The contents of the following of applicant's US patent applications are hereby incorporated herein in their entireties.
The present invention relates to computer security, and in particular to preventing attackers from harvesting credentials from an enterprise network.
Reference is made to
Access to endpoint computers 110 and databases 120 in network 100 may optionally be governed by an access governor 150, such as a directory service, that authorizes users to access endpoint computers 110 and databases 120 based on “credentials”. Access governor 150 may be a name directory, such as ACTIVE DIRECTORY® developed by Microsoft Corporation of Redmond, Wash., for WINDOWS® environments. Background information about ACTIVE DIRECTORY® is available at Wikipedia. Other access governors for WINDOWS and non-WINDOWS environments, include inter alia Lightweight Directory Access Protocol (LDAP), Remote Authentication Dial-In User Service (RADIUS), and Apple Filing Protocol (AFP), formerly APPLETALK®, developed by Apple Inc. of Cupertino, Calif. Background information about LDAP, RADIUS and AFP is available at Wikipedia.
Access governor 150 may be one or more local machine access controllers. Access governor 150 may be one or more authorization servers, such as a database server or an application server.
In lieu of access governor 150, the endpoints and/or servers of network 100 determine their local access rights.
Credentials for accessing endpoint computers 110 and databases 120 include inter alia server account credentials such as <address> <username> <password> for an FTP server, an SQL server, or an SSH server. Credentials for accessing endpoint computers 110 and databases 120 also include user login credentials <username> <password>, or <username> <ticket>, where “ticket” is an authentication ticket, such as a ticket for the Kerberos authentication protocol or NTLM hash used by Microsoft Corp., or login credentials via certificates or via another implementation used today or in the future. Background information about the Kerberos protocol and the LM hash is available at Wikipedia.
Access governor 150 may maintain a directory of endpoint computers 110, databases 120 and their users. Access governor 150 authorizes users and computers, assigns and enforces security policies, and installs and updates software. When a user logs into an endpoint computer 110, access governor 150 checks the submitted password, and determines if the user is an administrator (admin), a normal user (user) or other user type.
Endpoint computers 110 may run a local or remote security service, which is an operating system process that verifies users logging in to computers and other single sign-on systems and other credential storage systems.
Network 100 may include a security information and event management (SIEM) server 160, which provides real-time analysis of security alerts generated by network hardware and applications. Background information about SIEM is available at Wikipedia.
Network 100 may include a domain name system (DNS) server 170, or such other name service system, for translating domain names to IP addresses. Background information about DNS is available at Wikipedia.
Network 100 may include a firewall 180 located within a demilitarized zone (DMZ), which is a gateway between organization network 100 and external internet 10. Firewall 180 controls incoming and outgoing traffic for network 100. Background information about firewalls and DMZ is available at Wikipedia.
One of the most prominent threats that organizations face is a targeted attack; i.e., an individual or group of individuals that attacks the organization for a specific purpose, such as leaking data from the organization, modifying data and systems, and sabotaging data and systems.
Targeted attacks are carried out in multiple stages, typically including inter alia reconnaissance, penetration, lateral movement and payload. Lateral movement involves establishing a foothold within the organization and expanding that foothold to additional systems within the organization.
In order to carry out the lateral movement stage, an attacker, whether a human being who is operating tools within the organization's network, or a tool with “learning” capabilities, learns information about the environment it is operating in, such as network topology, organization structure, and implemented security solutions, and then operates in accordance with that data. One method to defend against such attacks is to plant misleading information/decoys/bait with the aim that the attacker learns of their existence and consumes those bait resources, which are monitored so as to notify an administrator of malicious activity. In order to monitor usage of deceptive information, trap servers, referred to as “honeypots”, are deployed in the organization. Background information about honeypots is available at Wikipedia.
Attackers generally harvest credentials from endpoint computers 110 of network 100, and then perform lateral movements within network 100. Conventional honeypot solutions have several drawbacks. Specifically, deceptive data planted in network resources is static, and may thus be visible and confusing to legitimate users. Conventional deceptive data may be triggered by legitimate user activity, thus triggering false positive events. Conventional deceptive data has large fingerprints.
