Detections

Once adversaries leverage serverless functions as infrastructure (ex: for command and control), it may be possible to look for unique characteristics associated with adversary software, if known.[1] Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle.

Monitor network data for uncommon data flows. Processes utilizing the network that do not normally have network communication or have never been seen before are suspicious. Monitor for suspicious email activity, such as numerous accounts receiving messages from a single unusual/unknown sender. Filtering based on DKIM+SPF or header analysis can help detect when the email sender is spoofed.[1][2] Monitor and analyze traffic patterns and packet inspection associated to protocol(s) that do not follow the expected protocol standards and traffic flows (e.g extraneous packets that do not belong to established flows, gratuitous or anomalous traffic patterns, anomalous syntax, or structure). Consider correlation with process monitoring and command line to detect anomalous processes execution and command line arguments associated to traffic patterns (e.g. monitor anomalies in use of files that do not normally initiate connections for respective protocol(s)).

Much of this activity may have a very high occurrence and associated false positive rate, as well as potentially taking place outside the visibility of the target organization, making detection difficult for defenders.

Monitor and analyze traffic patterns and packet inspection associated to protocol(s) that do not follow the expected protocol standards and traffic flows (e.g extraneous packets that do not belong to established flows, gratuitous or anomalous traffic patterns, anomalous syntax, or structure). Consider correlation with process monitoring and command line to detect anomalous processes execution and command line arguments associated to traffic patterns (e.g. monitor anomalies in use of files that do not normally initiate connections for respective protocol(s)). Monitor network data for uncommon data flows. Processes utilizing the network that do not normally have network communication or have never been seen before are suspicious.

Monitor for suspicious network traffic that could be indicative of scanning, such as large quantities originating from a single source (especially if the source is known to be associated with an adversary/botnet).

Much of this activity may have a very high occurrence and associated false positive rate, as well as potentially taking place outside the visibility of the target organization, making detection difficult for defenders.

Detection efforts may be focused on related stages of the adversary lifecycle, such as during Initial Access.

Consider monitoring social media activity related to your organization. Suspicious activity may include personas claiming to work for your organization or recently modified accounts making numerous connection requests to accounts affiliated with your organization. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Initial Access (ex: Spearphishing via Service). Monitor and analyze traffic patterns and packet inspection associated to protocol(s), leveraging SSL/TLS inspection for encrypted traffic, that do not follow the expected protocol standards and traffic flows (e.g extraneous packets that do not belong to established flows, gratuitous or anomalous traffic patterns, anomalous syntax, or structure). Consider correlation with process monitoring and command line to detect anomalous processes execution and command line arguments associated to traffic patterns (e.g. monitor anomalies in use of files that do not normally initiate connections for respective protocol(s)).

Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Command and Control. Once adversaries have provisioned a server (ex: for use as a command and control server), internet scans may reveal servers that adversaries have acquired. Consider looking for identifiable patterns such as services listening, certificates in use, SSL/TLS negotiation features, or other response artifacts associated with adversary C2 software.[1][2][3]

Consider analyzing malware for features that may be associated with the adversary and/or their developers, such as compiler used, debugging artifacts, or code similarities. Malware repositories can also be used to identify additional samples associated with the adversary and identify development patterns over time. Monitor for contextual data about a malicious payload, such as compilation times, file hashes, as well as watermarks or other identifiable configuration information. Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on post-compromise phases of the adversary lifecycle.

Monitor and analyze traffic patterns and packet inspection associated to protocol(s) that do not follow the expected protocol standards and traffic flows (e.g extraneous packets that do not belong to established flows, gratuitous or anomalous traffic patterns, anomalous syntax, or structure). Consider correlation with process monitoring and command line to detect anomalous processes execution and command line arguments associated to traffic patterns (e.g. monitor anomalies in use of files that do not normally initiate connections for respective protocol(s)). Consider monitoring social media activity related to your organization. Suspicious activity may include personas claiming to work for your organization or recently created/modified accounts making numerous connection requests to accounts affiliated with your organization. Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Initial Access (ex: Phishing).

Once adversaries have provisioned software on a compromised server (ex: for use as a command and control server), internet scans may reveal servers that adversaries have compromised. Consider looking for identifiable patterns such as services listening, certificates in use, SSL/TLS negotiation features, or other response artifacts associated with adversary C2 software.[1][2][3] Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Command and Control.

Consider analyzing code signing certificates for features that may be associated with the adversary and/or their developers, such as the thumbprint, algorithm used, validity period, common name, and certificate authority. Malware repositories can also be used to identify additional samples associated with the adversary and identify patterns an adversary has used in procuring code signing certificates. Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related follow-on behavior, such as Code Signing or Install Root Certificate.

