Abstract: Techniques for improving packaging systems are described. In an example, a computer system receives item data from a workstation. The item data includes a description of an item. The workstation is configured to facilitate packaging of the item. Based at least in part on an input to the predictive model, the computer system generates a package decision indicating a package type associated with the packaging of the item. The input is based at least in part on the item data. The predictive model is trained based at least in part on damage data associated with packaging. The computer system sends the package decision to the workstation.

Abstract: An indication to perform a permissions policy search may be received by an interface of an identity management service. A context may be determined associated with the permissions policy search. A plurality of weights for a plurality of permissions policies may be calculated based on the context. An order for display of the plurality of permissions policies may be determined based on the plurality of weights. The plurality of permissions policies may be presented, in a display area within the interface, in the order that is based on the plurality of weights. A selection of a first permissions policy from the plurality of permissions policies may be received by the interface. The first permissions policy may be attached to a first identity based at least in part on the selection of the first permissions policy.

Abstract: Context information may be obtained associated with an error corresponding to an operation. The operation may be defined in a programmatic interface, such as a command line interface. The context information may include identity information regarding an identity that operates the programmatic interface, operation information regarding the operation, and result information regarding a result of the operation. A selected resolution interface type for a resolution interface to assist in resolving the error may be selected based at least in part on the context information. The selected resolution interface type may be a permissions search interface. Scenario-based contents of the resolution interface, such as search terms, may be determined, based at least in part on the context information. The resolution interface may be automatically launched. Input for resolving the error, such as selection of an appropriate permissions policy for attachment to the identity, may be received via the resolution interface.

Abstract: A plurality of cross account resource accessibility instances may be identified in which a plurality of resources are accessible by a plurality of identities that are external to an account that controls the plurality of resources. A plurality of estimated occurrence probabilities of a plurality of links between the plurality of resources and the plurality of identities may be determined. A plurality of estimated removal probabilities of the plurality of cross account resource accessibility instances may be determined based at least in part on the plurality of estimated occurrence probabilities. A plurality of weights for the plurality of cross account resource accessibility instances may be generated based at least in part on the plurality of estimated removal probabilities. A prioritized display of a plurality of indications of the plurality of cross account resource accessibility instances may be provided based at least in part on the plurality of weights.

Abstract: A first permission allocated to a first identity may be identified. Permission usage information may be analyzed. The permission usage information may include permission usage history information and permission usage pattern data. An estimated probability of a future usage of the first permission by the first identity may be forecasted based, at least in part, on the permission usage information. A first recommendation relating to allocation of the first permission to the first identity may be determined based, at least in part, on the estimated probability. The first recommendation may be a recommendation for the first identity to retain the first permission or a recommendation to deallocate the first permission from the first identity. An indication of the first recommendation may be provided to a user.

Abstract: Identity management recommendations for use of existing policies are described herein. An available policy set of existing policies that are available to an identity may be determined. Selected permissions associated with permission-usage by the identity may be determined. It may be determined whether the available policy set includes one or more matching policy subsets that cover all the selected permissions without allowing any additional permissions. When the available policy set includes the one or more matching policy subsets, a first recommendation may be provided to attach, to the identity, at least one matching policy subset of the one or more matching policy subsets. When the available policy set does not include the one or more matching policy subsets, a second recommendation may be provided to attach, to the identity, one or more alternative policies.

Abstract: A machine learning model may generate a first recommendation relating to allocation of a first permission to an identity, wherein the first recommendation is a recommendation for the identity to retain the first permission or a recommendation to deallocate the first permission from the identity. A first indication of the first recommendation may be provided to one or more users. The machine learning model may, based on speculative execution, determine a first condition that, when attributed to the identity, causes changing of the first recommendation to a second recommendation relating to the allocation of the first permission to the identity, wherein the second recommendation differs from the first recommendation. A second indication may be provided, to the one or more users, that attribution of the first condition to the entity causes the changing of the first recommendation to the second recommendation.

Abstract: A first permission allocated to a first identity may be identified. Permission usage information may be analyzed. The permission usage information may include permission usage history information and permission usage pattern data. An estimated probability of a future usage of the first permission by the first identity may be forecasted based, at least in part, on the permission usage information. A first recommendation relating to allocation of the first permission to the first identity may be determined based, at least in part, on the estimated probability. The first recommendation may be a recommendation for the first identity to retain the first permission or a recommendation to deallocate the first permission from the first identity. An indication of the first recommendation may be provided to a user.

Abstract: Access management policies may be generated from example requests. An access management policy may be received. One or more example requests that have expected results when evaluated with respect to the access management policy may be received. Updates to the access management policy may be determined that cause the expected results to occur when a new version of the access management policy based on the updates is enforced. The new version of the access management policy may be generated based on the updates.

Abstract: In one respect, there is provided a system for classifying malware. The system may include a data processor and a memory. The memory may include program code that provides operations when executed by the processor. The operations may include: providing, to a display, contextual information associated with a file to at least enable a classification of the file, when a malware classifier is unable to classify the file; receiving, in response to the providing of the contextual information, the classification of the file; and updating, based at least on the received classification of the file, the malware classifier to enable the malware classifier to classify the file. Methods and articles of manufacture, including computer program products, are also provided.

Abstract: In one respect, there is provided a system for classifying malware. The system may include a data processor and a memory. The memory may include program code that provides operations when executed by the processor. The operations may include: providing, to a display, contextual information associated with a file to at least enable a classification of the file, when a malware classifier is unable to classify the file; receiving, in response to the providing of the contextual information, the classification of the file; and updating, based at least on the received classification of the file, the malware classifier to enable the malware classifier to classify the file. Methods and articles of manufacture, including computer program products, are also provided.

Abstract: A user can designate a dataset and one or more n-grams in a graphical user interface displayed by a client computing device (“the client”). The client can send the designations to a server computing device (“the server”). The server can execute a query over the dataset based on the n-grams, and return statistics indicating occurrences of the n-grams in the dataset. The client can generate a graphical representation corresponding to the statistics. The user can select a portion of the graphical representation, which the client sends to the server. The server can respond with excerpts of documents corresponding to the selected portion and other n-grams within the documents. The client can then display a list of the excerpts and a list of other n-grams. The user can then perform further actions on the lists such as viewing the underlying documents or adding n-grams to the search query.

Abstract: A user can designate a dataset and one or more n-grams in a graphical user interface displayed by a client computing device (“the client”). The client can send the designations to a server computing device (“the server”). The server can execute a query over the dataset based on the n-grams, and return statistics indicating occurrences of the n-grams in the dataset. The client can generate a graphical representation corresponding to the statistics. The user can select a portion of the graphical representation, which the client sends to the server. The server can respond with excerpts of documents corresponding to the selected portion and other n-grams within the documents. The client can then display a list of the excerpts and a list of other n-grams. The user can then perform further actions on the lists such as viewing the underlying documents or adding n-grams to the search query.