Abstract: A random password policy for a specific user associated with an entity is generated based on a global password requirement. A new password created by the specific user based on the generated random password policy is identified. That the new password complies with a set of requirements specified by the generated random password policy is confirmed.

Abstract: A random password policy for a specific user associated with an entity is generated based on a global password requirement. A new password created by the specific user based on the generated random password policy is identified. That the new password complies with a set of requirements specified by the generated random password policy is confirmed.

Abstract: A random password policy for a specific user associated with an entity is generated based on a global password requirement. A new password created by the specific user based on the generated random password policy is identified. That the new password complies with a set of requirements specified by the generated random password policy is confirmed.

Abstract: Disclosed is a computer-implemented method for analyzing server for security vulnerabilities. The method includes selecting a first server from a plurality of servers, wherein the first sever includes a plurality of accounts. The method includes identifying, by a password vulnerability scanner, weak accounts in the plurality of accounts including a first weak account. The method includes determining, by a user risk engine, a user risk score for a user associated with the weak account. The method includes determining, by a server risk engine, a server risk score for the first server, wherein the server risk score is based on a set of server factors and a set of data factors. The method includes generating, by a smart risk scorer, an overall risk score for the first server. The method includes categorizing, based on the overall risk score of the first sever, a risk level for the first server.

Abstract: Embodiments are disclosed for preventing network attacks. The techniques include generating a usage profile for a computing device that accesses a network. The techniques also include determining a plurality of actual use real-time indicators for a network connection on the network. The techniques further include determining a plurality of expected use real-time indicators for the network connection. Additionally, the techniques include calculating a risk assessment value for the network connection based on the actual use real-time indicators and the expected use real-time indicators. Further, the techniques include performing a security action for the network connection based on the calculated risk assessment value.

Abstract: Disclosed is a computer-implemented method for analyzing server for security vulnerabilities. The method includes selecting a first server from a plurality of servers, wherein the first sever includes a plurality of accounts. The method includes identifying, by a password vulnerability scanner, weak accounts in the plurality of accounts including a first weak account. The method includes determining, by a user risk engine, a user risk score for a user associated with the weak account. The method includes determining, by a server risk engine, a server risk score for the first server, wherein the server risk score is based on a set of server factors and a set of data factors. The method includes generating, by a smart risk scorer, an overall risk score for the first server. The method includes categorizing, based on the overall risk score of the first sever, a risk level for the first server.

Abstract: Aspects of the present disclosure relate to identifying a driving mode of an autonomous vehicle. A driving mode of an autonomous vehicle is determined by one or more processing circuits of the autonomous vehicle, the driving mode representing an amount of autonomy of the autonomous vehicle at a particular time. A request for the driving mode of the autonomous vehicle is received from a requesting device. The driving mode is then transmitted to the requesting device.

Abstract: Embodiments are disclosed for preventing network attacks. The techniques include generating a usage profile for a computing device that accesses a network. The techniques also include determining a plurality of actual use real-time indicators for a network connection on the network. The techniques further include determining a plurality of expected use real-time indicators for the network connection. Additionally, the techniques include calculating a risk assessment value for the network connection based on the actual use real-time indicators and the expected use real-time indicators. Further, the techniques include performing a security action for the network connection based on the calculated risk assessment value.

Abstract: Aspects of the present disclosure relate to identifying a driving mode of an autonomous vehicle. A driving mode of an autonomous vehicle is determined by one or more processing circuits of the autonomous vehicle, the driving mode representing an amount of autonomy of the autonomous vehicle at a particular time. A request for the driving mode of the autonomous vehicle is received from a requesting device. The driving mode is then transmitted to the requesting device.