IP Library Granted Patent US 10,084,806
Granted Patent B2
US 10,084,806 · App. 14/015,663 · Granted Sep 25, 2018

Traffic simulation to identify malicious activity

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Quick Facts
Patent No.
US 10,084,806
App. No.
14/015,663
Granted
Sep 25, 2018
Kind
B2
Abstract

Systems and methods may simulate traffic to identify malicious activity. A dynamic analysis system comprising a processor in communication with a network may receive a copy of a malware program and load the copy of the malware program into a simulated endpoint. The system may monitor simulated endpoint network traffic to or from the simulated endpoint, assess the simulated endpoint network traffic to determine a source and/or destination for the simulated endpoint network traffic and/or content of the simulated endpoint network traffic, and capture and store metadata associated with the simulated endpoint network traffic. A comparison system may compare simulated network traffic metadata to observed network traffic metadata to determine whether the metadata are statistically similar. When the metadata are not statistically similar, the system may generate a low infection confidence score. When the metadata are statistically similar, the system may generate a high infection confidence score.

Claims (61)

1. A method comprising:

using a dynamic analysis system comprising a processor in communication with a network:

receiving, by the processor, a copy of a malware program;

loading, using the processor, the copy of the malware program into a simulated endpoint;

executing, using the processor, the copy of the malware program in the simulated endpoint, the simulated endpoint being within the dynamic analysis system;

generating, based on the execution, network traffic at the simulated endpoint for the malware program, the traffic being generated by the malware program for communicating with a network infrastructure;

receiving, using the processor, network traffic intended for the malware program at the simulated endpoint;

monitoring, using the processor, the traffic to and from the malware program on the simulated endpoint;

assessing, using the processor, the network traffic on the simulated endpoint to determine at least one of a source and a destination for the traffic on the simulated endpoint, and content of the traffic on the simulated endpoint; and

capturing using the processor, metadata associated with the traffic on the simulated endpoint and storing the metadata in the database; and

using a comparison system comprising a processor;

comparing, using the processor of the comparison system, metadata associated with observed network traffic to the metadata associated with the traffic on the simulated endpoint to determine whether the metadata associated with the observed network traffic and the metadata associated with the traffic on the simulated endpoint are statistically similar;

when the metadata associated with the observed network traffic and the metadata associated with the traffic on the simulated endpoint are not statistically similar, generating a low infection confidence score associated with the observed network traffic; and

when the metadata associated with the suspicious network traffic and the metadata associated with the on the simulated endpoint are statistically similar, generating a high infection confidence score associated with the observed network traffic, the high infection confidence score being higher than the low infection confidence score.

2. The method of claim 1 , further comprising: sending, with the comparison system, the low infection confidence score or the high infection confidence score to a display in communication with the comparison system.

3. The method of claim 1 , further comprising: when the metadata associated with the observed network traffic and the metadata associated with the traffic on the simulated endpoint are statistically similar, analyzing, with the dynamic analysis system, the metadata associated with the traffic on the simulated endpoint to identify a simulated network traffic type.

4. The method of claim 1 , wherein the observed network traffic comprises all traffic to and from an asset having a potential malware infection associated with the network.

5. The method of claim 1 , wherein the observed network traffic comprises suspicious network traffic.

6. The method of claim 5 , further comprising:

monitoring, with a monitoring system comprising a processor in communication with the network, network traffic to and from an asset associated with the network;

assessing, with the monitoring system, the network traffic to determine at least one of a source and destination for the network traffic, and content of the network traffic;

determining, with the monitoring system, whether the network traffic is suspicious network traffic based on the assessed at least one of source, destination, and content;

when the network traffic is determined to be suspicious network traffic, capturing, with the monitoring system, metadata associated with the suspicious network traffic and storing the metadata in a database in communication with the processor; and

when the network traffic is not determined to be suspicious network traffic, disregarding, with the monitoring system, metadata associated with the network traffic.

7. The method of claim 6 , wherein the monitoring comprises monitoring a transport protocol of the network traffic, monitoring an application protocol of the network traffic, monitoring a source and destination of the network traffic, and monitoring content of the network traffic.

8. The method of claim 6 , wherein the determining whether the network traffic is suspicious network traffic is based on a low reputation score associated with the source and destination for the network traffic, a suspicious DGA cluster associated with the source and destination for the network traffic, a suspicious DGA cluster associated with the content of the network traffic, and a suspicious content element within the content of the network traffic.

9. The method of claim 6 , further comprising: when the network traffic is determined to be suspicious network traffic, indexing, with the monitoring system, the metadata.

10. The method of claim 6 , wherein the metadata comprises at least one of a source port, a destination port, a transport protocol, an application protocol, a time stamp, a duration, a source identifier, a destination identifier, a bytes in count, a bytes out count, a connection success indicator, a connection status, a DNS RR set, HTTP data, a file within the content of the network traffic, the content of the network traffic, and a subsequent communication.

11. The method of claim 6 , further comprising: when the network traffic is determined to be suspicious network traffic, sending, with the monitoring system, a report indicating that the network traffic is determined to be suspicious network traffic to a display in communication with the monitoring system.

12. The method of claim 6 , wherein determining whether the network traffic is suspicious network traffic comprises determining that all traffic to and from the asset is suspicious network traffic when the asset is an asset with a potential malware infection.

