Abstract: A device may detect or emulate a sequence of keystrokes to be used to detect a keystroke logger application. The device may determine a sequence of characters associated with the sequence of keystrokes. The sequence of characters may correspond to the sequence of keystrokes or a portion of the sequence of keystrokes. The device may search a memory for the sequence of characters. The device may determine that the sequence of characters is stored in the memory based on searching the memory for the sequence of characters. The device may perform an action to counteract the keystroke logger application based on determining that the sequence of characters is stored in the memory.

Abstract: A security device may receive, from a client device, a request associated with a server device. The security device may determine a communication channel and contact information for validating the request. The security device may provide validation information via the communication channel using the contact information. The security device may receive a validation response from the client device, and may determine whether the validation response is valid. The security device may selectively perform a first action or a second action based on determining whether the validation response is valid. The first action may be performed based on determining that the validation response is valid, and may include providing a validation indicator, with the request, to the server device. The second action may be performed based on determining that the validation response is not valid, and may include providing an invalidation indicator, with the request, to the server device.

Abstract: A device may determine a first set of hash values corresponding to a first set of files stored by a plurality of client devices. The device may analyze information associated with the first set of hash values to determine a second set of hash values corresponding to a second set of files to be analyzed. The second set of hash values may be different from the first set of hash values. The device may prioritize the second set of hash values to form a prioritized set of hash values corresponding to a prioritized set of files, of the second set of files, to be analyzed. The device may request the prioritized set of files from one or more client devices of the plurality of client devices. The device may receive the prioritized set of files, and may cause the prioritized set of files to be analyzed.

Abstract: A security device may receive actual behavior information associated with an object. The actual behavior information may identify a first set of behaviors associated with executing the object in a live environment. The security device may determine test behavior information associated with the object. The test behavior information may identify a second set of behaviors associated with testing the object in a test environment. The security device may compare the first set of behaviors and the second set of behaviors to determine a difference between the first set of behaviors and the second set of behaviors. The security device may identify whether the object is an evasive malicious object based on the difference between the first set of behaviors and the second set of behaviors. The security device may provide an indication of whether the object is an evasive malicious object.

Abstract: A device may detect an attack. The device may receive, from a client device, a request for a resource. The device may determine, based on detecting the attack, a computationally expensive problem to be provided to the client device, where the computationally expensive problem requires a computation by the client device to solve the computationally expensive problem. The device may instruct the client device to provide a solution to the computationally expensive problem. The device may receive, from the client device, the solution to the computationally expensive problem. The device may selectively provide the client device with access to the resource based on the solution.

Abstract: A device may receive a password-protected file to be accessed for analysis. The device may identify a contextual term, associated with the password-protected file, to be used as a password to attempt to access the password-protected file. The contextual term may be identified based on at least one of: metadata associated with the password-protected file, metadata associated with a source from which the password-protected file is received, or text associated with the source from which the password-protected file is received. The device may apply the contextual term as the password to attempt to access the password-protected file.

Abstract: A device may analyze a first file for malware. The device may determine that the first file causes a second file to be downloaded. The device may store linkage information that identifies a relationship between the first file and the second file based on determining that the first file causes the second file to be downloaded. The device may analyze the second file for malware. The device may determine a first malware score for the first file based on analyzing the second file for malware and based on the linkage information. The device may determine a second malware score for the second file based on analyzing the first file for malware and based on the linkage information.

Abstract: A device may receive a trigger to determine whether one or more client devices, of a set of client devices, are infected by a malicious file. The device may generate file identification information associated with the malicious file based on receiving the trigger to determine whether the one or more client devices are infected by the malicious file. The device may obtain remote access to the one or more client devices using a connection tool based on receiving the trigger to determine whether the one or more client devices are infected by the malicious file. The device may obtain information, associated with the one or more client devices, using the remote access. The device may provide information indicating whether the one or more client devices are infected by the malicious file based on the file identification information and the information associated with the one or more client devices.

Abstract: A security device may receive actual behavior information associated with an object. The actual behavior information may identify a first set of behaviors associated with executing the object in a live environment. The security device may determine test behavior information associated with the object. The test behavior information may identify a second set of behaviors associated with testing the object in a test environment. The security device may compare the first set of behaviors and the second set of behaviors to determine a difference between the first set of behaviors and the second set of behaviors. The security device may identify whether the object is an evasive malicious object based on the difference between the first set of behaviors and the second set of behaviors. The security device may provide an indication of whether the object is an evasive malicious object.

Abstract: A system may determine to perform an internal and an external malware detection operation to detect a malware infection associated with a client device. The system may perform the internal operation by modifying an environment, executing on a particular device, to form a modified environment. The system may perform the external operation by performing a communication from the particular device. The system may monitor the modified environment for a first behavior indicative of the malware infection, and may monitor a result of performing the communication for a second behavior indicative of the malware infection. The system may detect that the first or second behavior has occurred. The system may provide a notification that the client device is infected with malware based on detecting that the first or second behavior has occurred. The notification may cause one or more network devices to block network traffic to or from the client device.

