integer value, the application's arithmetic logic fails to account for this structural anomaly correctly. Instead of rejecting the input or treating it as a null operation, the system proceeds with calculations that assume scalar values. This mismatch between expected data types and actual received data leads to desynchronization between the denormalized counter stored in the database and the actual count of valid interactions recorded elsewhere in the application's logic. The arithmetic operations performed on these raw array inputs result in unpredictable mathematical outcomes, effectively bypassing the intended constraints on vote counts.
The operational impact of this vulnerability is significant for both data integrity and system reliability. Authenticated attackers can exploit this flaw by sending specially crafted requests with array-typed like parameters followed by subsequent ordinary requests. This sequence allows them to drive video like counts arbitrarily negative, creating substantial discrepancies in displayed metrics. Because the corruption persists within the denormalized counter until manual repair is performed, the issue does not self-correct through normal application processes. This persistence means that once exploited, the affected videos will display incorrect engagement statistics indefinitely unless an administrator intervenes to reset or recalculate these counters manually. Such manipulation can distort user perception of content popularity and potentially impact recommendation algorithms that rely on accurate interaction data.
From a classification perspective, this vulnerability aligns with CWE-20 Improper Input Validation, as the application fails to adequately verify input parameters before processing them in critical logic paths. It also relates closely to CWE-682 Incorrect Calculation, where the arithmetic operations yield erroneous results due to unexpected input types. In terms of offensive security frameworks, this behavior is consistent with ATT&CK technique T1505.003 Server Software Component: Web Shell or similar data manipulation techniques that involve modifying stored application state through API abuse. The fact that authentication is required limits the attack surface but does not eliminate it, as compromised credentials can be leveraged to execute these manipulations at scale.
Mitigation strategies must address both immediate remediation and long-term architectural improvements. For organizations running affected versions of AVideo, the most effective immediate action is to upgrade to a patched version where this logic flaw has been corrected by developers who likely implemented proper type checking before arithmetic operations. In cases where upgrading is not immediately feasible, administrators should implement strict input validation at the web server or application gateway level to reject requests containing array-typed parameters for fields that expect scalar integers. Additionally, implementing database-level constraints and periodic reconciliation jobs can help detect and correct desynchronized counters automatically rather than relying on manual repair processes which are prone to human error and operational delays.