Abstract: A method for identifying bundled software and an apparatus therefor. The method comprises: detecting a user interface for software installation; acquiring text information on the user interface; determining whether bundled software exists; and, based upon the determination, extracting the name and amount of bundled software from the text information and prompting the name and the amount of the bundled software. The embodiments may identify bundled software before installing software and avoid starting the bundled software process, having the effect of anti-bundling on the bundled software in advance. By extracting the name of the bundled software, acquiring the amount of bundled software, and prompting the name and amount of the bundled software, a user is able to determine whether to install the bundled software according to his or her requirements, thereby improving the autonomous right of selection of the user in the process of installing software.

Abstract: The present application provides a method and system for detecting malicious web addresses. The method includes: receiving a uniform resource locator (URL) reported by a user; acquiring a HyperText Transfer Protocol (HTTP) request chain associated with the URL, wherein the HTTP request chain is a sequential linked list including information about multiple HTTP request-response interactions during an access to the URL; and analyzing the HTTP request chain to determine whether the URL is a malicious web address. The technical solution of the present application can provide an accurate result of malicious web address detection, can detect various newly emerging malicious web addresses, and are user-friendly. The user only needs to upload the URL and does not need to provide any other information.

Abstract: The present application discloses a method and a system for detecting malicious code. The method comprises receiving a testing sample; testing the sample with a plurality of malicious code detectors to obtain a plurality of testing results; determining a credibility scale and a reputation value of each of the testing results, wherein the credibility scale indicates whether the testing result is malicious or safe, and the reputation value indicates a quantified trust level corresponding to the credibility scale; and determining a final detection result of the testing sample based on the determined credibility scales and the reputation values of the testing results. According to the technical solution of the present application, the testing results obtained from various malicious code detectors are rationally utilized to improve the testing accuracy for the malicious code.

Abstract: The present application discloses a method and an apparatus for file identification. The method for file identification comprises: determining a virus family of each malicious file sample in a plurality of the file samples resulting in a plurality of virus families; dividing the plurality of the virus families into at least one sample group based on a number of the malicious files belonging to each of the plurality of virus families; training the malicious file samples in each of the at least one sample group with a different training rule to obtain at least one file identification model; and determining, using the at least one identification model whether a file is a malicious file. The method for file identification of the present application may provide different identification models for various types of malicious files and thus improves the accuracy of the file identification.

Abstract: The present application discloses a method, an apparatus and a terminal for detecting a malware file. One embodiment of the method comprises: obtaining a file to be inspected; determining an entropy vector of the file; and inspecting the entropy vector of the file using a trained inspection model to determine if the file is a malware file, wherein a file type of the file is identical to the file type corresponding to the inspection model. This embodiment extracts the entropy vector of the file and determines if the file is a malware file based on the entropy vector of the file. Therefore, the technical problems existed in the art, such as a low speed, a poor capacity and a low efficiency of detecting and destroying the malware file, are addressed and the efficiency of detecting and destroying the malware file is enhanced.

Abstract: A method, apparatus, and device for locating a software failure are disclosed. The method comprises: determining a locating start time; obtaining a system environment at the locating start time; reproducing a running state of the software from the locating start time to an occurrence time of a software failure in the system environment at the locating start time; determining a cause of the software failure based on the reproduced running state. The apparatus comprises: a determination module, an obtaining module, a reproduction module, and an analysis module. Through this approach, automatic locating of a software failure is implemented, which helps the user to be aware of the operation problem and facilitates a software developer to find a deficiency in the software design.

Abstract: A method for identifying bundled software and an apparatus therefor. The method comprises: detecting a user interface for software installation; acquiring text information on the user interface; determining whether bundled software exists; and, based upon the determination, extracting the name and amount of bundled software from the text information and prompting the name and the amount of the bundled software. The embodiments may identify bundled software before installing software and avoid starting the bundled software process, having the effect of anti-bundling on the bundled software in advance. By extracting the name of the bundled software, acquiring the amount of bundled software, and prompting the name and amount of the bundled software, a user is able to determine whether to install the bundled software according to his or her requirements, thereby improving the autonomous right of selection of the user in the process of installing software.