Systems and methods for library function identification in automatic malware signature generation

A computer-implemented method for facilitating automatic malware signature generation may comprise disassembling a malware program, identifying one or more byte sequences within the disassembled malware program that have a likelihood of being representative of one or more library functions contained within the malware program, and preventing the one or more byte sequences from being included within one or more malware signatures. Corresponding systems and computer-readable storage media are also disclosed.

BACKGROUND

Consumers and businesses increasingly rely on computers to store sensitive data. Consequently, malicious programmers seem to continually increase their efforts to gain illegitimate control and access to others' computers. Computer programmers with malicious motivations have created and have continued to create viruses, Trojan horses, worms, and other programs meant to compromise computer systems and data belonging to other people. These malicious programs are often referred to as malware.

Security software companies are combating the growing tide of malware by creating and deploying malware signatures (e.g., sequences of bytes that identify malware) to their customers on a regular basis. By frequently updating malware signatures, security software companies may help their customers secure their computers against new and changing threats.

Given the rapidly increasing number of malicious programs that are being developed, there exists a strong motivation for developing techniques to automate malware signature generation. A technical challenge associated with automatic malware signature generation is ensuring that the malware signatures do not result in false positives when used to identify or detect malware. In other words, it is desirable to minimize the number of goodware programs that are incorrectly identified as malware using automatically generated malware signatures.

SUMMARY

As will be described in greater detail below, the instant disclosure generally relates to systems and methods for facilitating automatic malware signature generation by identifying byte sequences within a malware program that have a likelihood of being representative of library functions. Library functions are often used by both malware and goodware. Hence, the systems and methods described herein may prevent the identified byte sequences from being included within one or more automatically generated malware signatures. In this manner, the number of goodware programs that are incorrectly identified as malware using the automatically generated malware signatures is minimized.

In some embodiments, a computer-implemented method for facilitating automatic malware signature generation may comprise: 1) disassembling a malware program, 2) identifying one or more byte sequences within the disassembled malware program that have a likelihood of being representative of one or more library functions contained within the malware program, and 3) preventing the one or more byte sequences from being included within one or more malware signatures.

In some embodiments, a byte sequence may be identified as having a likelihood of being representative of a library function if the byte sequence matches a library signature corresponding to a library function associated with at least one compiler, is associated with a function called by a known library function, is located within a predetermined distance from an address space corresponding to at least one known library function, and/or accesses at least one global variable associated with the malware program.

By proceeding in this manner, the exemplary systems and methods described herein may reduce the number of library functions used to generate malware signatures, and thereby minimize the number of goodware programs incorrectly identified as comprising malware.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

As will be described in greater detail below, the instant disclosure generally relates to systems and methods for facilitating automatic malware signature generation. As used herein, the term “malware signature” refers to a sequence of bytes used to identify malware.

The systems and methods described herein facilitate automatic signature generation by identifying byte sequences within a malware program that have a likelihood of being representative of library functions. The identified byte sequences may then be prevented from being included within one or more automatically generated malware signatures. In this manner, as will be described in more detail below, the systems and methods described herein may minimize the number of goodware programs (e.g., programs and/or files that do not comprise malware) that are incorrectly identified as malware using automatically generated malware signatures.

The terms “byte sequence within a malware program” and “byte sequence within a disassembled malware program” will be used interchangeably herein to refer to a byte sequence contained within a malware program in a disassembled state. A byte sequence within a malware program may be identified as having a “likelihood” of being representative of a library function if it is determined that the byte sequence is associated with a known library function, matches a library signature associated with a known library function, is associated with a function called by a known library function, and/or accesses a global variable associated with the malware program.

References made herein to “marking” a byte sequence as being associated with a library function refer to a particular manner in which a byte sequence may be identified as having a likelihood of being representative of a library function. It will be recognized that in some instances, a byte sequence identified as having a likelihood of being representative of a library function may in actuality not be representative of a library function. This is acceptable in light of the desire to prevent any byte sequence that may potentially be associated with a library function from being used as a malware signature.

FIG. 1illustrates an exemplary system100for identifying malware. As shown inFIG. 1, system100may include a client device102and a security computing subsystem104configured to communicate with one another. As will be described in more detail below, security computing subsystem104may be configured to automatically generate malware signatures. The malware signatures may be utilized by security computing subsystem104and/or client device102to identify or detect malware residing on client device102.