Embodiments of the present invention overcome drawbacks of conventional honeypot solutions by generating deceptive data that is only visible to an attacker. As such, legitimate user activity is unaffected by the deceptive data. Furthermore, there is a very high likelihood that triggering of deceptive data is done by an attacker, thus minimizing false positives.
Embodiments of the present invention install deceptive agents on endpoint computers of an enterprise network. The deceptive agents hook resources of the endpoint computers that contain valuable credentials, such as registries and file systems, and respond to attempts, by a malicious process being run by an attacker on an endpoint computer, to read from these resources by generating and returning deceptive content. The deceptive content is inter alia IP addresses, hostnames and user credentials that point to trap servers.
The deceptive agents may install hooks on network adaptors of endpoint computers, to monitor outgoing remote calls.
Alternative embodiments of the present invention install deceptive agents on remote servers of the enterprise. The deceptive agents monitor inbound requests to the remote servers and authenticate the requests to ensure that they originate from legitimate client processes.
There is thus provided in accordance with an embodiment of the present invention a system for deceiving an attacker who harvests credentials within an enterprise network, including a management server deploying a deceptive agent on an endpoint computer of the enterprise network, the deceptive agent including a hook manager creating system hooks on resources in the endpoint computer that holds valuable credentials, which would be desired by attackers, and a deceptive content provider, generating deceptive content and returning the deceptive content to a malicious process run by an attacker on the endpoint computer, the malicious process making a read request directed to a resource in the endpoint computer that holds valuable credentials, thus making it appear to the attacker that a response is coming from the resource whereas in fact the response is coming from the deceptive agent, when the hook manager hooks the read request.
There is additionally provided in accordance with an embodiment of the present invention a method for deceiving an attacker who is harvesting credentials within an enterprise network, including deploying, by a management server, a deceptive agent on an endpoint computer of an enterprise network, creating, by the deceptive agent, system hooks on resources in the endpoint computer that hold valuable credentials, which would be desired by attackers, and in response to hooking a read request, by a malicious process being run by an attacker on the endpoint computer, directed to a resource in the endpoint computer that holds valuable credentials, generate, by the deceptive agent, deceptive content and respond to the read request by returning the deceptive content to the malicious process, thus making it appear to the attacker that the response is coming from the resource whereas in fact the response is coming from the deceptive agent.
There is further provided in accordance with an embodiment of the present invention a method for deceiving an attacker who is harvesting credentials within an enterprise network, including deploying, by a management server, a deceptive agent on a remote server of an enterprise network, wherein the deceptive agent listens to inbound requests for the remote server and authenticates the inbound requests as coming from a legitimate client computer of the enterprise network, and in response to detecting a remote call to a service of the remote server from a malicious process being run by an attacker on a client computer of the enterprise network, generate, by the deceptive agent, deceptive content and respond to the remote call by returning the deceptive content to the malicious process, thus making it appear to the attacker that the response is coming from the service in the remote server whereas in fact the response is coming from the deceptive agent.
The present invention will be more fully understood and appreciated from the following detailed description, taken in conjunction with the drawings in which:
For reference to the figures, the following index of elements and their numerals is provided. Similarly numbered elements represent elements of the same type, but they need not be identical elements.
Elements numbered in the 1000's are operations of flow charts.
Embodiments of the present invention overcome drawbacks of conventional honeypot solutions by generating deceptive data that is only visible to an attacker. As such, legitimate user activity is unaffected by the deceptive data. Furthermore, there is a very high likelihood that triggering of deceptive data is done by an attacker, thus minimizing false positives.
Inter alia, embodiments of the present invention address two cases in which attackers attempt to harvest data; namely, (1) locally via files, memory and registry, and (2) remotely from other servers including Active Directory, from authentication servers, and from cloud providers such as Amazon Web Services. Some embodiments of the present invention address case (1) by installing agents in network endpoint computers that hook to local resources (
It will be appreciated by those skilled in the art that embodiments of the present invention may be combined to address both cases (1) and (2).
Reference is made to
Management server 210 includes a policy manager 211. Policy manager 211 defines a decoy and response policy. The decoy and response policy defines different decoy types, different decoy combinations, response procedures, notification services, and assignments of policies to specific network nodes, network users, groups of nodes or users or both. Once policies are defined, they are stored in policy database 230 with the defined assignments.