Abstract: This disclosure describes techniques for proactively identifying possible attackers based on a profile of a device. For example, a device includes one or more processors and network interface cards to receive, from a remote device, network traffic directed to one or more computing devices protected by the device, determine, based on content of the network traffic, a first set of data points for the device, send a response to the remote device to ascertain a second set of data points for the device, and receive, from the remote device, at least a portion of the second set of data points. The device also includes a security module operable by the processors to determine a maliciousness rating, and selectively manage, based on the maliciousness rating, additional network traffic directed to the one or more computing devices protected by the security device and received from the remote device.

Abstract: A network device comprises one or more processors coupled to a memory, and a dynamic services module configured for execution by the one or more processors to receive, from a client device, a service request specifying a service. The dynamic service module is further configured for execution by the one or more processors to, in response to obtaining a negative indication for the service, send a representation of the service request to a honeypot to cause the honeypot to offer the service to the client device.

Abstract: A device may detect or emulate a sequence of keystrokes to be used to detect a keystroke logger application. The device may determine a sequence of characters associated with the sequence of keystrokes. The sequence of characters may correspond to the sequence of keystrokes or a portion of the sequence of keystrokes. The device may search a memory for the sequence of characters. The device may determine that the sequence of characters is stored in the memory based on searching the memory for the sequence of characters. The device may perform an action to counteract the keystroke logger application based on determining that the sequence of characters is stored in the memory.

Abstract: A device may receive a trigger to determine whether a malicious file is operating on a client device. The device may determine a network activity profile associated with the malicious file based on receiving the trigger to determine whether the malicious file is operating on the client device. The network activity profile may include information regarding network activity associated with the malicious file when the malicious file is executed in a testing environment. The device may monitor network activity associated with the client device. The device may determine that the network activity associated with the client device matches the network activity profile associated with the malicious file based on monitoring the network activity associated with the client device. The device may provide information indicating that the network activity associated with the client device matches the network activity profile associated with the malicious file.

Abstract: A device may receive a file to be analyzed in a sandbox environment, and may determine configuration information for configuring the sandbox environment. The configuration information may be determined based on at least one of: file information associated with the file to be analyzed, or client device information associated with a client device for which the file is intended. The device may configure the sandbox environment using the configuration information. The configuration information may identify a system configuration for the sandbox environment. The device may analyze the file in the sandbox environment based on configuring the sandbox environment using the configuration information.

Abstract: A device may analyze a first file for malware. The device may determine that the first file causes a second file to be downloaded. The device may store linkage information that identifies a relationship between the first file and the second file based on determining that the first file causes the second file to be downloaded. The device may analyze the second file for malware. The device may determine a first malware score for the first file based on analyzing the second file for malware and based on the linkage information. The device may determine a second malware score for the second file based on analyzing the first file for malware and based on the linkage information.

Abstract: A device may determine that a file of a client device is a malicious file. The device may obtain remote access to the client device using a connection tool. The connection tool may provide access and control of the client device. The remote access may include access to a file location of the malicious file. The device may determine file information associated with the malicious file using the remote access to the client device. The device may select one or more remediation actions based on the file information. The device may cause the one or more remediation actions to be executed using the remote access to the client device.

Abstract: A device may identify a set of features associated with the unknown object. The device may determine, based on inputting the set of features into a threat prediction model associated with a set of security functions, a set of predicted threat scores. The device may determine, based on the set of predicted threat scores, a set of predicted utility values. The device may determine a set of costs corresponding to the set of security functions. The device may determine a set of predicted efficiencies, associated with the set of security functions, based on the set of predicted utility values and the set of costs. The device may identify, based on the set of predicted efficiencies, a particular security function, and may cause the particular security function to be executed on the unknown object. The device may determine whether another security function is to be executed on the unknown object.

Abstract: A device may detect an attack. The device may receive, from a client device, a request for a resource. The device may determine, based on detecting the attack, a computationally expensive problem to be provided to the client device, where the computationally expensive problem requires a computation by the client device to solve the computationally expensive problem. The device may instruct the client device to provide a solution to the computationally expensive problem. The device may receive, from the client device, the solution to the computationally expensive problem. The device may selectively provide the client device with access to the resource based on the solution.

Abstract: A system may determine to perform an internal and an external malware detection operation to detect a malware infection associated with a client device. The system may perform the internal operation by modifying an environment, executing on a particular device, to form a modified environment. The system may perform the external operation by performing a communication from the particular device. The system may monitor the modified environment for a first behavior indicative of the malware infection, and may monitor a result of performing the communication for a second behavior indicative of the malware infection. The system may detect that the first or second behavior has occurred. The system may provide a notification that the client device is infected with malware based on detecting that the first or second behavior has occurred. The notification may cause one or more network devices to block network traffic to or from the client device.