Abstract: A method of determining the level of maliciousness of an element using a directed hypergraph to classify the element based on information aggregated from its locally identified close neighbors, queried in a data base such as VirusTotal (VT). A crawling procedure is used starting from elements needing classification and collecting a set of their neighbors forming neighborhoods. These neighbors are then used to classify the elements. The neural network classifier is able to obtain as input an entire neighborhood. The input includes several feature vectors, one for each element in the neighborhood. In addition, a mapping of interconnections can be provided for each group of elements. Finally, a maliciousness level is provided for the elements in question.

Abstract: Systems and methods are provided to measure the similarity between a first and second data sample. The method can include creating a plurality of k-mers from the first data sample, each k-mer having a first length; generating a first vector from the plurality of k-mers by processing the plurality of k-mers with a plurality of hash functions; calculating a similarity level between the first and second data sample by comparing the first vector to a second vector, the second vector representing the second data sample; and based on the similarity level, determining a maliciousness level of the first data sample.

Abstract: Systems and methods are provided to measure the similarity between a first and second data sample. The method can include creating a plurality of k-mers from the first data sample, each k-mer having a first length; generating a first vector from the plurality of k-mers by processing the plurality of k-mers with a plurality of hash functions; calculating a similarity level between the first and second data sample by comparing the first vector to a second vector, the second vector representing the second data sample; and based on the similarity level, determining a maliciousness level of the first data sample.

Abstract: Systems and methods are provided to measure the similarity between a first and second data sample. The method can include creating a plurality of k-mers from the first data sample, each k-mer having a first length; generating a first vector from the plurality of k-mers by processing the plurality of k-mers with a plurality of hash functions; calculating a similarity level between the first and second data sample by comparing the first vector to a second vector, the second vector representing the second data sample; and based on the similarity level, determining a maliciousness level of the first data sample.

Abstract: Systems and methods are provided to determine a maliciousness level of an element using a hypergraph of neighbors. The method can include receiving the element; generating a hypergraph of neighbor target elements found in a database, the hypergraph comprising a set of nodes and a set of edges, wherein the set of nodes represents the neighbor target elements, and the set of edges represents connections between the neighbor target elements; classifying nodes and edges in the hypergraph; generating a maliciousness level profile for the element based on aggregation of nodes and edges in the hypergraph; linking information related to the element with the maliciousness level profile for the element; and performing an action based on a type of the element.

Abstract: A method of determining the level of maliciousness of an element using a directed hypergraph to classify the element based on information aggregated from its locally identified close neighbors, queried in a data base such as VirusTotal (VT). A crawling procedure is used starting from elements needing classification and collecting a set of their neighbors forming neighborhoods. These neighbors are then used to classify the elements. The neural network classifier is able to obtain as input an entire neighborhood. The input includes several feature vectors, one for each element in the neighborhood. In addition, a mapping of interconnections can be provided for each group of elements. Finally, a maliciousness level is provided for the elements in question.

Abstract: A system, method, and computer program product are provided for automatic database validation associated with a software test. In use, an indication that a user is beginning a software test that utilizes one or more databases is received. A first configuration snapshot of the one or more databases is recorded in response to receiving the indication that the user is beginning the software test, prior to the user beginning the software test. Additionally, an indication that the user has finished the software test is received. A second configuration snapshot of the one or more databases is recorded in response to receiving the indication that the user has finished the software test. The first configuration snapshot of the one or more databases is automatically compared to the second configuration snapshot of the one or more databases.

Abstract: Systems and method for generating contact suggestions are provided in which one or more suggested contacts are identified from a set of contacts associated with a user. This includes identifying in historical communications in a user account associated with the user, one or more groups of contacts. Scores are generated for contacts in the identified groups of contacts, including generating a contact score for a respective contact by accumulating score contributions for a plurality of the identified groups of contacts that include the respective contact. One or more suggested contacts are identified in accordance with the generated scores. A contact suggestion is sent based on the suggested contacts for display to the user. The contact suggestion includes a suggested contact with a generated score that is above a predefined threshold.

