Abstract: Described systems and methods allow protecting a computer system from computer security threats such as malware and spyware. In some embodiments, a security application executes a set of detection routines to determine whether a set of monitored entities (processes, threads, etc.) executing on the computer system comprise malicious software. The detection routines are formulated in bytecode and executed within a bytecode translation virtual machine. Execution of a detection routine comprises translating bytecode instructions of the respective routine into native processor instructions, for instance via interpretation or just-in-time compilation. Execution of the respective routines is triggered selectively, due to the occurrence of specific events within the protected client system. Detection routines may output a set of scores, which may be further used by the security application to determine whether a monitored entity is malicious.

Abstract: According to one aspect, a dynamic binary instrumentation (DBI) framework is used to identify rootkits and disable their malicious functionality. A user-mode or kernel-mode anti-rootkit (ARK) engine monitors the execution of a program running on a host machine in user more or kernel mode. Upon encountering calls to certain functions that may be used by rootkits to subvert system functionality (e.g. system calls used to manage the system registry, storage/disk, processes/threads, and/or network communications), the anti-rootkit engine executes translated versions of the functions in an isolated environment and continues execution of the program under analysis using the results of the translated code execution. The translated code execution replaces the execution of original code which may or may not have been subverted by a rootkit. Isolating the stack and registers of the isolated environment impedes detection of the monitoring process by rootkits.

Abstract: Described systems and methods enable a host system to efficiently perform computer security activities, when operating in a hardware virtualization configuration. A hypervisor exposes a virtual machine on the host system. In some embodiments, the hypervisor further configures a processor of the host system to generate a virtualization exception in response to detecting a memory access violation, and to deliver such exceptions to a computer security program operating within the virtual machine. The hypervisor may further set access permissions to a section of memory containing a part of a function targeted for hooking, so that an attempt to execute the respective target function triggers a virtualization exception. Some embodiments thus achieve hooking of the target function without resorting to conventional methods, such as patching, inline hooking, and MSR hooking.

Abstract: Described systems and methods allow conducting computer security operations, such as detecting malware and spyware, in a bare-metal computer system. In some embodiments, a first processor of a computer system executes the code samples under assessment, whereas a second, distinct processor is used to carry out the assessment and to control various hardware components involved in the assessment. Such hardware components include, among others, a memory shadower configured to detect changes to a memory connected to the first processor, and a storage shadower configured to detect an attempt to write to a non-volatile storage device of the computer system.

Abstract: Described systems and methods allow protecting a computer system from malware such as viruses, Trojans, and spyware. For each of a plurality of executable entities (such as processes and threads executing on the computer system), a scoring engine records a plurality of evaluation scores, each score determined according to a distinct evaluation criterion. Every time an entity satisfies an evaluation criterion (e.g, performs an action), the respective score of the entity is updated. Updating a score of an entity may trigger score updates of entities related to the respective entity, even when the related entities are terminated, i.e., no longer active. Related entities include, among others, a parent of the respective entity, and/or an entity injecting code into the respective entity. The scoring engine determines whether an entity is malicious according to the plurality of evaluation scores of the respective entity.

Abstract: Described systems and methods allow protecting a client system, such as a computer system or smartphone, from malware. In some embodiments, a network regulator device is used to distribute a bootable image of a hypervisor, on demand, to each of a set of client systems connected to a network. After booting on a client system, the hypervisor loads the local OS and applications into a virtual machine. Integrity measurements of the hypervisor and/or OS are sent to the network regulator for verification. When the network regulator determines that software executing on a client system, such as the hypervisor and/or the OS, are not in a trusted state, the network regulator may block access of the respective client system to the network.

Abstract: Described systems and methods allow protecting a host computer system from malware, such as return-oriented programming (ROP) and jump-oriented programming (JOP) exploits. In some embodiments, a processor of the host system is endowed with two counters configured to store a count of branch instructions and a count of inter-branch instructions, respectively, occurring within a stream of instructions fetched by the processor for execution. Exemplary counted branch instructions include indirect JMP, indirect CALL, and RET on x86 platforms, while inter-branch instructions consist of instructions executed between two consecutive counted branch instructions. The processor may be further configured to generate a processor event, such as an exception, when a value stored in a counter exceeds a predetermined threshold. Such events may be used as triggers for launching a malware analysis to determine whether the host system is subject to a code reuse attack.

Abstract: Described systems and methods allow a mobile device, such as a smartphone or a tablet computer, to protect a user of the respective device from fraud and/or loss of privacy. In some embodiments, the mobile device receives from a server a risk indicator indicative of whether executing a target application causes a privacy risk. Determining the risk indicator includes automatically supplying a test input to a data field used by the target application, the data field configured to hold a private item such as a password or a geolocation indicator. Determining the risk indicator further comprises determining whether a test device executing an instance of the target application transmits an indicator of the test input, such as the test input itself or a hash of the test input, to another party on the network.

Abstract: Described systems and methods allow protecting a host system, such as a computer system or smartphone, from malware such as viruses, exploits, and rootkits. In some embodiments, a hypervisor executes at the highest processor privilege level and displaces other software to a guest virtual machine (VM). A security application detects the launch of a target process within the guest VM. In response to the launch, the hypervisor instantiates a process VM isolated from the guest VM, and relocates the target process to the process VM. In some embodiments, when the relocated target process attempts to access a resource, such as a file or registry key, an instance of the respective resource is fetched on-demand, from the guest VM to the respective process VM. Executing the target process within an isolated environment helps to contain malware to the respective environment.