Client device102generally represents any type or form of computing device capable of reading computer-executable instructions. Examples of client device102include, without limitation, laptops, desktops, servers, cellular phones, personal digital assistants (PDAs), multimedia players, embedded systems, combinations of one or more of the same, exemplary computing system710inFIG. 7, or any other suitable computing device.

Security computing subsystem104generally represents any combination of hardware, software, and/or firmware configured to provide one or more data security features to client device102. Such data security features may include, but are not limited to, automatic malware signature generation, identification and removal of malware residing on client device102, and/or any other data security feature as may serve a particular application.

Client device102and security computing subsystem104may each include one or modules configured to perform one or more of the tasks described herein. In certain embodiments, one or more of the modules described herein may represent one or more software applications or programs that, when executed by a computing device, may cause the computing device to perform one or more tasks. For example, as will be described in greater detail below, one or more of the modules described herein may represent software modules stored and configured to run on one or more computing devices or subsystems, such as client device102, security computing subsystem104, computing system710inFIG. 7, and/or portions of exemplary network architecture800inFIG. 8. One or more of the modules described herein may also represent all or portions of one or more special-purpose computers configured to perform one or more tasks.

Client device102and security computing subsystem104may communicate using any communication platforms and technologies suitable for transporting data, including known communication technologies, devices, media, and protocols supportive of remote or local data communications. For example, as will be described in connection withFIG. 2, client device102and security computing subsystem104may communicate using a network. Additionally or alternatively, a computer-readable storage medium (e.g., an optical disc, flash drive, etc.) may be used to transport data from security computing subsystem104to client device102.

FIG. 2shows an exemplary implementation200of system100wherein client device102and security computing subsystem104are communicatively coupled via a network202. Network202generally represents any medium or architecture capable of facilitating communication or data transfer. Examples of network202include, without limitation, an intranet, a wide area network (WAN), a local area network (LAN), a personal area network (PAN), the Internet, power line communications (PLC), a cellular network (e.g., GSN network), exemplary network architecture900inFIG. 9, or the like. Network202may facilitate communication or data transfer using wireless or wired connections. In one embodiment, network202may facilitate communication between client device102and security computing subsystem104.

As shown inFIG. 2, client device102may include a local security module204and a local storage206. Local storage206generally represents any type or form of storage device, such as the storage devices illustrated and described in connection withFIGS. 7 and 8. Local storage206may be configured to store one or more files (e.g., files208-1through208-N, collectively referred to herein as “files208”) and malware security data210. Files208may include any type of file, such as, but not limited to, data files and executable files. In some instances, one or more of files208may undesirably comprise malware. Malware security data210may include any data used to identify and/or treat files comprising or otherwise associated with malware. For example, malware security data210may include one or more malware signatures generated by security computing subsystem104and/or any other data associated with malware security as may serve a particular application.

Local security module204may be configured to receive malware security data210from security computing subsystem104. Local security module204may be further configured to identify malware residing on client device102by comparing one or more files (e.g., files208) with one or more malware signatures provided by security computing subsystem104. Local security module204may be further configured to remove, quarantine, and/or otherwise treat files comprising or otherwise associated with malware.

Security computing subsystem104may include, but is not limited to, a remote security module212, an automatic malware signature generator214, and a storage device216.

Remote security module212may be configured to transmit malware security data210to local security module204of client device102. For example, remote security module212may transmit one or more malware updates comprising malware signatures generated by automatic malware signature generator214to local security module204. Remote security module212may transmit malware security data210on a periodic (e.g., daily or hourly) basis, in response to one or more newly generated malware signatures, and/or as requested by local security module204.

Automatic malware signature generator214may include any combination of hardware, software, and/or firmware configured to automatically generate one or more malware signatures. The malware signatures may be used to identify malware residing on client device102. Specific embodiments of automatic malware signature generator214will be described in more detail below.

