Cobalt strike beacon https C2 heuristic detection
Techniques for Cobalt Strike Beacon HTTPS C2 heuristic detection are disclosed. In some embodiments, a system/process/computer program product for Cobalt Strike Beacon HTTPS C2 heuristic detection includes monitoring HyperText Transfer Protocol Secure (HTTPS) network traffic at a firewall; prefiltering the monitored HTTPS network traffic at the firewall to select a subset of the HTTPS network traffic to forward to a cloud security service; determining whether the subset of the HTTPS network traffic is associated with Cobalt Strike Beacon HTTPS C2 traffic activity based on a plurality of heuristics; and performing an action in response to detecting the Cobalt Strike Beacon HTTPS C2 traffic activity.
1 . A system, comprising:
a processor configured to:
monitor HyperText Transfer Protocol Secure (HTTPS) network traffic at a firewall;
prefilter the monitored HTTPS network traffic at the firewall to select a subset of the HTTPS network traffic to forward to a cloud security service;
determine that the subset of the HTTPS network traffic is associated with Cobalt Strike Beacon HTTPS C2 traffic activity based on a plurality of heuristics, comprising to:
determine that a plurality of session timestamps associated with the subset of the HTTPS network traffic has a Gaussian distribution or a normal distribution, wherein the subset of the HTTPS network traffic includes a plurality of sessions, wherein the plurality of sessions includes a first session and a second session; and
in response to a determination that the plurality of session timestamps has the Gaussian distribution or the normal distribution:
determine that a timestamp gap between the first session and the second session is less than or equal to a predefined period of time; and
in response to a determination that the timestamp gap is less than or equal to the predefined period of time:
determine that a first hash value of a first header of the first session matches a second hash value of a second header of the second session; and
in response to a determination that the first hash value matches the second hash value:
determine that a number of fields in the first header is less than or equal to a predetermined threshold number of fields; and
in response to a determination that the number of fields in the first header is less than or equal to the predetermined threshold number of fields, determine that the subset of the HTTPS network traffic is associated with the Cobalt Strike Beacon HTTPS C2 traffic activity;
and
perform an action in response to detecting the Cobalt Strike Beacon HTTPS C2 traffic activity; and
a memory coupled to the processor and configured to provide the processor with instructions.
2 . The system of claim 1 , wherein a fast match table of a detection system stores previously detected Cobalt Strike Beacon HTTPS C2 traffic activity.
3 . The system of claim 1 , wherein a fast match table of a detection system stores a 3-tuple of previously detected Cobalt Strike Beacon HTTPS C2 traffic activity, wherein the 3-tuple includes a source IP address, a destination IP address, and a destination port.
4 . The system of claim 1 , wherein data statistics based on an automated heuristic analysis of the subset of the HTTPS network traffic is stored in a data statistics table of a detection system.
5 . The system of claim 1 , wherein the processor is further configured to perform a validation of the detected Cobalt Strike Beacon HTTPS C2 traffic activity.
6 . The system of claim 1 , wherein the processor is further configured to perform a validation of the detected Cobalt Strike Beacon HTTPS C2 traffic activity based on probing of a destination IP address associated with the detected Cobalt Strike Beacon HTTPS C2 traffic activity.
7 . The system of claim 1 , wherein the processor is further configured to perform a validation of the detected Cobalt Strike Beacon HTTPS C2 traffic activity based on probing of a destination IP address associated with the detected Cobalt Strike Beacon HTTPS C2 traffic activity and using a fingerprint data store.
8 . A method, comprising:
monitoring HyperText Transfer Protocol Secure (HTTPS) network traffic at a firewall;
prefiltering the monitored HTTPS network traffic at the firewall to select a subset of the HTTPS network traffic to forward to a cloud security service;
determining that the subset of the HTTPS network traffic is associated with Cobalt Strike Beacon HTTPS C2 traffic activity based on a plurality of heuristics, comprising:
determining that a plurality of session timestamps associated with the subset of the HTTPS network traffic has a Gaussian distribution or a normal distribution, wherein the subset of the HTTPS network traffic includes a plurality of sessions, wherein the plurality of sessions includes a first session and a second session; and
in response to a determination that the plurality of session timestamps has the Gaussian distribution or the normal distribution:
determining that a timestamp gap between the first session and the second session is less than or equal to a predefined period of time; and
in response to a determination that the timestamp gap is less than or equal to the predefined period of time:
determining that a first hash value of a first header of the first session matches a second hash value of a second header of the second session; and
in response to a determination that the first hash value matches the second hash value:
determining that a number of fields in the first header is less than or equal to a predetermined threshold number of fields; and
in response to a determination that the number of fields in the first header is less than or equal to the predetermined threshold number of fields, determining that the subset of the HTTPS network traffic is associated with the Cobalt Strike Beacon HTTPS C2 traffic activity;
and
performing an action in response to detecting the Cobalt Strike Beacon HTTPS C2 traffic activity.