Management server 210 also includes a forensic application 212, which is a real-time application that is transmitted to an endpoint computer 110 in the network, when a deception is accessed by that endpoint computer 110, thus indicating that that endpoint computer 110 has been breached by an attacker. When forensic application 212 is launched on the endpoint computer 110, it identifies a process running within that endpoint computer 110 that accessed the deception, logs the activities performed by the thus-identified process in a forensic report, and transmits the forensic report to management server 210.
Management server 210 also includes a deployer 213 that deploys agents A in endpoint computers and in remote servers, as described hereinbelow.
Each trap server 240 includes incident manager 241, which alerts management system 210 that an attacker is accessing the trap server via an endpoint computer 110 of network 200, and causes management server 210 to send forensic application 212 to the endpoint computer 110 that is accessing trap server 240. In an alternative embodiment of the present invention, trap server 240 may store forensic application 212, in which case trap server 240 may transmit forensic application 212 directly to the endpoint computer 110 that is accessing trap server 240. In another alternative embodiment of the present invention, management server 210 or trap server 240 may transmit forensic application 212 to a destination computer other than the endpoint computer 110 that is accessing trap server 240, for collections of forensics remotely from the endpoint computer that is accessing trap server 240.
Reference is made to
Reference is made to
At operation 1020 each local agent creates system hooks at network resources that hold desired credentials, also referred to as “crown jewels”. The hooks are created via driver and process hooks. Reference is made to
At operation 1030 a determination is made, for each endpoint computer 110, whether protection for remote servers is desired. If the determination is affirmative, then at operation 1040 the local agent for endpoint computer 110 creates a hook on the endpoint computer's network adapter. Using the hook, the local agent sees each outbound request. Reference is made to
At operation 1050 in response to a malicious process attempting to read from a network resource that holds crown jewels, the local agent detects the attempted read and returns deceptive content. Reference is made to
Identification of a malicious process by the local agent at operation 1050 may be performed by whitelisting authorized processes.
Reference is made to
At operation 1120, in response to a malicious process making a remote call to a remote service, the agent generates and returns deceptive content, instead of actual content. Reference is made to
In the foregoing specification, the invention has been described with reference to specific exemplary embodiments thereof. It will, however, be evident that various modifications and changes may be made to the specific exemplary embodiments without departing from the broader spirit and scope of the invention. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense.
Number | Name | Date | Kind |
---|---|---|---|
