T1071 Application Layer Protocol

This diagnostic statement provides for implementation of methods to block similar future attacks via security tools such as antivirus and IDS/IPS to provide protection against threats and exploitation attempts.

This diagnostic statement protects against adversaries that may try to utilize different protocols, such as web browsing, transferring files, email, from attacking at the OSI level. Network intrusion detection and prevention systems that use network signatures to identify traffic for specific adversary malware can be used to mitigate activity at the network level.

This diagnostic statement describes how the organization establishes and manages baseline measures of network activity. Supported by network monitoring tools and other controls to detect events and identify incidents. Mitigating mechanisms may include: Data Loss Prevention (DLP); Filtering Network Traffic; Limit Network Traffic; Network Intrusion Prevention Systems (NIPS); and Network Segmentation for these type of network-based techniques.

This diagnostic statement provides protection through secure network device configurations (e.g., firewall rules, ports, protocols) aligned to security baselines. Using network appliances to block or filter network traffic that is not necessary within the environment can mitigate adversary use of application layer protocols.

This diagnostic statement protects against Application Layer Protocol through the use of secure network configurations, architecture, implementations of zero trust architecture, and segmentation.

This diagnostic statement protects against Application Layer Protocol through the use of limiting access to resources to only authorized devices, management of personal computing devices, network intrusion prevention, and the use of antimalware.

This control can identify connections to known malicious sites. Scored minimal since the malicious sites must be on block list.

Can detect potential DNS protocol misuse/anomalies. Technique coverage is restricted to DNS and therefore results in a Minimal score.

This control can be used forensically to identify clients that communicated with identified C2 hosts via DNS.

This control can identify anomalous traffic with respect to NSG and application layer protocols.

This control can protect against command and control via application layer protocol.

This control can detect one of the sub-techniques of this technique while not providing detection for the remaining, resulting in a Minimal overall score.

This control can protect against one of the sub-techniques of this technique while not providing protection for the remaining, resulting in a Minimal overall score.

Cloud NGFW can allow or deny traffic based on the traffic's protocol, destination ports, sources, and destinations. This functionality can be used to block malicious or unwanted traffic leveraging application layer protocols. Given this supports all sub-techniques, the mapping is given a score of Significant.

Google Security Ops is able to trigger an alert based on suspicious modifications to the network infrastructure. This technique was scored as minimal based on low or uncertain detection coverage factor. https://github.com/chronicle/detection-rules/tree/main/gcp_cloudaudit https://github.com/chronicle/detection-rules/blob/main/gcp_cloudaudit/gcp_vpc_network_changes.yaral

GuardDuty flags events matching the following finding types that relate to adversaries attempting to communicate using application layer protocols to avoid detection. UnauthorizedAccess:EC2/MaliciousIPCaller.Custom Trojan:EC2/DropPoint!DNS Trojan:EC2/DropPoint Backdoor:EC2/C&CActivity.B!DNS Trojan:EC2/BlackholeTraffic Trojan:EC2/BlackholeTraffic!DNS

The following AWS IoT Device Defender cloud-side detection metrics can detect indicators that an adversary may be leveraging compromised AWS IoT devices and application layer protocols - especially the Message Queuing Telemetry Transport (MQTT) protocol - to communicate for command and control purposes: "Source IP" ("aws:source-ip-address") values outside of expected IP address ranges may suggest that a device has been stolen. "Messages sent" ("aws:num-messages-sent"), "Messages received" ("aws:num-messages-received"), and "Message size" ("aws:message-byte-size") values outside of expected norms may indicate that devices are sending and/or receiving non-standard traffic, which may include command and control traffic. The following AWS IoT Device Defender device-side detection metrics can detect indicators that an adversary may be leveraging compromised AWS IoT devices and application layer protocols - especially the Message Queuing Telemetry Transport (MQTT) protocol - to communicate for command and control purposes: "Destination IPs" ("aws:destination-ip-addresses") outside of expected IP address ranges may suggest that a device is communicating with unexpected parties. "Bytes in" ("aws:all-bytes-in"), "Bytes out" ("aws:all-bytes-out"), "Packets in" ("aws:all-packets-in"), and "Packets out" ("aws:all-packets-out") values outside of expected norms may indicate that the device is sending and/or receiving non-standard traffic, which may include command and control traffic. "Listening TCP ports" ("aws:listening-tcp-ports"), "Listening TCP port count" ("aws:num-listening-tcp-ports"), "Established TCP connections count" ("aws:num-established-tcp-connections"), "Listening UDP ports" ("aws:listening-udp-ports"), and "Listening UDP port count" ("aws:num-listening-udp-ports") values outside of expected norms may indicate that devices are communicating via unexpected ports/protocols that may suggest application layer command and control traffic. Coverage factor is minimal, since these metrics are limited to IoT device communication and none of this technique's sub-techniques are addressed, resulting in an overall score of Minimal.

AWS Network Firewall has the ability to pass, drop, or alert on traffic based on the network protocol as well as perform deep packet inspection on the payload. This functionality can be used to block malicious or unwanted traffic leveraging application layer protocols. Given this supports all sub-techniques, the mapping is given a score of Significant.

AWS WAF protects against this by inspecting incoming requests and blocking malicious traffic. AWS WAF uses the following rule sets to provide this protection. AWSManagedRulesCommonRuleSet AWSManagedRulesAdminProtectionRuleSet AWSManagedRulesKnownBadInputsRuleSet AWSManagedRulesSQLiRuleSet AWSManagedRulesLinuxRuleSet AWSManagedRulesUnixRuleSet AWSManagedRulesWindowsRuleSet AWSManagedRulesPHPRuleSet AWSManagedRulesWordPressRuleSet AWSManagedRulesBotControlRuleSet This is scored as Minimal because the rule sets only protect against a subset of the sub-techniques (1 of 4).