Abstract: Techniques for protecting against unauthorized technique support calls are disclosed. In one embodiment, the techniques may be realized as a system for protecting against unauthorized technique support calls including one or more computer processors. The one or more computer processors may be configured to register a client security application installed on a client device. The client security application may be associated with a mobile device. The client device may be separate from the mobile device. The one or more computer processors may further be configured to receive a notification to start monitoring the client device. The one or more computer processors may further be configured to monitor activities of the client device. The one or more computer processors may further be configured to alert a user of the client device for security risks associated with the activities.

Abstract: The disclosed computer-implemented method for detecting illegitimate voice calls may include (1) identifying an incoming voice call, (2) processing the incoming voice call in real time by (a) segmenting the incoming voice call into progressively produced call segments and, (b) for each new segment as the progressively produced call segments are produced, (A) extracting a set of features from the new segment and (B) feeding, as input into a neural network, the set of features and an output from the neural network generated based on a preceding segment of the incoming voice call, thereby generating a new output representing the current likelihood that the incoming voice call is illegitimate, (3) determining that the likelihood that the incoming voice call is illegitimate is above a predetermined threshold, and (4) performing a security action during the incoming voice call. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Locally securing sensitive data stored on a mobile phone. In one embodiment, a computer-implemented method for locally securing sensitive data stored on a mobile phone may be performed, at least in part, by a computing device including at least one processor. The method may include operating a mobile phone in an owner mode. The method may also include locally detecting, by the mobile phone, an insecurity event on the mobile phone. The method may further include, in response to locally detecting the insecurity event on the mobile phone, automatically switching, by the mobile phone, to operating the mobile phone in a guest mode, with the automatic switching to operating the mobile phone in the guest mode resulting in automatically securing sensitive data stored locally on the mobile phone.

Abstract: A computer-implemented method for identifying variants of samples based on similarity analysis may include (1) collecting, from security agents on endpoint computing systems, metadata attributes that describe samples identified by the security agents over an initial period of time, (2) collecting metadata attributes that describe a current sample identified after the initial period of time, (3) comparing at least two of the metadata attributes that describe the current sample with corresponding metadata attributes of the samples identified over the initial period of time, (4) designating the current sample as related to another sample from the samples identified over the initial period of time based on the comparison of the two metadata attributes, and (5) performing a security action to protect a user from malware based on the designation of the current sample as related to the other sample. Various other methods, systems, and computer-readable media are also disclosed.