6363489 | Comay et al. | Mar 2002 | B1 |
6618709 | Sneeringer | Sep 2003 | B1 |
7065657 | Moran | Jun 2006 | B1 |
7089589 | Chefalas et al. | Aug 2006 | B2 |
7093291 | Bailey | Aug 2006 | B2 |
7516227 | Cohen | Apr 2009 | B2 |
7574741 | Aviani et al. | Aug 2009 | B2 |
7636944 | Raikar | Dec 2009 | B2 |
7665134 | Hernacki et al. | Feb 2010 | B1 |
7694339 | Blake et al. | Apr 2010 | B2 |
7725937 | Levy | May 2010 | B1 |
7752664 | Satish et al. | Jul 2010 | B1 |
7945953 | Salinas et al. | May 2011 | B1 |
8015284 | Isenberg et al. | Sep 2011 | B1 |
8181249 | Chow et al. | May 2012 | B2 |
8181250 | Rafalovich | May 2012 | B2 |
8250654 | Kennedy et al. | Aug 2012 | B1 |
8375447 | Amoroso et al. | Feb 2013 | B2 |
8499348 | Rubin | Jul 2013 | B1 |
8528091 | Bowen et al. | Sep 2013 | B2 |
8549642 | Lee | Oct 2013 | B2 |
8549643 | Shou | Oct 2013 | B1 |
8719938 | Chasko et al. | May 2014 | B2 |
8739281 | Wang et al. | May 2014 | B2 |
8739284 | Gardner | May 2014 | B1 |
8769684 | Stolfo et al. | Jul 2014 | B2 |
8819825 | Keromytis et al. | Aug 2014 | B2 |
8826400 | Amaya Calvo | Sep 2014 | B2 |
8856928 | Rivner et al. | Oct 2014 | B1 |
8881288 | Levy et al. | Nov 2014 | B1 |
8925080 | Hebert | Dec 2014 | B2 |
9009829 | Stolfo et al. | Apr 2015 | B2 |
9043905 | Allen et al. | May 2015 | B1 |
9124622 | Falkowitz et al. | Sep 2015 | B1 |
9152808 | Ramalingam et al. | Oct 2015 | B1 |
9240976 | Murchison | Jan 2016 | B1 |
9325728 | Kennedy et al. | Apr 2016 | B1 |
9356942 | Joffe | May 2016 | B1 |
9386030 | Vashist et al. | Jul 2016 | B2 |
9495188 | Ettema et al. | Nov 2016 | B1 |
20020066034 | Schlossberg et al. | May 2002 | A1 |
20020194489 | Almogy et al. | Dec 2002 | A1 |
20030084349 | Friedrichs et al. | May 2003 | A1 |
20030110396 | Lewis et al. | Jun 2003 | A1 |
20030145224 | Bailey | Jul 2003 | A1 |
20040088581 | Brawn et al. | May 2004 | A1 |
20040128543 | Blake et al. | Jul 2004 | A1 |
20040148521 | Cohen et al. | Jul 2004 | A1 |
20040160903 | Gai et al. | Aug 2004 | A1 |
20040172557 | Nakae et al. | Sep 2004 | A1 |
20040255155 | Stading | Dec 2004 | A1 |
20050114711 | Hesselink et al. | May 2005 | A1 |
20050132206 | Palliyil et al. | Jun 2005 | A1 |
20050149480 | Deshpande | Jul 2005 | A1 |
20050235360 | Pearson | Oct 2005 | A1 |
20060010493 | Piesco et al. | Jan 2006 | A1 |
20060041761 | Neumann et al. | Feb 2006 | A1 |
20060069697 | Shraim et al. | Mar 2006 | A1 |
20060101516 | Sudaharan et al. | May 2006 | A1 |
20060161982 | Chari et al. | Jul 2006 | A1 |
20060224677 | Ishikawa et al. | Oct 2006 | A1 |
20060242701 | Black et al. | Oct 2006 | A1 |
20070028301 | Shull et al. | Feb 2007 | A1 |
20070039038 | Goodman | Feb 2007 | A1 |
20070157315 | Moran | Jul 2007 | A1 |
20070192853 | Shraim et al. | Aug 2007 | A1 |
20070226796 | Gilbert et al. | Sep 2007 | A1 |
20070299777 | Shraim et al. | Dec 2007 | A1 |
20080016570 | Capalik | Jan 2008 | A1 |
20080086773 | Tuvell et al. | Apr 2008 | A1 |
20080155693 | Mikan et al. | Jun 2008 | A1 |
20090019547 | Palliyil et al. | Jan 2009 | A1 |
20090144827 | Peinado et al. | Jun 2009 | A1 |
20090222920 | Chow et al. | Sep 2009 | A1 |
20090241173 | Troyansky | Sep 2009 | A1 |
20090241191 | Keromytis et al. | Sep 2009 | A1 |
20090241196 | Troyansky et al. | Sep 2009 | A1 |
