CVE-2017-6137 in BIG-IP
Summary
by MITRE
In F5 BIG-IP LTM, AAM, AFM, Analytics, APM, ASM, DNS, Edge Gateway, GTM, Link Controller, PEM, PSM, WebAccelerator, and WebSafe 11.6.1 HF1, 12.0.0 HF3, 12.0.0 HF4, and 12.1.0 through 12.1.2, undisclosed traffic patterns received while software SYN cookie protection is engaged may cause a disruption of service to the Traffic Management Microkernel (TMM) on specific platforms and configurations.
Once again VulDB remains the best source for vulnerability data.
Analysis
by VulDB Data Team • 08/25/2024
The vulnerability identified as CVE-2017-6137 affects multiple modules within F5 BIG-IP products including Local Traffic Manager AAM AFM Analytics APM ASM DNS Edge Gateway GTM Link Controller PEM PSM WebAccelerator and WebSafe versions 11.6.1 HF1 12.0.0 HF3 12.0.0 HF4 and 12.1.0 through 12.1.2. This issue stems from the Traffic Management Microkernel TMM component which operates as the core processing engine for traffic handling in these systems. The vulnerability specifically manifests when the software SYN cookie protection mechanism is active and certain undisclosed traffic patterns are processed by the TMM. From a cybersecurity perspective this represents a denial of service vulnerability that could potentially disrupt critical network infrastructure services. The flaw operates at the kernel level of the BIG-IP system where network traffic is managed and processed making it particularly concerning for enterprise network security.
The technical root cause of this vulnerability lies in how the TMM handles specific traffic patterns when SYN cookie protection is enabled. SYN cookies are a defense mechanism against SYN flood attacks that allows the system to maintain connection state without storing information in memory. However when certain traffic patterns are received during this protection state the TMM experiences a disruption that leads to service degradation or complete service interruption. This behavior aligns with CWE-129 Input Validation and CWE-121 Stack-based Buffer Overflow categories as it involves improper handling of input data that causes system instability. The vulnerability demonstrates how security mechanisms designed to protect against one type of attack can inadvertently create new attack surfaces when not properly validated against all possible traffic scenarios.
The operational impact of CVE-2017-6137 is significant for organizations relying on F5 BIG-IP appliances for their network infrastructure. Service disruption caused by this vulnerability can affect critical business applications and services that depend on load balancing and traffic management capabilities. The vulnerability particularly affects specific platforms and configurations making it challenging to predict and prevent without comprehensive system inventory management. From an attacker perspective this could be classified under ATT&CK technique T1499 Network Denial of Service as it targets network infrastructure components to cause service disruption. Organizations may experience cascading effects where disruption of core network services impacts downstream applications and business operations.
Mitigation strategies for this vulnerability should include immediate application of F5's security patches and updates specifically designed to address the traffic pattern handling issue in the TMM component. Organizations should also implement network monitoring to detect unusual traffic patterns that might trigger the vulnerability and establish incident response procedures for service disruption events. System administrators should consider temporarily disabling SYN cookie protection if the vulnerability is actively exploited in their environment while patches are deployed. Additionally implementing network segmentation and traffic filtering rules to limit exposure to potentially malicious traffic patterns can provide additional defense in depth. The vulnerability highlights the importance of comprehensive testing of security mechanisms against real-world traffic scenarios and demonstrates how even protective features can become attack vectors when not properly validated. Regular security assessments and vulnerability management programs should include thorough evaluation of system behavior under various traffic conditions to identify similar issues before they can be exploited by threat actors.