CVE-2026-4526 in EmberZNet
Summary
by MITRE • 06/25/2026
In EmberZNet v9.0.2 and earlier, malformed global ZCL messages can trigger out-of-bounds reads in framework parsing logic and terminate the process. These messages must come from a device that has already joined the network, and no information leakage back to the sender was observed.
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Analysis
by VulDB Data Team • 06/25/2026
This vulnerability exists within EmberZNet v9.0.2 and earlier versions where the framework fails to properly validate incoming global ZCL messages during parsing operations. The flaw manifests as out-of-bounds read conditions that occur when malformed messages are processed by the Zigbee Cluster Library parsing logic. These messages must originate from devices that have successfully joined the network, indicating that the vulnerability exploits a trust relationship rather than bypassing initial authentication mechanisms. The parsing error results in process termination rather than simply ignoring the malformed data, creating a denial of service condition that affects the entire network coordinator or router functionality.
The technical implementation involves improper input validation within the ZCL message handling code where buffer boundaries are not adequately checked during message parsing operations. This represents a classic buffer over-read vulnerability that falls under CWE-125 in the Common Weakness Enumeration catalog, specifically addressing out-of-bounds read conditions in memory management. The vulnerability operates at the application layer of the Zigbee protocol stack where ZCL messages are interpreted and processed, making it particularly dangerous as it can disrupt legitimate network operations without requiring special privileges or bypassing network security mechanisms.
From an operational perspective, this vulnerability creates significant risks for Zigbee-based IoT deployments where network stability is critical. The process termination effect means that any legitimate device within the network could trigger a complete service disruption through a single malformed message. Network administrators cannot rely on the assumption that joined devices will behave properly since malicious actors or compromised devices could exploit this weakness to create persistent denial of service conditions. The vulnerability does not appear to allow information leakage back to the sender, which suggests that while it can cause system instability, it may not enable data exfiltration through this specific vector.
The attack surface is limited to devices already within the network, requiring an attacker to first compromise or gain access to a legitimate network member. This constraint reduces the initial attack complexity but does not eliminate the threat since compromised devices are common in IoT environments. The vulnerability aligns with ATT&CK technique T1499.001 which covers network denial of service attacks targeting network infrastructure components. Organizations should implement immediate mitigation strategies including firmware updates to EmberZNet v9.0.3 or later versions that contain the necessary parsing validation fixes. Additionally, network monitoring should be enhanced to detect unusual message patterns that could indicate exploitation attempts, and access controls should be strengthened to prevent unauthorized device additions to the network.
Network resilience measures should include implementing redundant coordinator systems and establishing automated recovery procedures to minimize downtime from process termination events. The vulnerability demonstrates the importance of robust input validation in embedded IoT systems where resource constraints may limit defensive capabilities. Security teams should also consider implementing message filtering mechanisms at network boundaries to detect and block malformed ZCL messages before they reach vulnerable endpoints. Regular security assessments of Zigbee networks are essential to identify similar parsing vulnerabilities in other protocol implementations that could present analogous risks to network stability and availability.