20090328216 | Rafalovich et al. | Dec 2009 | A1 |
20100058456 | Jajodia et al. | Mar 2010 | A1 |
20100071051 | Choyi et al. | Mar 2010 | A1 |
20100077483 | Stolfo et al. | Mar 2010 | A1 |
20100082513 | Liu | Apr 2010 | A1 |
20100251369 | Grant | Sep 2010 | A1 |
20100269175 | Stolfo et al. | Oct 2010 | A1 |
20110016527 | Yanovsky et al. | Jan 2011 | A1 |
20110154494 | Sundaram et al. | Jun 2011 | A1 |
20110167494 | Bowen et al. | Jul 2011 | A1 |
20110214182 | Adams et al. | Sep 2011 | A1 |
20110258705 | Vestergaard et al. | Oct 2011 | A1 |
20110302653 | Frantz et al. | Dec 2011 | A1 |
20110307705 | Fielder | Dec 2011 | A1 |
20120005756 | Hoefelmeyer et al. | Jan 2012 | A1 |
20120084866 | Stolfo | Apr 2012 | A1 |
20120167208 | Buford et al. | Jun 2012 | A1 |
20120210388 | Kolishchak | Aug 2012 | A1 |
20120246724 | Sheymov et al. | Sep 2012 | A1 |
20120311703 | Yanovsky et al. | Dec 2012 | A1 |
20130061055 | Schibuk | Mar 2013 | A1 |
20130086691 | Fielder | Apr 2013 | A1 |
20130212644 | Hughes et al. | Aug 2013 | A1 |
20130227697 | Zandani | Aug 2013 | A1 |
20130263226 | Sudia | Oct 2013 | A1 |
20130333040 | Diehl | Dec 2013 | A1 |
20140082730 | Vashist et al. | Mar 2014 | A1 |
20140101724 | Wick et al. | Apr 2014 | A1 |
20140115706 | Silva et al. | Apr 2014 | A1 |
20140201836 | Amsler | Jul 2014 | A1 |
20140208401 | Balakrishnan et al. | Jul 2014 | A1 |
20140237599 | Gertner et al. | Aug 2014 | A1 |
20140259095 | Bryant | Sep 2014 | A1 |
20140298469 | Marion et al. | Oct 2014 | A1 |
20140310770 | Mahaffey | Oct 2014 | A1 |
20140337978 | Keromytis et al. | Nov 2014 | A1 |
20140359708 | Schwartz | Dec 2014 | A1 |
20140359769 | Sabin | Dec 2014 | A1 |
20150007326 | Mooring et al. | Jan 2015 | A1 |
20150013006 | Shulman et al. | Jan 2015 | A1 |
20150047032 | Hannis et al. | Feb 2015 | A1 |
20150074750 | Pearcy et al. | Mar 2015 | A1 |
20150074811 | Capalik | Mar 2015 | A1 |
20150096048 | Zhang et al. | Apr 2015 | A1 |
20150101044 | Martin | Apr 2015 | A1 |
20150128246 | Feghali et al. | May 2015 | A1 |
20150156211 | Chi Tin et al. | Jun 2015 | A1 |
20150264062 | Hagiwara | Sep 2015 | A1 |
20150326587 | Vissamsetty et al. | Nov 2015 | A1 |
20150326598 | Vasseur et al. | Nov 2015 | A1 |
20160019395 | Ramalingam et al. | Jan 2016 | A1 |
20160080414 | Kolton et al. | Mar 2016 | A1 |
20160212167 | Dotan et al. | Jul 2016 | A1 |
20160261608 | Hu et al. | Sep 2016 | A1 |
20160300227 | Subhedar et al. | Oct 2016 | A1 |
20160308895 | Kotler et al. | Oct 2016 | A1 |
20160323316 | Kolton et al. | Nov 2016 | A1 |
20160373447 | Akiyama et al. | Dec 2016 | A1 |
20170032130 | Joseph Durairaj et al. | Feb 2017 | A1 |
20180176251 | Belikovetsky | Jun 2018 | A1 |
Number | Date | Country |
---|---|---|
2006131124 | Dec 2006 | WO |
2015001969 | Jan 2015 | WO |
2015047555 | Apr 2015 | WO |
Entry |
---|
Wikipedia, Active Directory, https://en.wikipedia.org/wiki/Active_Directory, Jun. 24, 2015. |
Wikpedia, Apple Filing Protocol, https://en.wikipedia.org/wiki/Apple_Filing_Protocol, Aug. 14, 2015. |
Wikipedia, DMZ (computing), https://en.wikipedia.org/wiki/DMZ_(computing), Jun. 17, 2015. |
Wikipedia, Domain Name System, https://en.wikipedia.org/wiki/Domain_Name_System, Jul. 14, 2015. |