Abstract: Methods, systems, and apparatus, including computer programs for identifying, using historical interactions associated with a first user, contact groups, where the first user is associated with each contact group, are provided. A score, with respect to a second user, is calculated for each contact group based on an amount of interaction between the second user and the respective contact group, thereby deriving a plurality of scores. A first contact group is determined. The first contact group has a first score in the plurality of scores that satisfies a predetermined threshold. A contact group suggestion is generated, responsive to the determining, that comprises an invitation to add the second user to the first contact group. The first user is notified of the contact group suggestion.

Abstract: A system, method, and computer program product are provided for centralized guided testing. In use, at least one software testing project is identified. Additionally, data associated with the at least one software testing project is accessed from at least one of a plurality of knowledge repositories that are capable of being dynamically and constantly updated, the plurality of knowledge repositories including: at least one first repository including official testing methodology associated with a plurality of testing processes; at least one second repository including test project management information; at least one third repository including test knowledge information provided by users; and at least one fourth repository including historical testing project information and ongoing testing project information. Further, the data associated with the at least one software testing project is presented utilizing at least one user interface.

Abstract: Systems and method for generating contact suggestions are provided in which one or more suggested contacts are identified from a set of contacts associated with a user. This includes identifying in historical communications in a user account associated with the user, one or more groups of contacts. Scores are generated for contacts in the identified groups of contacts, including generating a contact score for a respective contact by accumulating score contributions for a plurality of the identified groups of contacts that include the respective contact. One or more suggested contacts are identified in accordance with the generated scores. A contact suggestion is sent based on the suggested contacts for display to the user. The contact suggestion includes a suggested contact with a generated score that is above a predefined threshold.

Abstract: In some implementations, a method includes, at a computing device, identifying a first recipient of a draft electronic communication prepared by a user. A is score is obtained for a second recipient using respective messages in a plurality of historical messages in a user account associated with the user. The second recipient is a sender or receiver of the respective messages. There is suggested to a user, second recipient for the draft electronic communication in accordance with a condition that both the first recipient and the second recipient shared a single electronic communication and the score for the second recipient satisfies a predefined score threshold. The single electronic communication was communicated at a time prior to identifying the first recipient.

Abstract: Systems and methods for generating contact suggestions are provided. In some implementations, a method includes, at a computing device, identifying a first recipient of a draft electronic communication; and suggesting, to a user, a second recipient for the draft electronic communication in accordance with a condition that both the first recipient and the second recipient shared a single electronic communication. The single electronic communication was communicated at a time prior to identifying the first recipient. In some implementations, the method optionally includes, suggesting, to the user, a removal of a third recipient of the draft electronic communication. In other implementations, the method optionally includes, suggesting, to the user, a replacement of a fourth recipient of the draft electronic communication.

Abstract: A computer system having one or more processors and memory receives seed data comprising contacts specified for a draft communication, selects at least a subset of the seed data as a seed set of contacts, and identifies one or more suggested contacts based on the seed set. Identifying the suggested contacts includes: identifying in historical communications in a user account, groups of contacts that include one or more of the contacts in the seed set; generating scores for contacts in the identified groups of contacts, including generating a contact score for a respective contact by accumulating score contributions for a plurality of the identified groups of contacts that include the respective contact; and identifying the one or more suggested contacts in accordance with the generated scores. The computer system sends a contact suggestion based on the suggested contacts for display in conjunction with the draft communication.

Abstract: Methods, systems, and apparatus, including computer programs for identifying, using historical interactions associated with a first user, contact groups, where the first user is associated with each contact group, are provided. A score, with respect to a second user, is calculated for each contact group based on an amount of interaction between the second user and the respective contact group, thereby deriving a plurality of scores. A first contact group is determined. The first contact group has a first score in the plurality of scores that satisfies a predetermined threshold. A contact group suggestion is generated, responsive to the determining, that comprises an invitation to add the second user to the first contact group. The first user is notified of the contact group suggestion.