Storage device216generally represents any type or form of storage device, such as the storage devices illustrated and described in connection withFIGS. 7 and 8. Storage device216may be configured to store library signature data218representative of one or more library signatures, malware signature data220representative of one or more malware signatures, malware data222representative of one or more malware programs, and/or any other type of data. Data218,220, and222may be arranged in one or more databases, look-up tables, and/or file structures as may serve a particular application. As will be described in more detail below, data218,220, and222may be generated, used, and/or modified by automatic malware signature generator214to generate one or more malware signatures.

As mentioned, it is desirable to ensure that the malware signatures generated by automatic malware signature generator214do not result in false positives when used to identify malware. A false positive may occur when goodware is incorrectly identified as comprising malware. In some instances, a false positive may result when the particular malware signature used to identify malware comprises a byte sequence representative of a library function. This is because library functions are often used by both malware and goodware. Hence, it is desirable to prevent byte sequences representative of library functions from being used as malware signatures in order to minimize the number of goodware programs that are incorrectly identified as malware using automatically generated malware signatures.

To this end, automatic malware signature generator214may be configured to identify byte sequences within a malware program that have a likelihood of being representative of library functions contained within the malware program. The identified byte sequences may then be prevented from being used as malware signatures. As will be described in more detail below, the identification of byte sequences within a malware program that have a likelihood of being representative of one or more library functions may be realized by marking one or more byte sequences as being associated with one or more library functions.

In some instances, it is possible that automatic signature generator214may incorrectly identify one or more byte sequences representative of one or more non-library functions as having a likelihood of being representative of one or more library functions. Such misidentification is acceptable in light of the desire to prevent any byte sequence that may potentially be associated with a library function from being used as a malware signature. In this manner, the number of goodware programs that are incorrectly identified as malware using automatically generated malware signatures may be minimized.

FIG. 3is a flow diagram of an exemplary method300for facilitating automatic malware signature generation. Each step shown inFIG. 3may be performed by one or more components of security computing subsystem104. For example, one or more steps shown inFIG. 3may be performed by automatic malware signature generator214. To this end,FIG. 4shows that automatic malware signature generator214may include a disassembly module402, a library function identification module404, a prevention module406, and a malware signature generation module408. One or more of these modules may be configured to perform one or more of the steps shown inFIG. 3.

In step302, a malware program is disassembled. For example, disassembly module402shown inFIG. 4may be configured to receive malware data222representative of a malware program and transform the malware program into a disassembled malware program. In this manner, the individual bytes that comprise the malware program may be analyzed. For example, disassembly module402may be configured to parse a binary image of a malware program and transform it into assembly language or some equivalent representation. Any suitable disassembly algorithm or heuristic may be used by disassembly module402to disassemble the malware program as may serve a particular application.

In step304, one or more byte sequences within the disassembled malware program that have a likelihood of being representative of one or more library functions contained within the malware program are identified. In some examples, the identifying may be performed by library function identification module404in accordance with one or more identification heuristics. Exemplary, but not exclusive, identification heuristics that may be used by library function identification module404to identify one or more byte sequences within a disassembled malware program that have a likelihood of being representative of one or more library functions will now be described.

In some embodiments, library function identification module404may identify a byte sequence within a disassembled malware program as having a likelihood of being representative of a library function by comparing the byte sequence with one or more library signatures associated with at least one compiler. The library signatures may be stored within storage device216as library signature data218. Each library signature comprises a sequence of bytes representative of a known library function. Hence, if a byte sequence within a disassembled malware program matches one of the library signatures, library function identification module404may mark the byte sequence as being associated with a library function.

As mentioned, the one or more library signatures to which a byte sequence is compared may be associated with at least one compiler. Exemplary compilers include, but are not limited to, Borland Delphi, Microsoft Visual C, C++, Java, etc. In some examples, a byte sequence within a malware program is compared to library signatures associated with a plurality of different compilers, regardless of the particular compiler used to generate the malware program. This is because an author of a particular malware program can post-process the malware program to hide or obfuscate the information that reveals which compiler generated the particular malware program. Hence, as long as a byte sequence within a malware program matches a library signature corresponding to a library function associated with a particular compiler within the plurality of compilers, the byte sequence may be identified as having a likelihood of being representative of a library function, even if the particular compiler does not appear to have been used to generate the malware program.

An additional or alternative identification heuristic that may be used by library function identification module404includes marking a byte sequence within a disassembled malware program that represents a function called (statically or in some other manner) by a known library function as being associated with a library function. The known library function may be represented by library signature data218, identified in the library signature comparison heuristic described above, and/or provided in any other manner as may serve a particular application.