9 . The method of claim 8 , wherein a fast match table of a detection system stores previously detected Cobalt Strike Beacon HTTPS C2 traffic activity.
10 . The method of claim 8 , wherein a fast match table of a detection system stores a 3-tuple of previously detected Cobalt Strike Beacon HTTPS C2 traffic activity, wherein the 3-tuple includes a source IP address, a destination IP address, and a destination port.
11 . The method of claim 8 , wherein data statistics based on an automated heuristic analysis of the subset of the HTTPS network traffic is stored in a data statistics table of a detection system.
12 . The method of claim 8 , further comprising performing a validation of the detected Cobalt Strike Beacon HTTPS C2 traffic activity.
13 . The method of claim 8 , further comprising performing a validation of the detected Cobalt Strike Beacon HTTPS C2 traffic activity based on probing of a destination IP address associated with the detected Cobalt Strike Beacon HTTPS C2 traffic activity.
14 . The method of claim 8 , further comprising performing a validation of the detected Cobalt Strike Beacon HTTPS C2 traffic activity based on probing of a destination IP address associated with the detected Cobalt Strike Beacon HTTPS C2 traffic activity and using a fingerprint data store.
15 . A computer program product embodied in a non-transitory computer readable medium and comprising computer instructions for:
monitoring HyperText Transfer Protocol Secure (HTTPS) network traffic at a firewall;
prefiltering the monitored HTTPS network traffic at the firewall to select a subset of the HTTPS network traffic to forward to a cloud security service;
determining that the subset of the HTTPS network traffic is associated with Cobalt Strike Beacon HTTPS C2 traffic activity based on a plurality of heuristics, comprising:
determining that a plurality of session timestamps associated with the subset of the HTTPS network traffic has a Gaussian distribution or a normal distribution, wherein the subset of the HTTPS network traffic includes a plurality of sessions, wherein the plurality of sessions includes a first session and a second session; and
in response to a determination that the plurality of session timestamps has the Gaussian distribution or the normal distribution:
determining that a timestamp gap between the first session and the second session is less than or equal to a predefined period of time; and
in response to a determination that the timestamp gap is less than or equal to the predefined period of time:
determining that a first hash value of a first header of the first session matches a second hash value of a second header of the second session; and
in response to a determination that the first hash value matches the second hash value:
determining that a number of fields in the first header is less than or equal to a predetermined threshold number of fields; and
in response to a determination that the number of fields in the first header is less than or equal to the predetermined threshold number of fields, determining that the subset of the HTTPS network traffic is associated with the Cobalt Strike Beacon HTTPS C2 traffic activity;
and
performing an action in response to detecting the Cobalt Strike Beacon HTTPS C2 traffic activity.
16 . The computer program product of claim 15 , wherein a fast match table of a detection system stores previously detected Cobalt Strike Beacon HTTPS C2 traffic activity.
17 . The computer program product of claim 15 , wherein a fast match table of a detection system stores a 3-tuple of previously detected Cobalt Strike Beacon HTTPS C2 traffic activity, wherein the 3-tuple includes a source IP address, a destination IP address, and a destination port.
18 . The computer program product of claim 15 , further comprising computer instructions for performing a validation of the detected Cobalt Strike Beacon HTTPS C2 traffic activity.
19 . The computer program product of claim 15 , further comprising computer instructions for performing a validation of the detected Cobalt Strike Beacon HTTPS C2 traffic activity based on probing of a destination IP address associated with the detected Cobalt Strike Beacon HTTPS C2 traffic activity.
20 . The computer program product of claim 15 , further comprising computer instructions for performing a validation of the detected Cobalt Strike Beacon HTTPS C2 traffic activity based on probing of a destination IP address associated with the detected Cobalt Strike Beacon HTTPS C2 traffic activity and using a fingerprint data store.