Sonicwall Inc.

Soumyadipta Das

Aleksandr Dubrovsky

Senthilkumar Gopinathan Cheetancheri

Sai Sravan Kumar Ganachari

Yao He

Igor Korsunsky

SushilKumar Kuchan

Bhushit Joshipura

Navaneeth Ashok

Arun Yogeesh

John Everett Gmuender

Atul Dhablania

Alex M Dubrovsky

The present disclosure is directed to protecting data stored at a database in a manner that increases data protection minimizing performance reductions. Apparatus and methods consistent with the present disclosure may collect information from user devices from which user inputs are received when collecting data that may be used to protect database data. Methods consistent with the present disclosure may identify code paths traversed, pages of program code where actions were initiated, and functions associated with those actions. This information may be cross-referenced with a set of data, constraints, rules, or command parameters when data associated with a database query is initially associated with an 'allow' action or a “deny” action. This information may also be used to evaluate whether newly generated database queries should be allowed to be sent to a database server or to identify whether a database request should be blocked.

Call location based access control of query to database

The present disclosure is directed to analyzing received sets of computer data. Methods and apparatus consistent with the present disclosure may forecast that a received set of computer data does not include malware after allowing instructions included in that set of computer data to execute for an amount of time that does not exceed an allocated amount of time. Methods consistent with the present disclosure may instrument a set of received program code and allow instructions in that received set of program code to execute as instrumentation code collects information about the set of program code. This collected information may be compared with sets of known good data when determining whether a received set of program code is likely not to include malware. This collected information may be associated with 'behaviors' performed by the received set of program code that may be identified using sets of contextual data.

Early filtering of clean file using dynamic analysis

The present disclosure is directed to monitoring internal process memory of a computer at a time with program code executes. Methods and apparatus consistent with the present disclosure monitor the operation of program code with the intent of detecting whether received program inputs may exploit vulnerabilities that may exist in the program code at runtime. By detecting suspicious activity or malicious code that may affect internal process memory at run-time, methods and apparatus described herein identify suspected malware based on suspicious actions performed as program code executes. Runtime exploit detection may detect certain anomalous activities or chain of events in a potentially vulnerable application during execution. These events may be detected using instrumentation code when a regular code execution path of an application is deviated from.

Detection of exploitative program code

Methods and apparatus consistent with the present disclosure may be performed by a Cloud computing device may use instrumentation code that remains transparent to an application program that the instrumentation code has been injected into, may perform deep packet inspection (DPI) on computer data, or identify a content rating associated with computer data. In certain instances, data sets that include executable code may be received via packetized communications or be received via other means, such as, receiving a file from a data store. The present technique allows one or more processors executing instrumentation code to monitor actions performed by the program code included in a received data set. Malware can be detected using exception handling to track memory allocations of the program code included in the received data set. Furthermore, access to content associated with malware, potential malware, or with inappropriate content ratings may be blocked.

Cloud based just in time memory analysis for malware detection

The present disclosure is directed to protecting data stored at a database in a manner that increases data protection minimizing performance reductions. Apparatus and methods consistent with the present disclosure may collect information from user devices from which user inputs are received when collecting data that may be used to protect database data. Methods consistent with the present disclosure may identify code paths traversed, pages of program code where actions were initiated, and functions associated with those actions. This information may be cross-referenced with a set of data, constraints, rules, or command parameters when data associated with a database query is initially associated with an 'allow' action or a 'deny' action. This information may also be used to evaluate whether newly generated database queries should be allowed to be sent to a database server or to identify whether a database request should be blocked.

Methods and apparatus consistent with the present disclosure may use instrumentation code that remains transparent to an application program that the instrumentation code has been injected into. In certain instances, data sets that include executable code may be received via packetized communications or be received via other means, such as, receiving a file from a data store. The present technique allows a processor executing instrumentation code to monitor actions performed by the program code included in a received data set. Malware may be detected by scanning suspect program code with a malware scanner, malware may be detected by identifying suspicious actions performed by a set of program code, or malware may be detected by a combination of such techniques.

Just in time memory analysis for malware detection

Methods and apparatus consistent with the present disclosure may use instrumentation code that remains transparent to an application program that the instrumentation code has been injected into. In certain instances, data sets that include executable code may be received via packetized communications or be received via other means, such as, receiving a file from a data store. The present technique allows one or more processors executing instrumentation code to monitor actions performed by the program code included in a received data set. Malware can be detected using exception handling to track memory allocations of the program code included in the received data set.

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Bengaluru, India

Soumyadipta Das