A library typically includes one or more entry point functions, which are exposed to application developers, and internal functions, which are used internally within a library. An entry point function may call, either directly or indirectly, one or more other entry point functions and/or internal functions. In some examples, a function called by a known library function is also a library function. Hence, by determining which functions within a malware program are called by entry point functions and other known library functions, library function identification module404may mark the byte sequences corresponding to the called functions as being associated with library functions.

To facilitate identification of functions contained within a malware program that are called by known library functions, library function identification module404may be configured to build a function call graph representation of the malware program.

FIG. 5illustrates an exemplary function call graph representation500that may be built by library function identification module404. As shown inFIG. 5, function call graph representation500is configured to illustrate a call relationship between a plurality of functions contained within a malware program. For example,FIG. 5shows that a main function502, which may be an entry point function, calls a first function504. The first function504calls a second function506and a third function508. The third function508calls a fourth function510. The fourth function calls an Nth function512. It will be recognized that the call relationship illustrated inFIG. 5is merely illustrative of the many different call relationships that may exist within a particular malware program.

By analyzing function call graph representation500, library function identification module404may determine whether a function represented by a particular byte sequence within the malware program is called, either directly or indirectly, by a known library function. For example, function identification module404may determine, based on function call graph representation500, that byte sequences associated with functions502-512are associated with library functions and mark the byte sequences accordingly.

Once a byte sequence has been identified as being associated with a function called by a known library function, the function associated with the byte sequence is analyzed to determine if it calls any other functions. Byte sequences corresponding to those functions may in turn be marked as library functions. The process may be repeated until the set of marked library functions converges.

In some examples, a library function (e.g., an entry point function) calls another function through a function pointer. In some instances, these types of function calls do not appear in a function call graph representation. Hence, library function identification module404may be configured to heuristically detect function pointer tables used in known library functions, use these tables to identify functions called in this manner, and mark byte sequences corresponding to the identified functions as library functions. The function pointer tables may be detected using any suitable algorithm or heuristic as may serve a particular application.

In some examples, a compiler of a malware program automatically includes one or more startup functions within the malware program that call non-library functions included within the malware program. While these automatically included functions are sometimes referred to as library functions, library function identification module404may be configured to mark them as non-library functions. In this manner, other non-library functions called by such functions will not be marked as being library functions.

To illustrate, a “start” function may be automatically included by a compiler in a portable executable (PE) binary. This function may be configured to call non-library functions within the PE binary. Hence, library function identification module404may be configured to mark the “start” function as a non-library function. Library function identification module404may be configured to detect automatically included functions that call non-library functions and exclude the automatically included functions from being considered as library functions using any suitable heuristic as may serve a particular application.

For example, suppose that the main function502inFIG. 5is an automatically included startup function. It may therefore be considered to be a non-library function. Hence, if function508is a known library function, it can be deduced that functions510and512are also library functions because they are called by function508. However, functions504and506can remain classified as non-library functions since they merely call (and are not called by) known library functions.

An additional or alternative identification heuristic that may be used by library function identification module404includes marking one or more byte sequences within a malware program that are located within a predetermined distance from an address space corresponding to at least one known library function as being associated with a library function. When a library is statically linked into a binary malware program, the library occupies a contiguous address space range. Therefore, a byte sequence occupying an address space immediately surrounded by address spaces occupied by byte sequences associated with known library functions has a high likelihood of also being associated with a library function.

This physical proximity property of functions that belong to the same library may be exploited by library function identification module404to identify byte sequences having a likelihood of being associated with library functions. For example, library function identification module404may be configured to recognize that a particular byte sequence occupies an address space surrounded by address spaces immediately surrounded by address spaces occupied by byte sequences associated with known library functions and mark the byte sequence as being associated with a library function.

In some instances, padding space may be located in between address spaces corresponding to adjacent functions in a library. To illustrate,FIG. 6shows a representation of an exemplary address space range600. As shown inFIG. 6, byte sequences associated with known library functions may occupy address spaces602and604. Each address space602and604is separated from adjacent address spaces associated with other functions by padding space (e.g., padding space606-1and606-2, collectively referred to herein as “padding space606”). Each padding space606may be of any suitable size depending on the particular malware program.

