Organization attack surface management
A system for sanitizing an organization's network against attacker breach, including a data collector, gathering information about network hosts, an analyzer constructing the organization's network topology, a machine learning engine categorizing the hosts into organizational units and identifying key assets of the organization, a security rules engine mapping real-time data, and inferring security rules that prescribe on which specific hosts which specific credentials are permitted to be stored, and a user interface including an analyst dashboard enabling an analyst to visualize in real-time activities within the organizations' network, to automatically infer security rules for the network, to activate the security rules in the network, and to eliminate potential attack vectors for which the activated security rules are violated, and an attacker view visualizing the organization's network, identifying security rule violations across the organization's network, and enabling removal of credential-based security rule violations by use of actions.
1. A system for sanitizing an organization's network against attacker breach, comprising:
a data collector, gathering information about network hosts, including endpoint computers and server computers within an organization's network, and about credentials stored on these computers, the credentials being used to grant users access to hosts;
an analyzer applying graph theory to construct the organization's network topology and connections between hosts, and to depict hosts that have credentials stored therein;
a machine learning engine categorizing the hosts into users, groups and organizational units, and identifying key assets of the organization; and
a security rules engine mapping real-time data collected from said data collector, analyzed by said analyzer and categorized by said machine learning engine, automatically generating security rules for the organization's network, that prescribe on which specific hosts which specific credentials are permitted to be stored so as to prevent exploitation of the specific credentials in case of an attacker breach, and simulating the generated security rules for existing network data offline.
2. The system of claim 1 wherein said security rules engine implements production versions of the generated security rules.
3. The system of claim 1 further comprising a notification engine generating a report of all changes applied by security rule implementation, and all security rule violations that have been eliminated.
4. The system of claim 1 further comprising an analyst dashboard visualizing in real-time activities within the organizations' network.
5. The system of claim 4 wherein said analyst dashboard automatically generates security rules for the network.
6. The system of claim 5 wherein said analyst dashboard activates the generated security rules in the network.
7. The system of claim 6 wherein said analyst dashboard eliminates potential attack vectors for which the activated security rules are violated.
8. The system of claim 1 further comprising an attacker view visualizing the endpoints and the servers within the organization's network.
9. The system of claim 8 wherein said attacker view represents connections by protocol and by credentials within the network.
10. The system of claim 9 wherein said attacker view visualizes real and deceptive connections within the network.
11. The system of claim 10 wherein said attacker view identifies security rule violations across the organization's network.
12. The system of claim 11 wherein said attacker view enables removal of credential-based security rule violations by use of actions.
13. A method for sanitizing an organization's network against attacker breach, comprising:
gathering information about network hosts, including endpoint computers and server computers within an organization's network, and about credentials stored on these computers, the credentials being used to grant users access to hosts;
applying graph theory to construct the organization's network topology and connections between hosts, and to depict hosts that have credentials stored therein;
categorizing the hosts into users, groups and organizational units, and identifying key assets of the organization;
mapping real-time data collected from said gathering information, analyzed by said applying graph theory and categorized by said categorizing;
automatically generating security rules for the organization's network, that prescribe on which specific hosts which specific credentials are permitted to be stored so as to prevent exploitation of the specific credentials in case of an attacker breach; and
simulating the generated security rules for existing network data offline.
14. The method of claim 13 further comprising implementing production versions of the generated security rules.
15. The method of claim 13 further comprising generating a report of all changes applied by security rule implementation, and all security rule violations that have been eliminated.
16. The method of claim 13 further comprising:
visualizing in real-time activities within the organizations' network;
automatically inferring security rules for the network;
activating the security rules in the network; and
eliminating potential attack vectors for which the activated security rules are violated.
17. The method of claim 13 further comprising:
visualizing the endpoints and the servers within the organization's network;
representing connections by protocol and by credentials within the network; and
visualizing real and deceptive connections within the network.
18. The method of claim 13 further comprising:
identifying security rule violations across the organization's network; and
enabling removal of credential-based security rule violations by use of actions.