IP Library › Granted Patent US 12,463,997
Granted Patent B1
US 12,463,997 · App. 18/243,520 · Granted Nov 4, 2025

Attack path risk mitigation by a data platform using static and runtime data

Inventors: Xiaofei Guo (Sunnyvale, CA); John Payyappillil John (Seattle, WA); Matti A. Vanninen (Cary, NC); Theodore M. Reed (Berkeley Heights, NJ); Nolan K. Karpinski (San Francisco, CA); Mary L Singh (Arlington, VA); Sowmya A. Karmali (Tustin, CA); Yijou Chen (Cupertino, CA)
Assignee: Fortinet, Inc.
H04L63/1425G06F16/9024G06F16/9038G06F16/9535G06F16/9537G06F21/57H04L43/045H04L43/06H04L63/10H04L67/306H04L67/535G06F16/2456
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Quick Facts
Patent No.
US 12,463,997
App. No.
18/243,520
Filed
Sep 7, 2023
Granted
Nov 4, 2025
Kind
B1
Art Unit
2493
USPC
726/22
Abstract

An illustrative method includes identifying, based on static workload data associated with a compute environment, one or more attack paths from a network to one or more datasets associated with an entity, accessing runtime workload data associated with the compute environment, and performing, based on the runtime workload data, a risk mitigation operation associated with the one or more attack paths.

Claims (37)

1 . A method comprising:

identifying, by a data platform based on static workload data associated with a compute environment, one or more attack paths from a network to one or more datasets associated with an entity, the one or more attack paths each including a series of risk artifacts within the compute environment that could be exploited by an attacker to access the one or more datasets;

accessing, by the data platform, runtime workload data associated with the compute environment;

determining, based on differences between the static workload data and the runtime workload data, privilege configurations or access configurations that are unused or partially-used by the entity; and

performing, by the data platform based on the runtime workload data, a risk mitigation operation associated with the one or more attack paths.

2 . The method of claim 1 , wherein the performing the risk mitigation operation comprises determining, based on one or more differences between the static workload data and the runtime workload data, one or more levels of overprovisioning associated with one or more risk artifacts included in the series of risk artifacts.

3 . The method of claim 2 , wherein the one or more levels of overprovisioning are associated with one or more of a usage of privileges associated with one or more identities, a usage of network access, or a usage of one or more secrets.

4 . The method of claim 2 , wherein the performing the risk mitigation operation further comprises a select one or both of remediating or providing a recommendation to remediate the one or more levels of overprovisioning.

5 . The method of claim 1 , wherein the performing the risk mitigation operation comprises determining, based on one or more differences between the static workload data and the runtime workload data, one or more anomalies associated with one or more risk artifacts included in the series of risk artifacts, the one or more anomalies indicative of the one or more attack paths being exploited.

6 . The method of claim 1 , wherein the performing the risk mitigation operation comprises ranking, based on one or more levels of usage associated with one or more risk artifacts included in the series of risk artifacts, the one or more attack paths relative to one another such that an attack path having a lower level of usage than another attack path is ranked higher than the other attack path.

7 . The method of claim 6 , wherein the one or more levels of usage are associated with one or more of a usage of privileges associated with one or more identities, a usage of network access, or a usage of one or more secrets.

8 . The method of claim 1 , further comprising generating, based on the static workload data, an attack path graph representative of the one or more attack paths, wherein the risk mitigation operation comprises enhancing, based on the runtime workload data, the attack path graph.

9 . The method of claim 8 , wherein the enhancing the attack path graph includes providing one or more visual indicators indicative of one or more levels of activity associated with one or more risk artifacts included in the series of risk artifacts.

10 . The method of claim 8 , wherein the enhancing the attack path graph includes providing one or more visual indicators indicative of one or more differences between the static runtime data and the runtime workload data.

11 . The method of claim 1 , wherein the static workload data associated with the compute environment is collected using an agentless workload scanning configuration.

12 . The method of claim 1 , wherein the runtime workload data associated with the compute environment is collected using an agent configuration deployed in the compute environment.

13 . The method of claim 12 , further comprising:

constructing, by the data platform and based on the runtime workload data, a graph comprising a plurality of nodes connected by a plurality of edges, wherein each node of the plurality of nodes represents a logical entity associated with the runtime workload data and each edge of the plurality of edges represents a behavioral relationship between nodes connected by the edge; and

wherein the identifying the one or more attack paths is further based on the graph.

14 . The method of claim 1 , wherein the one or more datasets includes sensitive data associated with the entity.

15 . A method comprising:

identifying, by a data platform based on static workload data associated with a compute environment, an attack path from a network to a dataset associated with an entity, the attack path including a series of risk artifacts within the compute environment that could be exploited by an attacker to access the dataset;

generating, by the data platform based on the attack path, an attack path graph comprising a plurality of nodes connected by a plurality of edges, wherein each node of the plurality of nodes represents a risk artifact of the series of risk artifacts and each edge of the plurality of edges represents an access path between different risk artifacts connected by the edge;

accessing, by the data platform, runtime workload data associated with the compute environment;

determining, based on differences between the static workload data and the runtime workload data, privilege configurations or access configurations that are unused or partially-used by the entity; and

performing, by the data platform based on the runtime workload data, an operation associated with the attack path graph.

16 . The method of claim 15 , wherein the performing the operation associated with the attack path graph comprises providing one or more visual indicators indicative of one or more levels of activity associated with one or more risk artifacts included in the series of risk artifacts.

17 . The method of claim 15 , wherein the performing the operation associated with the attack path graph comprises providing one or more visual indicators indicative of one or more differences between the static runtime data and the runtime workload data.

18 . The method of claim 15 , further comprising receiving a request from a user input to display additional information associated with the attack path included in the attack path graph.

19 . The method of claim 18 , wherein the additional information includes one or more of an attack path risk score associated with the attack path, one or more risk factors associated with the attack path risk score, network access associated with the attack path, one or more identities associated with the attack path, one or more secrets associated with the attack path, one or more vulnerabilities associated with the attack path, one or more misconfigurations associated with the attack path, an impact associated with the dataset included in the attack path being exploited, or one or more compute resources associated with the attack path.

20 . A system comprising:

a memory storing instructions; and

one or more processors communicatively coupled to the memory and configured to execute the instructions to perform a process comprising:

identifying, based on static workload data associated with a compute environment, one or more attack paths from a network to one or more datasets associated with an entity, the one or more attack paths each including a series of risk artifacts within the compute environment that could be exploited by an attacker to access the one or more datasets;

accessing runtime workload data associated with the compute environment;

determining, based on differences between the static workload data and the runtime workload data, privilege configurations or access configurations that are unused or partially-used by the entity; and

performing, based on the runtime workload data, a risk mitigation operation associated with the one or more attack paths.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 7, 2024
From: LACEWORK, INC.
To: FORTINET, INC.
Reel/Frame 069301/0327 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 7, 2023
From: GUO, XIAOFEI; JOHN, JOHN PAYYAPPILLIL; VANNINEN, MATTI A.; REED, THEODORE M.; KARPINSKI, NOLAN K.; SINGH, MARY L.; KARMALI, SOWMYA A.; CHEN, YIJOU
To: LACEWORK, INC.
Reel/Frame 064834/0373 →
Continuity (7)
Continuation In Part 18119045 · Mar 8, 2023
Continuation 17510179 · Oct 25, 2021
Continuation 16786822 · Feb 10, 2020
Continuation 16134806 · Sep 18, 2018
Provisional Application 63422950 · Nov 5, 2022
Provisional Application 62650971 · Mar 30, 2018
Provisional Application 62590986 · Nov 27, 2017
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