To account for possible presence of padding space606, library function identification module404may be configured to detect whether a byte sequence occupies an address space that is within a predetermined threshold distance from an address space occupied by a known library function. If it is, library function identification module404may be configured to mark the byte sequence as being associated with a library function.

For example,FIG. 6shows that a particular byte sequence may occupy an address space608, which is immediately surrounded by padding space606. Library function identification module404may be configured to determine whether address space608is within a predetermined threshold distance from address space602and/or address space604. If address space608is within the predetermined threshold distance from either one of address spaces602and604, the byte sequence occupying address space608may be marked as being associated with a library function.

The predetermined threshold distance may be determined in any suitable manner. For example, the predetermined threshold distance may be based on a statistical analysis of the inter-library address space and intra-library address space of a plurality of binary malware and/or goodware programs generated by one or more compilers. The statistical analysis may be configured to determine an average size of padding spaces606, a maximum size of padding spaces606, and/or any other metric associated with the padding spaces606as may serve a particular application.

An additional or alternative identification heuristic that may be used by library function identification module404includes determining whether a byte sequence included within a malware program represents a function that accesses at least one global variable associated with the malware program. It will be recognized that libraries rarely export global variables for use outside of library functions. Hence, a byte sequence associated with a function that accesses one or more global variables may be marked by library function identification module404as being associated with a library function. To this end, library identification module404or any other suitable module may be configured to generate a list of global variables accessed by known library functions. The list of global variables may be generated in any suitable manner as may serve a particular application.

In some examples, one or more of the identification heuristics described herein may be used in an iterative manner by library function identification module404to mark byte sequences within a malware program as being associated with a library function until the set of marked byte sequences converges. For example, a first set of byte sequences may be marked as being associated with library functions by comparing the byte sequences to library signatures. Functions called by functions associated with the marked byte sequences may then be identified in order to mark more byte sequences as being associated with library functions. Address space proximity of byte sequences to address spaces associated with each of the identified library functions may then be used to mark yet more byte sequences as being associated with library functions. Global variable analysis may then be performed to identify more library functions. One or more of these steps may be repeated until the set of marked byte sequences converges. For purposes of the identification heuristics described herein, a byte sequence identified as having a likelihood of being representative of a library function may be treated as being representative of a known library function. It will be recognized that identification heuristics may be applied to a particular malware program in any order.

Returning toFIG. 3, the byte sequences identified as having a likelihood of being representative of one or more library functions are prevented from being included within one or more malware signatures (step306). For example, prevention module406included within automatic malware signature generator214may be configured to receive data indicative of which byte sequences have been identified as having a likelihood of being representative of a library function. Prevention module406may then prevent these byte sequences from being included within malware signatures generated by automatic malware signature generator214. Prevention module406may be configured to prevent byte sequences from being included within malware signatures generated by automatic malware signature generator214in any suitable manner as may serve a particular application.

In step308, one or more malware signatures are generated. For example, malware signature generation module408included within automatic malware signature generator214may be configured to generate one or more malware signatures using one or more byte sequences associated with non-library functions. Malware signature data220and storage device216may be transformed in response to the generation of the malware signatures.

It will be recognized that one or more of the steps shown inFIG. 3may be repeated for a plurality of malware programs in order to identify byte sequences contained within one or more of the malware programs that are associated with non-library functions. In this manner, the set of marked byte sequences associated with library functions may be increased, thereby decreasing the likelihood of generating malware signatures that result in false positives.

As detailed above, the automatic generation of malware signatures used to identify malware may be based on non-library functions included within malware as opposed to library functions that may be included within both malware and goodware. By proceeding in this manner, the exemplary systems and methods described herein may reduce the number of byte sequences associated with library functions used to generate malware signatures, and thereby minimize the number of goodware programs incorrectly identified as comprising malware.

FIG. 7is a block diagram of an exemplary computing system710capable of implementing one or more of the embodiments described and/or illustrated herein. Computing system710broadly represents any single or multi-processor computing device or system capable of executing computer-readable instructions. Examples of computing system710include, without limitation, workstations, laptops, client-side terminals, servers, distributed computing systems, handheld devices, or any other computing system or device. In its most basic configuration, computing system710may comprise at least one processor714and a system memory716.

