Abstract:
A malicious object detection system for use in managed runtime environments includes a check circuit to receive call information generated by an application, such as an Android application. A machine learning circuit coupled to the check circuit applies a machine learning model to assess the information and/or data included in the call and detect the presence of a malicious object, such as malware or a virus, in the application generating the call. The machine learning model may include a global machine learning model distributed across a number of devices, a local machine learning model based on use patterns of a particular device, or combinations thereof. A graphical user interface management circuit halts execution of applications containing malicious objects and generates a user perceptible output.
Abstract:
In one embodiment, a processor comprises: a first register to store a first bound value for a stack to be stored in a memory; a second register to store a second bound value for the stack; a checker logic to determine, prior to an exit point at a conclusion of a function to be executed on the processor, whether a value of a stack pointer is within a range between the first bound value and the second bound value; and a logic to prevent a return to a caller of the function if the stack pointer value is not within the range. Other embodiments are described and claimed.
Abstract:
Technologies for untrusted code execution include a computing device having a processor with sandbox support. The computing device executes code included in a native domain in a non-privileged, native processor mode. The computing device may invoke a sandbox jump processor instruction during execution of the code in the native domain to enter a sandbox domain. The computing device executes code in the sandbox domain in a non-privileged, sandbox processor mode in response to invoking the sandbox jump instruction. While executing in the sandbox processor mode, the processor denies access to memory outside of the sandbox domain and may deny execution of one or more prohibited instructions. From the sandbox domain, the computing device may execute a sandbox exit instruction to exit the sandbox domain and resume execution in the native domain. The computing device may execute processor instructions to configure the sandbox domain. Other embodiments are described and claimed.
Abstract:
In one embodiment, a system comprises a processor to, in response to a determination that a write command is suspect, identify a logical address associated with the write command; and send a checkpoint command identifying the logical address to a storage device to preserve data stored in the storage device at a physical address associated with the logical address.
Abstract:
A device and method for securely rendering content on a gesture-enabled computing device includes initializing a secure execution environment on a processor graphics of the computing device. The computing device transfers view rendering code and associated state data to the secure execution environment. An initial view of the content is rendered by executing the view rendering code in the secure execution environment. A gesture is recognized, and an updated view of the content is rendered in the secure execution environment in response to the gesture. The gesture may include a touch gesture recognized on a touch screen, or a physical gesture of the user recognized by a camera. After the updated view of the content is rendered, the main processor of the computing device may receive updated view data from the secure execution environment.
Abstract:
Technologies for untrusted code execution include a computing device having a processor with sandbox support. The computing device executes code included in a native domain in a non-privileged, native processor mode. The computing device may invoke a sandbox jump processor instruction during execution of the code in the native domain to enter a sandbox domain. The computing device executes code in the sandbox domain in a non-privileged, sandbox processor mode in response to invoking the sandbox jump instruction. While executing in the sandbox processor mode, the processor denies access to memory outside of the sandbox domain and may deny execution of one or more prohibited instructions. From the sandbox domain, the computing device may execute a sandbox exit instruction to exit the sandbox domain and resume execution in the native domain. The computing device may execute processor instructions to configure the sandbox domain. Other embodiments are described and claimed.
Abstract:
Technologies for untrusted code execution include a computing device having a processor with sandbox support. The computing device executes code included in a native domain in a non-privileged, native processor mode. The computing device may invoke a sandbox jump processor instruction during execution of the code in the native domain to enter a sandbox domain. The computing device executes code in the sandbox domain in a non-privileged, sandbox processor mode in response to invoking the sandbox jump instruction. While executing in the sandbox processor mode, the processor denies access to memory outside of the sandbox domain and may deny execution of one or more prohibited instructions. From the sandbox domain, the computing device may execute a sandbox exit instruction to exit the sandbox domain and resume execution in the native domain. The computing device may execute processor instructions to configure the sandbox domain. Other embodiments are described and claimed.
Abstract:
A processor includes an execution unit and a processing logic operatively coupled to the execution unit, the processing logic to: enter a first execution state and transition to a second execution state responsive to executing a control transfer instruction. Responsive to executing a target instruction of the control transfer instruction, the processing logic further transitions to the first execution state responsive to the target instruction being a control transfer termination instruction of a mode identical to a mode of the processing logic following the execution of the control transfer instruction; and raises an execution exception responsive to the target instruction being a control transfer termination instruction of a mode different than the mode of the processing logic following the execution of the control transfer instruction.
Abstract:
A malicious object detection system for use in managed runtime environments includes a check circuit to receive call information generated by an application, such as an Android application. A machine learning circuit coupled to the check circuit applies a machine learning model to assess the information and/or data included in the call and detect the presence of a malicious object, such as malware or a virus, in the application generating the call. The machine learning model may include a global machine learning model distributed across a number of devices, a local machine learning model based on use patterns of a particular device, or combinations thereof. A graphical user interface management circuit halts execution of applications containing malicious objects and generates a user perceptible output.
Abstract:
In one embodiment, a processor comprises: a first register to store a first bound value for a stack to be stored in a memory; a second register to store a second bound value for the stack; a checker logic to determine, prior to an exit point at a conclusion of a function to be executed on the processor, whether a value of a stack pointer is within a range between the first bound value and the second bound value; and a logic to prevent a return to a caller of the function if the stack pointer value is not within the range. Other embodiments are described and claimed.