Wikipedia, Firewall (computing), https://en.wikipedia.org/wiki/Firewall_(computing), Jul. 14, 2015. |
Wikipedia, Honeypot (computing), https://en.wikipedia.org/wiki/Honeypot_(computing), Jun. 21, 2015. |
Wikipedia, Kerberos (protocol), https://en.wikipedia.org/wiki/Kerberos_(protocol), Jun. 30, 2015. |
Wikipedia, Lightweight Directory Access Protocol, https://en.wikipedia.org/wiki/Lightweight_Directory_Access_Protocol, Aug. 15, 2015. |
Wikipedia, LM hash, https://en.wikipedia.org/wiki/LM_hash, Jun. 8, 2015. |
Wikipedia, RADIUS, https://en.wikipedia.org/wiki/RADIUS, Aug. 16, 2015. |
Wikipedia, Rainbow table, https://en.wikipedia.org/wiki/Rainbow_table, Jul. 14, 2015. |
Wikipedia, Secure Shell, https://en.wikipedia.org/wiki/Honeypot_(computing), Jul. 12, 2015. |
Wikipedia, Security Information and Event Management, https://en.wikipedia.org/wiki/Security_information_and_event_management, Jun. 23, 2015. |
Wikipedia, Tarpit (networking), https://en.wikipedia.org/wiki/Tarpit_(networking), Jul. 3, 2014. |
Mishra et al., Intrusion detection in wireless ad hoc networks, IEEE Wireless Communications, Feb. 2004, pp. 48-60. |
Zhang et al., Intrusion detection techniques for mobile wireless networks, Journal Wireless Networks vol. 9(5), Sep. 2003, pp. 545-556, Kluwer Academic Publishers, the Netherlands. |
U.S. Appl. No. 15/004,904, Office Action, dated May 27, 2016, 16 pages. |
U.S. Appl. No. 15/004,904, Notice of Allowance, dated Oct. 19, 2016, 13 pages. |
U.S. Appl. No. 15/175,048, Notice of Allowance, dated Oct. 13, 2016, 17 pages. |
U.S. Appl. No. 15/175,050, Office Action, dated Aug. 19, 2016, 34 pages. |
U.S. Appl. No. 15/175,050, Office Action, dated Nov. 30, 2016, 31 pages. |
U.S. Appl. No. 15/175,050, Notice of Allowance, dated Mar. 21, 2017, 13 pages. |
U.S. Appl. No. 15/175,052, Office Action, dated Feb. 13, 2017, 19 pages. |
U.S. Appl. No. 15/175,052, Office Action, dated Jun. 6, 2017, 19 pages. |
U.S. Appl. No. 15/175,054, Notice of Allowance, dated Feb. 21, 2017, 13 pages. |
U.S. Appl. No. 15/403,194, Office Action, dated Feb. 28, 2017, 13 pages. |
U.S. Appl. No. 15/403,194, Notice of Allowance, dated Jun. 16, 2017, 9 pages. |
U.S. Appl. No. 15/406,731, Notice of Allowance, dated Apr. 20, 2017. |
PCT Application No. PCT/IL16/50103, International Search Report and Written Opinion, dated May 26, 2016, 9 pages. |
PCT Application No. PCT/IL16/50579, International Search Report and Written Opinion, dated Sep. 30, 2016, 7 pages. |
PCT Application No. PCT/IL16/50581, International Search Report and Written Opinion, dated Nov. 29, 2016, 10 pages. |
PCT Application No. PCT/IL16/50582, International Search Report and Written Opinion, dated Nov. 16, 2016, 11 pages. |
PCT Application No. PCT/IL16/50583, International Search Report and Written Opinion, dated Dec. 8, 2016, 10 pages. |
U.S. Appl. No. 15/175,052, Notice of Allowance, dated Jan. 2, 2018, 9 pages. |
U.S. Appl. No. 15/679,180, Notice of Allowance, dated Mar. 26, 2018, 14 pages. |
U.S. Appl. No. 15/722,351, Office Action, dated Mar. 9, 2018, 17 pages. |
U.S. Appl. No. 15/722,351, Notice of Allowance, dated Aug. 8, 2018, 8 pages. |
U.S. Appl. No. 15/682,577, Notice of Allowance, dated Jun. 14, 2018, 15 pages. |
U.S. Appl. No. 15/641,817, Office Action, dated Jul. 26, 2018, 29 pages. |