Processor714generally represents any type or form of processing unit capable of processing data or interpreting and executing instructions. In certain embodiments, processor714may receive instructions from a software application or module. These instructions may cause processor714to perform the functions of one or more of the exemplary embodiments described and/or illustrated herein. For example, processor714may perform and/or be a means for performing, either alone or in combination with other elements, one or more of the disassembling, identifying, preventing, and generating steps described herein. Processor714may also perform and/or be a means for performing any other steps, methods, or processes described and/or illustrated herein.

System memory716generally represents any type or form of volatile or non-volatile storage device or medium capable of storing data and/or other computer-readable instructions. Examples of system memory716include, without limitation, random access memory (RAM), read only memory (ROM), flash memory, or any other suitable memory device. Although not required, in certain embodiments computing system710may comprise both a volatile memory unit (such as, for example, system memory716) and a non-volatile storage device (such as, for example, primary storage device732, as described in detail below).

In certain embodiments, exemplary computing system710may also comprise one or more components or elements in addition to processor714and system memory716. For example, as illustrated inFIG. 7, computing system710may comprise a memory controller718, an Input/Output (I/O) controller720, and a communication interface722, each of which may be interconnected via a communication infrastructure712. Communication infrastructure712generally represents any type or form of infrastructure capable of facilitating communication between one or more components of a computing device. Examples of communication infrastructure712include, without limitation, a communication bus (such as an ISA, PCI, PCIe, or similar bus) and a network.

Memory controller718generally represents any type or form of device capable of handling memory or data or controlling communication between one or more components of computing system710. For example, in certain embodiments memory controller718may control communication between processor714, system memory716, and I/O controller720via communication infrastructure712. In certain embodiments, memory controller may perform and/or be a means for performing, either alone or in combination with other elements, one or more of the steps or features described and/or illustrated herein, such as disassembling, identifying, preventing, and generating.

I/O controller720generally represents any type or form of module capable of coordinating and/or controlling the input and output functions of a computing device. For example, in certain embodiments I/O controller720may control or facilitate transfer of data between one or more elements of computing system710, such as processor714, system memory716, communication interface722, display adapter726, input interface730, and storage interface734. I/O controller720may be used, for example, to perform and/or be a means for performing, either alone or in combination with other elements, one or more of the disassembling, identifying, preventing, and generating steps described herein. I/O controller720may also be used to perform and/or be a means for performing other steps and features set forth in the instant disclosure.

Communication interface722broadly represents any type or form of communication device or adapter capable of facilitating communication between exemplary computing system710and one or more additional devices. For example, in certain embodiments communication interface722may facilitate communication between computing system710and a private or public network comprising additional computing systems. Examples of communication interface722include, without limitation, a wired network interface (such as a network interface card), a wireless network interface (such as a wireless network interface card), a modem, and any other suitable interface. In at least one embodiment, communication interface722may provide a direct connection to a remote server via a direct link to a network, such as the Internet. Communication interface722may also indirectly provide such a connection through, for example, a local area network (such as an Ethernet network), a personal area network, a telephone or cable network, a cellular telephone connection, a satellite data connection, or any other suitable connection.

In certain embodiments, communication interface722may also represent a host adapter configured to facilitate communication between computing system710and one or more additional network or storage devices via an external bus or communications channel. Examples of host adapters include, without limitation, SCSI host adapters, USB host adapters, IEEE 794 host adapters, SATA and eSATA host adapters, ATA and PATA host adapters, Fibre Channel interface adapters, Ethernet adapters, or the like. Communication interface722may also allow computing system710to engage in distributed or remote computing. For example, communication interface722may receive instructions from a remote device or send instructions to a remote device for execution. In certain embodiments, communication interface722may perform and/or be a means for performing, either alone or in combination with other elements, one or more of the disassembling, identifying, preventing, and generating steps disclosed herein. Communication interface722may also be used to perform and/or be a means for performing other steps and features set forth in the instant disclosure.