Abstract: Described systems and methods allow a classification of electronic documents such as email messages and HTML documents, according to a document-specific text fingerprint. The text fingerprint is calculated for a text block of each target document, and comprises a sequence of characters determined according to a plurality of text tokens of the respective text block. In some embodiments, the length of the text fingerprint is forced within a pre-determined range of lengths (e.g. between 129 and 256 characters) irrespective of the length of the text block, by zooming in for short text blocks, and zooming out for long ones. Classification may include, for instance, determining whether an electronic document represents unsolicited communication (spam) or online fraud such as phishing.

Abstract: Described spam detection techniques including string identification, pre-filtering, and frequency spectrum and timestamp comparison steps facilitate accurate, computationally-efficient detection of rapidly-changing spam arriving in short-lasting waves. In some embodiments, a computer system extracts a target character string from an electronic communication such as a blog comment, transmits it to an anti-spam server, and receives an indicator of whether the respective electronic communication is spam or non-spam from the anti-spam server. The anti-spam server determines whether the electronic communication is spam or non-spam according to features of the frequency spectrum of the target string. Some embodiments also perform an unsupervised clustering of incoming target strings into clusters, wherein all members of a cluster have similar spectra.

Abstract: Described systems and methods allow protecting a computer system from malware, such as viruses and rootkits. An anti-malware component executes within a virtual machine (VM) exposed by a hypervisor executing on the computer system. A memory introspection engine executes outside the virtual machine, at the processor privilege level of the hypervisor, and protects a process executing within the virtual machine by write-protecting a memory page of the respective process. By combining anti-malware components executing inside and outside the respective VM, some embodiments of the present invention may use the abundance of behavioral data that inside-VM components have access to, while protecting the integrity of such components from outside the respective VM.

Abstract: In some embodiments, an anti-malware system accounts for benign differences between non-malicious data objects, such as differences introduced by compilers and other polymorphisms. A target object is separated into a multitude of code blocks, and a hash is calculated for each code block. The obtained set of target hashes is then compared against a database of hashes corresponding to code blocks extracted from whitelisted objects. A target object may be labeled as whitelisted (trusted, non-malicious) if it has a substantial number of hashes in common with a whitelisted object. Objects which are slightly different from known whitelisted objects may still receive whitelisting status. By allowing a certain degree of mismatch between the sets of hashes of distinct objects, some embodiments of the present invention increase the efficiency of whitelisting without an unacceptable decrease in safety.

Abstract: Described systems and methods allow protecting a host system, such as a computer or smartphone, from malware. In some embodiments, an anti-malware application installs a hypervisor, which displaces an operating system executing on the host system to a guest virtual machine (VM). The hypervisor further creates a set of virtual containers (VC), by setting up a memory domain for each VC, isolated from the memory domain of the guest VM. The hypervisor then maps a memory image of a malware scanner to each VC. When a target object is selected for scanning, the anti-malware application launches the malware scanner. Upon intercepting the launch, the hypervisor switches the memory context of the malware scanner to the memory domain of a selected VC, for the duration of the scan. Thus, malware scanning is performed within an isolated environment.

Abstract: Described systems and methods allow protecting a computer system from malware, such as viruses, Trojans, and spyware. A reputation manager executes in conjunction with an anti-malware engine. The reputation manager determines a reputation of a target process executing on the computer system according to a reputation of a set of executable modules, such as shared libraries, loaded by the target process. The anti-malware engine may be configured to employ a process-specific protocol to scan the target process for malware, the protocol selected according to process reputation. Processes trusted to be non-malicious may thus be scanned using a more relaxed protocol than unknown or untrusted processes. The reputation of executable modules may be static; an indicator of module reputation may be stored and/or retrieved by a remote reputation server. Process reputation may be dynamically changeable, i.e. re-computed repeatedly by the reputation manager in response to process life-cycle and/or security events.

Abstract: Described spam detection techniques including string identification, pre-filtering, and character histogram and timestamp comparison steps facilitate accurate, computationally-efficient detection of rapidly-changing spam arriving in short-lasting waves. In some embodiments, a computer system extracts a target character string from an electronic communication such as a blog comment, transmits it to an anti-spam server, and receives an indicator of whether the respective electronic communication is spam or non-spam from the anti-spam server. The anti-spam server determines whether the electronic communication is spam or non-spam according to certain features of the character histogram of the target string. Some embodiments also perform an unsupervised clustering of incoming target strings into clusters, wherein all members of a cluster have similar character histograms.

Abstract: Described systems and methods allow a classification of electronic documents such as email messages and HTML documents, according to a document-specific text fingerprint. The text fingerprint is calculated for a text block of each target document, and comprises a sequence of characters determined according to a plurality of text tokens of the respective text block. In some embodiments, the length of the text fingerprint is forced within a pre-determined range of lengths (e.g. between 129 and 256 characters) irrespective of the length of the text block, by zooming in for short text blocks, and zooming out for long ones. Classification may include, for instance, determining whether an electronic document represents unsolicited communication (spam) or online fraud such as phishing.

Abstract: Described systems and methods allow the detection and prevention of malware and/or malicious activity within a network comprising multiple client computer systems, such as an enterprise network with multiple endpoints. Each endpoint operates a hardware virtualization platform, including a hypervisor exposing a client virtual machine (VM) and a security VM. The security VM is configured to have exclusive use of the network adapter(s) of the respective endpoint, and to detect whether data traffic to/from the client VM comprises malware or is indicative of malicious behavior. Upon detecting malware/malicious behavior, the security VM may block access of the client VM to the network, thus preventing the spread of malware to other endpoints. The client system may further comprise a memory introspection engine configured to perform malware scanning of the client VM from the level of the hypervisor.