Consider monitoring social media activity related to your organization. Suspicious activity may include personas claiming to work for your organization or recently modified accounts making numerous connection requests to accounts affiliated with your organization. Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Initial Access (ex: Phishing). Monitor and analyze traffic patterns and packet inspection associated to protocol(s) that do not follow the expected protocol standards and traffic flows (e.g extraneous packets that do not belong to established flows, gratuitous or anomalous traffic patterns, anomalous syntax, or structure). Consider correlation with process monitoring and command line to detect anomalous processes execution and command line arguments associated to traffic patterns (e.g. monitor anomalies in use of files that do not normally initiate connections for respective protocol(s)).

Much of this activity may have a very high occurrence and associated false positive rate, as well as potentially taking place outside the visibility of the target organization, making detection difficult for defenders.

Detection efforts may be focused on related stages of the adversary lifecycle, such as during Initial Access.

Monitor for suspicious email activity, such as numerous accounts receiving messages from a single unusual/unknown sender. Filtering based on DKIM+SPF or header analysis can help detect when the email sender is spoofed.[1][2] Monitor for references to uncategorized or known-bad sites. URL inspection within email (including expanding shortened links and identifying obfuscated URLs) can also help detect links leading to known malicious sites.[3]

Furthermore, monitor browser logs for homographs in ASCII and in internationalized domain names abusing different character sets (e.g. Cyrillic vs Latin versions of trusted sites). Monitor network data for uncommon data flows. Processes utilizing the network that do not normally have network communication or have never been seen before are suspicious. Monitor and analyze traffic patterns and packet inspection associated to protocol(s), leveraging SSL/TLS inspection for encrypted traffic, that do not follow the expected protocol standards and traffic flows (e.g extraneous packets that do not belong to established flows, gratuitous or anomalous traffic patterns, anomalous syntax, or structure). Consider correlation with process monitoring and command line to detect anomalous processes execution and command line arguments associated to traffic patterns (e.g. monitor anomalies in use of files that do not normally initiate connections for respective protocol(s)).

Furthermore, monitor network traffic for homographs via the use of internationalized domain names abusing different character sets (e.g. Cyrillic vs Latin versions of trusted sites). Also monitor and analyze traffic patterns and packet inspection for indicators of cloned websites. For example, if adversaries use HTTrack to clone websites, Mirrored from (victim URL) may be visible in the HTML section of packets.

Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during exfiltration (ex: Transfer Data to Cloud Account).

Much of this activity may have a very high occurrence and associated false positive rate, as well as potentially taking place outside the visibility of the target organization, making detection difficult for defenders.

Detection efforts may be focused on related stages of the adversary lifecycle, such as during Initial Access.

If infrastructure or patterns in the malicious web content related to SEO poisoning or Drive-by Target have been previously identified, internet scanning may uncover when an adversary has staged web content supporting a strategic web compromise. Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on other phases of the adversary lifecycle, such as Drive-by Compromise or Exploitation for Client Execution.

Once adversaries leverage the abused web service as infrastructure (ex: for command and control), it may be possible to look for unique characteristics associated with adversary software, if known.[1] Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Command and Control Web Service or Exfiltration Over Web Service .

Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Phishing, Endpoint Denial of Service, or Network Denial of Service.

Much of this takes place outside the visibility of the target organization, making detection difficult for defenders.

Detection efforts may be focused on related stages of the adversary lifecycle, such as during Initial Access.

Once adversaries have provisioned compromised infrastructure (ex: a server for use in command and control), internet scans may help proactively discover compromised infrastructure. Consider looking for identifiable patterns such as services listening, certificates in use, SSL/TLS negotiation features, or other response artifacts associated with adversary C2 software.[1][2][3] Consider monitoring for anomalous changes to domain registrant information and/or domain resolution information that may indicate the compromise of a domain. Efforts may need to be tailored to specific domains of interest as benign registration and resolution changes are a common occurrence on the internet. Monitor for queried domain name system (DNS) registry data that may compromise third-party infrastructure that can be used during targeting. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Command and Control. Monitor for logged domain name system (DNS) data that may compromise third-party infrastructure that can be used during targeting. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Command and Control. Monitor for contextual data about an Internet-facing resource gathered from a scan, such as running services or ports that may compromise third-party infrastructure that can be used during targeting. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Command and Control.

Monitor call logs from corporate devices to identify patterns of potential voice phishing, such as calls to/from known malicious phone numbers.

Internet scanners may be used to look for patterns associated with malicious content designed to collect host hardware information from visitors.[1][2] Much of this activity may have a very high occurrence and associated false positive rate, as well as potentially taking place outside the visibility of the target organization, making detection difficult for defenders. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Initial Access.

Internet scanners may be used to look for patterns associated with malicious content designed to collect host software information from visitors.[1][2] Much of this activity may have a very high occurrence and associated false positive rate, as well as potentially taking place outside the visibility of the target organization, making detection difficult for defenders. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Initial Access.