Fireeye, Inc.

Fireeye Security Holdings US LLC

Phung-Te Ha

Osman Abdoul Ismael

Sai Omkar Vashisht

Sushant Paithane

Dawn Song

Hui Xue

Peter J Gilbert

Wei Xu

Sumer Deshpande

Min Li

Jonas Pfoh

Alex Pilipenko

Seva Tonkonoh

Durvesh Ashok Raut

According to one embodiment of the disclosure, a method for reassigning execution of certain instructions directed to a speculative execution task or a reserved instruction, attempted by a guess process, to be handled by a host process is described herein. The method involves detecting whether a software component, operating within a virtual machine deployed within a guest environment of the network device, is attempting to execute an instruction associated with a speculative execution task. If so, the speculative execution task is prevented from being performed by the software component without the virtual machine detecting that speculative execution by the software component has been reassigned.

System and method for mitigating cyberattacks against processor operability by a guest process

According to one embodiment, a computerized method features monitoring behaviors of an object during processing within a guest system of a virtual machine. Within a guest system, a rule-based analysis of data associated with the monitored behaviors is conducted. The rule-based analysis includes prioritizing data associated with the monitored behaviors that correspond to an exception, and thereafter, storing the data associated with the monitored behaviors that correspond to the exception into a prescribed area of a virtual image file. The prescribed area is accessible by (i) logic within the guest system and (ii) logic within a host system of the virtual machine.

Data extraction system for malware analysis

A computerized method that assists in preventing malware from evading detection through analysis of the virtual hardware components operating within a malware detection system is described. First, a virtual machine (VM) is provisioned in accordance with a guest image, which includes a guest operating system and one or more virtual hardware component. The virtual hardware component including an identifier, and the guest operating system includes a software driver that controls access to the virtual hardware component and features the identifier of the virtual hardware component. Responsive to processing an object within the VM and issuance of a request for an identifier of a hardware component, the identifier of the first virtualized hardware component (virtualization of the hardware component) is received. The first identifier of the first virtual hardware component being an identifier substituted for a prior identifier of the first virtual hardware component before creation of the guest image.

System and method for preventing malware evasion

A method for detecting a ROP attack comprising processing of an object within a virtual machine managed by a virtual machine monitor (VMM), intercepting an attempted execution by the object of an instruction, the instruction stored on a page in memory that is accessed by the virtual machine, responsive to determining the page includes instructions corresponding to one of a predefined set of function calls, (i) inserting a first transition event into the memory at a starting address location of a function call, and (ii) setting a permission of the page to be execute only, and responsive to triggering the first transition event, halting, by the VMM, the processing of the object and analyzing, by logic within the VMM, content of last branch records associated with the virtual machine to determine whether the processing of the object displays characteristics of a ROP attack is shown.

Method to detect forgery and exploits using last branch recording registers

A method for updating a virtual machine disk snapshot for use in instantiating one or more virtual guest instances for malware detection is described. The method features (i) detecting a guest image update package that includes information for updating one or more software components included as part of the virtual machine disk snapshot, and (ii) determining whether the guest image update package is currently contained in a contiguous storage area that is part of the virtual machine disk snapshot. Responsive to determining that the guest image update package is more recent than content currently contained in the contiguous storage area, the guest image update package is inserted into the contiguous storage area that is part of the virtual machine disk snapshot to generate a revised virtual machine disk snapshot that includes the one or more updated software components.

Adaptive virtual machine snapshot update framework for malware behavioral analysis

A method for hiding transition events during malware detection comprising processing of an object within a VM, intercepting an attempted execution of an instruction located on a page in memory associated with the VM, responsive to determining the page includes instructions corresponding to one of a predefined set of function calls, (i) inserting a first transition event into the memory at a location on the page of a first instruction of the instructions, and (ii) setting a permission of the page to be execute only, and responsive to further processing within the VM causing an attempt to read from or write to the page including the first transition event, (i) halting processing within the VM, (ii) removing the first transition event, (iii) setting the permission of the page to prohibit execution, and (iv) resuming the processing is shown.

Methods and system for hiding transition events for malware detection

A non-transitory storage medium including instructions that are executable by one or more processors to perform operations including instrumenting a VM is shown. The VM is used to process an object to determine whether the object is associated with malware. Logic within the VM analyzes memory allocated for a process within the VM for a point of interest (POI), the POI being an address of one of a set predetermined instructions likely to be associated with malware. The VMM detects a memory violation during processing of the object and responsive to detecting the memory violation, injects a transition event at the POI on the page on which the POI is located in memory. Further, responsive to detecting an attempted execution of the transition event, the VMM (i) emulates an instruction located at the POI, and (ii) the logic within the VM performs one or more malware detection routines.

System and methods for advanced malware detection through placement of transition events

Techniques for malicious content detection using code injection are described herein. In one embodiment a first code section of a target program is loaded into a first memory page of a virtual machine (VM) hosted by a virtual machine monitor (VMM). The target program to receive code injection. The VMM injects a second code section into the target program by replacing the first code section with a second code section loaded in a second memory page. Determining a behavior of a content specimen using the injected second code section instead of the first code section, and the second code section is injected after the target program.

Page replacement code injection

According to one embodiment of the invention, a computerized method is described for improved efficiency in malware detection. The method comprises detecting a system call initiated by a virtual machine and determining a class assigned to the detected system call. In response to determining that the system call is associated with a first class of system calls, providing information associated with the system call to virtualized device hardware. In contrast, in response to determining that the system call is associated with a second class of system calls, which is different from the first class of system calls, the virtual machine resumes virtual processing of an object without providing information to the virtualized device hardware.

Selective system call monitoring

For one embodiment, a method is described that involves the instrumenting of an application of a computing system with at least one monitoring function, where the monitoring function is capable of operating in a run-time environment during processing of the instrumented application. The movement of data associated with the application is tracked by one or more monitoring functions. This data is at least partially identified by a storage location. Thereafter, a determination is made whether movement of the data from a first storage location to a second storage location is suspicious, and if so, suspicious movement of the data is reported.

Framework for efficient security coverage of mobile software applications using machine learning

A method is described that involves generating one or more machine learned rules with a machine learning system. The method also involves generating a representation of an application that describes various states and state transitions of the application. The method also involves referring to the one or more machine learned rules and the representation to identify a region of interest of the application. The method also involves configuring one or more monitors for the application to be enabled in a run time environment of the application. The method also involves setting conditions of the application within the run time environment to drive the application's execution to the region of interest. The method also involves observing behaviors of the application and determining whether the region of interest corresponds to improperly behaving code.

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Dublin, CA, United States of America

Phung-Te Ha