Carbon Black, Inc.

Vmware, Inc.

Paul Matthew Drapeau

Jeffrey Albin Kraemer

Kyle P Gwinnup

Brian M Sturk

Improved tools and techniques for generating stateful rules for behavior-based threat detection enable threat analysts, who do not have advanced computer programming skills, to quickly and easily generate high-level representations of stateful behavioral rules, which are then compiled into a format suitable for execution by a stateful rule processing engine. In some examples, the high-level representations of stateful rules are coded in a high-level, domain specific language (DSL). The DSL may provide high-level primitives suitable for (1) expressing sequences of attack behaviors, (2) tagging computational entities (e.g., threads, processes, applications, systems, users, etc.) with states (e.g., user-defined states), and/or (3) performing operations on endpoint nodes (e.g., reporting activity, blocking activity, terminating processes, etc.).

Stateful rule generation for behavior based threat detection

A computing apparatus for protecting software hooks from interference may include a processing device and a memory access monitoring device configured to monitor access to the memory addresses of one or more hooks. When a task T1 attempts to write to a memory address of a monitored hook, the monitoring device may generate a notification (e.g., an interrupt), and the processing device may pause execution of the task T1 and initiate execution of a hook protection task T2. The hook protection task T2 may determine whether to allow task T1 to modify the monitored hook. If task T1 is not a trusted task (e.g., if task T1 is or may be malware), the processing device blocks T1 from modifying the monitored hook. In this manner, some attempts to unhook critical software hooks may be thwarted.

Methods for protecting software hooks, and related computer security systems and apparatus

A method and system for remediating a process hollowing intrusion on a user device comprising detecting a process starting on the user device, preparing the process to monitor Application Programming Interface (API) calls between the process and an operating system of the user device, determining whether the process is associated with a process hollowing intrusion based on information associated with the process and/or the API calls, and executing security policies against the process associated with the process hollowing intrusion. In examples, it is determined whether the child process is associated with a process hollowing intrusion in response to determining whether one or more API calls associated with known process hollowing intrusions modify executable memory of and/or modify an entry point address of the child process.

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Mendon, MA, United States of America

Paul Matthew Drapeau