As illustrated inFIG. 7, computing system710may also comprise at least one display device724coupled to communication infrastructure712via a display adapter726. Display device724generally represents any type or form of device capable of visually displaying information forwarded by display adapter726. Similarly, display adapter726generally represents any type or form of device configured to forward graphics, text, and other data from communication infrastructure712(or from a frame buffer, as known in the art) for display on display device724.

As illustrated inFIG. 7, exemplary computing system710may also comprise at least one input device728coupled to communication infrastructure712via an input interface730. Input device728generally represents any type or form of input device capable of providing input, either computer or human generated, to exemplary computing system710. Examples of input device728include, without limitation, a keyboard, a pointing device, a speech recognition device, or any other input device. In at least one embodiment, input device728may perform and/or be a means for performing, either alone or in combination with other elements, one or more of the disassembling, identifying, preventing, and generating steps disclosed herein. Input device728may also be used to perform and/or be a means for performing other steps and features set forth in the instant disclosure.

As illustrated inFIG. 7, exemplary computing system710may also comprise a primary storage device732and a backup storage device733coupled to communication infrastructure712via a storage interface734. Storage devices732and733generally represent any type or form of storage device or medium capable of storing data and/or other computer-readable instructions. For example, storage devices732and733may be a magnetic disk drive (e.g., a so-called hard drive), a floppy disk drive, a magnetic tape drive, an optical disk drive, a flash drive, or the like. Storage interface734generally represents any type or form of interface or device for transferring data between storage devices732and733and other components of computing system710.

In certain embodiments, storage devices732and733may be configured to read from and/or write to a removable storage unit configured to store computer software, data, or other computer-readable information. Examples of suitable removable storage units include, without limitation, a floppy disk, a magnetic tape, an optical disk, a flash memory device, or the like. Storage devices732and733may also comprise other similar structures or devices for allowing computer software, data, or other computer-readable instructions to be loaded into computing system710. For example, storage devices732and733may be configured to read and write software, data, or other computer-readable information. Storage devices732and733may also be a part of computing system710or may be a separate device accessed through other interface systems.

In certain embodiments, storage devices732and733may be used, for example, to perform and/or be a means for performing, either alone or in combination with other elements, one or more of the disassembling, identifying, preventing, and generating steps disclosed herein. Storage devices732and733may also be used to perform and/or be a means for performing other steps and features set forth in the instant disclosure.

The computer-readable storage medium containing the computer program may be loaded into computing system710. All or a portion of the computer program stored on the computer-readable storage medium may then be stored in system memory716and/or various portions of storage devices732and733. When executed by processor714, a computer program loaded into computing system710may cause processor714to perform and/or be a means for performing the functions of one or more of the exemplary embodiments described and/or illustrated herein. Additionally or alternatively, one or more of the exemplary embodiments described and/or illustrated herein may be implemented in firmware and/or hardware. For example, computing system710may be configured as an application specific integrated circuit (ASIC) adapted to implement one or more of the exemplary embodiments disclosed herein.

FIG. 8is a block diagram of an exemplary network architecture800in which client systems810,820, and830and servers840and845may be coupled to a network850. Client systems810,820, and830generally represent any type or form of computing device or system, such as exemplary computing system710inFIG. 7. Similarly, servers840and845generally represent computing devices or systems, such as application servers or database servers, configured to provide various database services and/or run certain software applications. Network850generally represents any telecommunication or computer network including, for example, an intranet, a wide area network (WAN), a local area network (LAN), a personal area network (PAN), or the Internet.

As illustrated inFIG. 8, one or more storage devices860(1)-(N) may be directly attached to server840. Similarly, one or more storage devices870(1)-(N) may be directly attached to server845. Storage devices860(1)-(N) and storage devices870(1)-(N) generally represent any type or form of storage device or medium capable of storing data and/or other computer-readable instructions. In certain embodiments, storage devices860(1)-(N) and storage devices870(1)-(N) may represent network-attached storage (NAS) devices configured to communicate with servers840and845using various protocols, such as NFS, SMB, or CIFS.

