IP Library Granted Patent US 12,603,896
Granted Patent B2
US 12,603,896 · App. 17/676,275 · Granted Apr 14, 2026

Agent prevention augmentation based on organizational learning

Inventors: Jonathan Allon (Haifa, IL); Niv Sela (Tel Aviv-Jaffa, IL); Liav Zigelbaum (Herzliya, IL); Guy Pilosof (Shoham, IL); Ori Beck (Tel Aviv-Jaffa, IL)
Assignee: Palo Alto Networks, Inc.
H04L63/1416
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Quick Facts
Patent No.
US 12,603,896
App. No.
17/676,275
Granted
Apr 14, 2026
Kind
B2
Abstract

A method, including collecting, by a security server, reports from multiple computing devices of events belonging to a set of specified event types occurring in execution of software processes on the devices, and collating the reports in the server to extract context information with respect to each of the events. Upon detecting an event occurring in execution of a process on a given device and matching one of the types, a software agent executing on the given device extracts, one or more features from the detected event, and conveys a query with respect to the detected event from the agent to the server. Upon receiving, from the server in response to the query, the context information with respect to the detected event, the agent decides to initiate a protective action on the given device based on the received context information and the one or more features extracted by the agent.

Claims (31)

1 . A method for computer protection, comprising:

detecting, by a security agent running on an endpoint computing device, an event of given event type associated with suspicious behavior occurring in execution of a software process by the endpoint computing device;

conveying a query with respect to the event type over a network from the security agent to a security server;

receiving, from the security server in response to the query, context information with respect to the event type based on collation of event reports from multiple endpoint computing devices;

extracting, by the security agent, one or more features from the detected event;

making a real-time decision, by the security agent, whether to block the suspicious behavior on the endpoint computing device based on the context information received from the security server and the one or more features extracted by the security agent, wherein the context information comprises a profile for the given event type, the profile comprising a set of profile features and a corresponding set of feature weights, wherein the feature weights are determined based on at least one of a frequency and a recency of the profile features in event records, and wherein making the real-time decision comprises computing a suspiciousness score by applying the feature weights to the one or more features extracted from the detected event wherein less frequent or less recent feature combinations are weighted to produce a higher suspiciousness score; and

initiating a protective action by the security agent on the endpoint computing device in response to the decision.

2 . The method according to claim 1 , wherein the event reports comprise event logs maintained by the computing devices.

3 . The method according to claim 1 , wherein ARM a making the real-time decision comprises modeling the one or more features.

4 . The method according to claim 1 , wherein the context information comprises a frequency of occurrence of the event type on other endpoint computing devices in the network.

5 . The method according to claim 1 , wherein the context information comprises a recency of occurrence of the event type on other endpoint computing devices in the network.

6 . The method according to claim 1 , wherein the event comprises receiving a file via the network at the endpoint computing device.

7 . The method according to claim 6 , wherein initiating the protective action comprises preventing the endpoint computing device from storing the file to a storage device.

8 . The method according to claim 6 , wherein initiating the protective action comprises preventing the endpoint computing device from accessing the file.

9 . The method according to claim 1 , wherein the event comprises establishing a connection between the endpoint computing device and a web site.

10 . The method according to claim 9 , wherein initiating the protective action comprises closing the connection.

11 . The method according to claim 1 , wherein initiating the protective action comprises terminating execution of the software process.

12 . The method according to claim 1 , wherein the context information comprises an identifier of a software application usually associated with the event type.

13 . An endpoint computing device, comprising:

a memory configured to store a security agent; and

a processor configured to execute the security agent so as to detect an event of given event type associated with suspicious behavior occurring in execution of a software process by the endpoint computing device, to convey a query with respect to the event type over a network from the security agent to a security server, to receive, from the security server in response to the query, context information with respect to the event type based on collation of event reports from multiple endpoint computing devices,

wherein the security agent is configured to extract one or more features from the detected event, to make a real-time decision whether to block the suspicious behavior on the endpoint computing device based on the context information received from the security server and the one or more features extracted by the security agent, wherein the context information comprises a profile for the given event type, the profile comprising a set of profile features and a corresponding set of feature weights, wherein the feature weights are determined based on at least one of a frequency and a recency of the profile features in event records, and wherein making the real-time decision comprises computing a suspiciousness score by applying the feature weights to the one or more features extracted from the detected event, wherein less frequent or less recent feature combinations are weighted to produce a higher suspiciousness score, and to initiate a protective action by the security agent on the endpoint computing device in response to the decision.

14 . A computer software product, comprising a non-transitory computer-readable medium, in which program instructions are stored, which instructions, when read by a processor in an endpoint computing device, cause the processor to execute a security agent so as to detect an event of given event type associated with suspicious behavior occurring in execution of a software process by the endpoint computing device, to convey a query with respect to the event type over a network from the security agent to a security server, to receive, from the security server in response to the query, context information with respect to the event type based on collation of event reports from multiple endpoint computing devices,

wherein the instructions cause the security agent to extract one or more features from the detected event, to make a real-time decision whether to block the suspicious behavior on the endpoint computing device based on the context information received from the security server and the one or more features extracted by the security agent, wherein the context information comprises a profile for the given event type, the profile comprising a set of profile features and a corresponding set of feature weights, wherein the feature weights are determined based on at least one of a frequency and a recency of the profile features in event records, and wherein making the real-time decision comprises computing a suspiciousness score by applying the feature weights to the one or more features extracted from the detected event, wherein less frequent or less recent feature combinations are weighted to produce a higher suspiciousness score, and to initiate a protective action by the security agent on the endpoint computing device in response to the decision.

15 . The product according to claim 14 , wherein making the real-time decision comprises modeling the one or more features.

16 . The product according to claim 14 , wherein the context information comprises a frequency of occurrence of the event type on other endpoint computing devices in the network.

17 . The product according to claim 14 , wherein the context information comprises a recency of occurrence of the event type on other endpoint computing devices in the network.

18 . The product according to claim 14 , wherein the event comprises receiving a file via the network at the endpoint computing device.

19 . The product according to claim 14 , wherein the event comprises establishing a connection between the endpoint computing device and a web site.

20 . The product according to claim 14 , wherein initiating the protective action comprises terminating execution of the software process.

21 . The product according to claim 14 , wherein the context information comprises an identifier of a software application usually associated with the event type.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 3, 2024
From: PALO ALTO NETWORKS (ISRAEL ANALYTICS) LTD.
To: PALO ALTO NETWORKS INC.
Reel/Frame 068823/0886 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 21, 2022
From: ALLON, JONATHAN; SELA, NIV; ZIGELBAUM, LIAV; PILOSOF, GUY; BECK, ORI
To: PALO ALTO NETWORKS (ISRAEL ANALYTICS) LTD.
Reel/Frame 059055/0266 →
Continuity (1)
Related Publication 20230269256A1 · Aug 24, 2023
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