CVE-2020-1683 in Junos
Summary
by MITRE • 10/17/2020
On Juniper Networks Junos OS devices, a specific SNMP OID poll causes a memory leak which over time leads to a kernel crash (vmcore). Prior to the kernel crash other processes might be impacted, such as failure to establish SSH connection to the device. The administrator can monitor the output of the following command to check if there is memory leak caused by this issue: user@device> show system virtual-memory | match "pfe_ipc|kmem" pfe_ipc 147 5K - 164352 16,32,64,8192
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Analysis
by VulDB Data Team • 11/20/2020
The vulnerability described in CVE-2020-1683 represents a critical memory management flaw within Juniper Networks Junos OS operating systems that specifically affects SNMP-based monitoring operations. This issue manifests when certain SNMP Object Identifier (OID) queries are executed against affected devices, triggering a systematic memory leak in the kernel space. The vulnerability operates at the intersection of network management protocols and kernel memory allocation, creating a scenario where legitimate administrative monitoring activities inadvertently cause system instability. The flaw is particularly concerning because it affects the fundamental operating system components that manage network connectivity and system resources, making it a potential vector for service disruption attacks.
The technical implementation of this vulnerability involves improper memory handling during SNMP OID polling operations that target specific kernel memory pools. When the affected SNMP queries are processed, they cause incremental memory allocation without proper deallocation, leading to gradual memory exhaustion within the kernel's physical memory management structures. The pfe_ipc and kmem memory pools referenced in the monitoring command represent critical kernel components responsible for packet forwarding engine operations and kernel memory management respectively. The memory leak occurs in the kernel's memory allocator subsystem, which is governed by the underlying memory management architecture that follows standard operating system principles for virtual memory allocation and deallocation.
From an operational impact perspective, this vulnerability creates a cascading failure scenario where initial memory leaks eventually lead to complete system kernel crashes, resulting in vmcore generation and system downtime. The intermediate phase of memory exhaustion can cause significant service degradation, including the inability to establish new SSH connections to the device, which severely impacts administrative capabilities and system management operations. Network administrators may experience complete loss of remote access to affected devices, forcing them into potentially dangerous situations where physical access becomes necessary for recovery operations. This vulnerability directly impacts the availability and reliability of network infrastructure, particularly affecting devices that rely heavily on SNMP-based monitoring for operational management.
The mitigation strategies for CVE-2020-1683 should focus on immediate patch deployment and monitoring of memory utilization patterns. Organizations must implement proactive monitoring of the pfe_ipc and kmem memory pools using the provided command to detect early signs of memory leakage before system crashes occur. This vulnerability aligns with CWE-401: Improper Release of Memory and follows ATT&CK technique T1490: Inhibit System Recovery, as it creates conditions that prevent normal system operation and recovery processes. Network security teams should also consider implementing SNMP access controls to limit which systems can perform the specific OID queries that trigger this vulnerability, while also establishing baseline memory usage monitoring to detect anomalous patterns that may indicate exploitation attempts. The vulnerability demonstrates the importance of proper memory management in embedded network operating systems and highlights the need for comprehensive testing of management protocols against system resource exhaustion scenarios.