Servers840and845may also be connected to a storage area network (SAN) fabric880. SAN fabric880generally represents any type or form of computer network or architecture capable of facilitating communication between a plurality of storage devices. SAN fabric880may facilitate communication between servers840and845and a plurality of storage devices890(1)-(N) and/or an intelligent storage array895. SAN fabric880may also facilitate, via network850and servers840and845, communication between client systems810,820, and830and storage devices890(1)-(N) and/or intelligent storage array895in such a manner that devices890(1)-(N) and array895appear as locally attached devices to client systems810,820, and830. As with storage devices860(1)-(N) and storage devices870(1)-(N), storage devices890(1)-(N) and intelligent storage array895generally represent any type or form of storage device or medium capable of storing data and/or other computer-readable instructions.

In certain embodiments, and with reference to exemplary computing system710ofFIG. 7, a communication interface, such as communication interface722inFIG. 7, may be used to provide connectivity between each client system810,820, and830and network850. Client systems810,820, and830may be able to access information on server840or845using, for example, a web browser or other client software. Such software may allow client systems810,820, and830to access data hosted by server840, server845, storage devices860(1)-(N), storage devices870(1)-(N), storage devices890(1)-(N), or intelligent storage array895. AlthoughFIG. 8depicts the use of a network (such as the Internet) for exchanging data, the embodiments described and/or illustrated herein are not limited to the Internet or any particular network-based environment.

In at least one embodiment, all or a portion of one or more of the exemplary embodiments disclosed herein may be encoded as a computer program and loaded onto and executed by server840, server845, storage devices860(1)-(N), storage devices870(1)-(N), storage devices890(1)-(N), intelligent storage array895, or any combination thereof. All or a portion of one or more of the exemplary embodiments disclosed herein may also be encoded as a computer program, stored in server840, run by server845, and distributed to client systems810,820, and830over network850. Accordingly, network architecture800may perform and/or be a means for disassembling, identifying, preventing, and generating steps disclosed herein. Network architecture800may also be used to perform and/or be a means for performing other steps and features set forth in the instant disclosure.

As detailed above, computing system710and/or one or more components of network architecture800may perform and/or be a means for performing, either alone or in combination with other elements, one or more steps of an exemplary method for facilitating automatic malware signature generation. In one example, a method for performing such a task may comprise: 1) disassembling a malware program, 2) identifying one or more byte sequences within the disassembled malware program that have a likelihood of being representative of one or more library functions contained within the malware program, and 3) preventing the one or more byte sequences from being included within one or more malware signatures.

In some embodiments, the identified one or more byte sequences match one or more library signatures associated with at least one compiler.

The identified one or more byte sequences may additionally or alternatively represent one or more functions called by at least one known library function. To identify the one or more functions called by at least one known library function, the method may further include building a function call graph representation of the malware program and using the function call graph representation to determine that the one or more byte sequences represent the one or more functions called by the at least one known library function. Additionally or alternatively, the method may include detecting one or more function pointer tables used in the at least one known library function and using the one or more function pointer tables to determine that the one or more byte sequences represent the one or more functions called by the at least one known library function. Additionally or alternatively, the method may include excluding from the at least one known library function one or more functions automatically included within the malware program by a compiler of the malware program.

In some embodiments, the identified one or more byte sequences represent one or more functions directly or indirectly called by the at least one known library function.

In some embodiments, the identified one or more byte sequences are located within a predetermined threshold distance from an address space corresponding to at least one of the known library functions. For example, the identified one or more byte sequences may be located at an address immediately surrounded by address spaces corresponding to two of the known library functions. In some embodiments, the method further comprises basing the predetermined threshold distance on a statistical analysis of inter-library space and intra-library space in programs generated by one or more compilers.

In some embodiments, the identified one or more byte sequences represent one or more functions that access at least one global variable. A variable may be determined to be one of the at least one global variable if the variable is accessed by at least one known library function.

In some embodiments, a system for facilitating automatic malware signature generation includes a disassembly module configured to disassemble a malware program, a library function identification module communicatively coupled to the disassembly module and configured to identify one or more byte sequences within the disassembled malware program that have a likelihood of being associated with one or more library functions contained within the malware program, and a prevention module communicatively coupled to the library function identification module and configured to prevent the one or more byte sequences from being included within one or more malware signatures.

In some embodiments, a computer-readable storage medium includes instructions configured to direct a computer system to disassemble a malware program, identify one or more byte sequences within the disassembled malware program that have a likelihood of being representative of one or more library functions contained within the malware program, and prevent the one or more byte sequences from being included within one or more malware signatures.