CVE-2026-79625 in Control RTE
Summary
by MITRE • 09/30/2026
Affected products do not properly synchronize access to their monitoring functionality. When multiple clients send concurrent requests, this may lead to incorrect reads or writes, or to corruption of internal memory structures. An authenticated remote attacker with monitoring access can exploit this issue to cause incorrect data processing or a denial-of-service condition.
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Analysis
by VulDB Data Team • 09/30/2026
The vulnerability described constitutes a classic race condition within the application logic responsible for handling concurrent requests against the system's monitoring functionality. This flaw arises from improper synchronization of shared resources, meaning that multiple threads or processes can access and modify critical data structures simultaneously without adequate locking mechanisms or atomic operations to ensure consistency. In software engineering terms, this is often categorized under CWE-362: Concurrent Execution using Shared Resource with Improper Synchronization (Race Condition). The core technical issue lies in the failure of the affected products to serialize access to internal memory structures that track monitoring states or metrics. When an authenticated remote attacker sends multiple concurrent requests targeting these endpoints, the application fails to properly lock the relevant data segments during read-modify-write cycles. This lack of synchronization allows for interleaved execution where one request may overwrite changes made by another before they are committed, leading to unpredictable behavior in how system state is maintained and reported.
The operational impact of this vulnerability is significant due to its potential to disrupt both data integrity and service availability. Because the flaw affects internal memory structures, an attacker can induce incorrect reads or writes that corrupt the monitoring subsystem's understanding of the environment it is observing. This corruption may result in inaccurate reporting of system health, performance metrics, or security events, which undermines the reliability of any automated responses or human decisions based on this data. More critically, the race condition can lead to a denial-of-service condition by causing internal memory corruption that crashes the monitoring service or forces the entire application into an unstable state requiring restart. This is particularly dangerous in production environments where continuous monitoring is essential for operational visibility and incident response capabilities. The requirement for authentication limits the attack surface slightly but does not eliminate it, as insider threats or compromised legitimate accounts can still exploit this flaw to degrade system reliability.
From a threat modeling perspective, this vulnerability aligns with ATT&CK technique T1496: Resource Hijacking if exploited to consume excessive resources during the race condition, or potentially T1530: Data from Cloud Storage Object if the corruption leads to data exfiltration through malformed responses, though primarily it serves as a mechanism for service disruption. The exploitation vector is remote and requires authentication, which classifies it under CWE-287: Improper Authentication if the attacker bypasses initial checks, but more accurately reflects CWE-364 in its execution phase. To mitigate this risk, developers must implement robust concurrency controls within the monitoring module. This includes using thread-safe data structures, implementing fine-grained locking mechanisms around critical sections of code that access shared memory, or utilizing atomic operations for simple counter updates where appropriate. Additionally, introducing request throttling can reduce the likelihood of triggering race conditions by limiting the rate at which concurrent requests are processed. Regular security testing focused on concurrency issues, such as fuzzing with high-concurrency scenarios and static analysis for synchronization errors, is essential to identify and resolve these latent defects before they reach production environments.