Detections

If infrastructure or patterns in malware, tooling, certificates, or malicious web content have been previously identified, internet scanning may uncover when an adversary has staged their capabilities. 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 initial access and post-compromise behaviors.

Consider use of services that may aid in the tracking of certificates in use on sites across the Internet. In some cases it may be possible to pivot on known pieces of certificate information to uncover other adversary infrastructure.[1] Detection efforts may be focused on related behaviors, such as Web Protocols or Asymmetric Cryptography.

Monitor for suspicious network traffic that could be indicative of probing for user information, such as large/iterative quantities of authentication requests originating from a single source (especially if the source is known to be associated with an adversary/botnet). Analyzing web metadata may also reveal artifacts that can be attributed to potentially malicious activity, such as referer or user-agent string HTTP/S fields.

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 behaviors relating to the potential use of generative artificial intelligence (i.e. Phishing, Phishing for Information).

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 use of services that may aid in the tracking of certificates in use on sites across the Internet. In some cases it may be possible to pivot on known pieces of certificate information to uncover other adversary infrastructure.[1] Detection efforts may be focused on related behaviors, such as Web Protocols , Asymmetric Cryptography , and/or Install Root Certificate .

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. Consider analyzing malware for features that may be associated with malware providers, such as compiler used, debugging artifacts, code similarities, or even group identifiers associated with specific MaaS offerings. Malware repositories can also be used to identify additional samples associated with the developers and the adversary utilizing their services. Identifying overlaps in malware use by different adversaries may indicate malware was obtained by the adversary rather than developed by them. In some cases, identifying overlapping characteristics in malware used by different adversaries may point to a shared quartermaster.[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 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.

Consider use of services that may aid in the tracking of newly issued certificates and/or certificates in use on sites across the Internet. In some cases it may be possible to pivot on known pieces of certificate information to uncover other adversary infrastructure.[1] Some server-side components of adversary tools may have default values set for SSL/TLS certificates.[2] Monitor for logged network traffic in response to a scan showing both protocol header and body values that may buy and/or steal SSL/TLS certificates that can be used during targeting. Detection efforts may be focused on related behaviors, such as Web Protocols, Asymmetric Cryptography, and/or Install Root Certificate.

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 use of services that may aid in the tracking of newly issued certificates and/or certificates in use on sites across the Internet. In some cases it may be possible to pivot on known pieces of certificate information to uncover other adversary infrastructure.[1] Some server-side components of adversary tools may have default values set for SSL/TLS certificates.[2] 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 Defense Evasion or Command and Control. 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 related stages of the adversary lifecycle, such as during Defense Evasion or Command and Control. Monitor for logged network traffic in response to a scan showing both protocol header and body values that may buy and/or steal capabilities that can be used during targeting. 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 Defense Evasion or Command and Control. Consider analyzing malware for features that may be associated with malware providers, such as compiler used, debugging artifacts, code similarities, or even group identifiers associated with specific Malware-as-a-Service (MaaS) offerings. Malware repositories can also be used to identify additional samples associated with the developers and the adversary utilizing their services. Identifying overlaps in malware use by different adversaries may indicate malware was obtained by the adversary rather than developed by them. In some cases, identifying overlapping characteristics in malware used by different adversaries may point to a shared quartermaster.[3] Malware repositories can also be used to identify features of tool use associated with an adversary, such as watermarks in Cobalt Strike payloads.[4]

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. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Initial Access (ex: Spearphishing via Service).

Monitor for contextual data about a malicious payload, such as compilation times, file hashes, as well as watermarks or other identifiable configuration information. In some cases, malware repositories can also be used to identify features of tool use associated with an adversary, such as watermarks in Cobalt Strike payloads.[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 post-compromise phases of the adversary lifecycle.

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. 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 Defense Evasion or Command and Control. 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 related stages of the adversary lifecycle, such as during Defense Evasion or Command and Control. Consider use of services that may aid in the tracking of capabilities, such as certificates, in use on sites across the Internet. In some cases it may be possible to pivot on known pieces of information to uncover other adversary infrastructure.[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 Defense Evasion or Command and Control.

Once adversaries have provisioned software on a compromised VPS (ex: for use as a command and control server), internet scans may reveal VPSs 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.

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.

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.

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.

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.

Once adversaries leverage compromised network devices 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.

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.

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).

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.

Monitor for logged domain name system (DNS) registry data that may hijack domains and/or subdomains that can be used during targeting. In some cases, abnormal subdomain IP addresses (such as those originating in a different country from the root domain) may indicate a malicious subdomain.[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. 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 hijack domains and/or subdomains that can be used during targeting. In some cases, abnormal subdomain IP addresses (such as those originating in a different country from the root domain) may indicate a malicious subdomain.[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.