13. A system comprising:

a database;

a dynamic analysis system comprising a processor in communication with a network and in communication with the database, the dynamic analysis system being constructed and arranged to:

receive, by the processor, a copy of a malware program;

load, using the processor, the copy of the malware program into a simulated endpoint;

execute, using the processor, the copy of the malware program in the simulated endpoint, the simulated endpoint being within the dynamic analysis system;

generate, based on the execution, network traffic at the simulated endpoint for the malware program, the traffic being generated by the malware program for communicating with a network infrastructure;

receive, using the processor, network traffic intended for the malware program at the simulated endpoint in response;

monitor, using the processor, the traffic to and from the malware program on the simulated endpoint;

assess, using the processor, the traffic on the simulated endpoint to determine at least one of a source and a destination for the traffic on the simulated endpoint, and content of the traffic on the simulated endpoint;

capture, using the processor, metadata associated with the traffic on the simulated endpoint and store the metadata in the database; and

compare, using the processor, metadata associated with observed network traffic to the metadata associated with the traffic on the simulated endpoint to determine whether the metadata associated with the observed network traffic and the metadata associated with the traffic on the simulated endpoint are statistically similar;

when the metadata associated with the observed network traffic and the metadata associated with the traffic on the simulated endpoint are not statistically similar, generate a low infection confidence score associated with the observed network traffic; and

when the metadata associated with the observed network traffic and the metadata associated with the traffic on the simulated endpoint are statistically similar, generate a high infection confidence score associated with the observed network traffic, the high infection confidence score being higher than the low infection confidence score.

14. The system of claim 13 , wherein the comparison system is further constructed and arranged to: send the low infection confidence score or the high infection confidence score to a display in communication with the comparison system.

15. The system of claim 13 , wherein the dynamic analysis system is further constructed and arranged to: when the metadata associated with the observed network traffic and the metadata associated with the traffic on the simulated endpoint are statistically similar, analyze the metadata associated with the simulated network traffic to identify a simulated network traffic type.

16. The system of claim 13 , wherein the observed network traffic comprises all traffic to and from an asset having a potential malware infection associated with the network.

17. The system of claim 13 , wherein the observed network traffic comprises suspicious network traffic.

18. The system of claim 17 , further comprising:

a monitoring system comprising a processor in communication with the network and in communication with the database, the monitoring system being constructed and arranged to:

monitor network traffic to and from an asset associated with the network;

assess the network traffic to determine at least one of a source and destination for the network traffic and content of the network traffic;

determine whether the network traffic is suspicious network traffic based on the assessed destination and/or content;

when the network traffic is determined to be suspicious network traffic, capture metadata associated with the suspicious network traffic and store the metadata in the database; and

when the network traffic is not determined to be suspicious network traffic, disregard metadata associated with the network traffic.

19. The system of claim 18 , wherein the monitoring comprises monitoring a transport protocol of the network traffic, monitoring an application protocol of the network traffic, monitoring a source and destination of the network traffic, and monitoring content of the network traffic.

20. The system of claim 18 , wherein the determining whether the network traffic is suspicious network traffic is based on a low reputation score associated with the source and destination for the network traffic, a suspicious DGA cluster associated with the source and destination for the network traffic, a suspicious DGA cluster associated with the content of the network traffic, and a suspicious content element within the content of the network traffic.

21. The system of claim 18 , wherein the monitoring system is further constructed and arranged to: when the network traffic is determined to be suspicious network traffic, index the metadata.

22. The system of claim 18 , wherein the metadata comprises at least one of a source port, a destination port, a transport protocol, an application protocol, a time stamp, a duration, a source identifier, a destination identifier, a bytes in count, a bytes out count, a connection success indicator, a connection status, a DNS RR set, HTTP data, a file within the content of the network traffic, the content of the network traffic, and a subsequent communication.

23. The system of claim 18 , wherein the monitoring system is further constructed and arranged to: when the network traffic is determined to be suspicious network traffic, send a report indicating that the network traffic is determined to be suspicious network traffic to a display in communication with the monitoring system.

24. The system of claim 18 , wherein the monitoring system is constructed and arranged to determine whether the network traffic is suspicious network traffic with a method comprising determining that all traffic to and from the asset is suspicious network traffic when the asset is an asset with a potential malware infection.

Assignments (20)
SECURITY INTEREST Recorded Jan 6, 2026
From: ALERT LOGIC, INC.; DIGITAL GUARDIAN LLC; ECRIME MANAGEMENT STRATEGIES, INC.; FORTRA, LLC; GLOBALSCAPE, INC.; TRIPWIRE, INC.
To: ACQUIOM AGENCY SERVICES LLC, AS COLLATERAL AGENT
Reel/Frame 074233/0632 →
TERMINATION AND RELEASE OF FIRST LIEN INTELLECTUAL PROPERTY SECURITY INTEREST RECORDED AT REEL/FRAME 51059/0861 Recorded Nov 24, 2025
From: JEFFERIES FINANCE LLC
To: FORTRA, LLC (FORMERLY KNOWN AS HELP/SYSTEMS, LLC)
Reel/Frame 073783/0406 →
TERMINATION AND RELEASE OF SECOND LIEN INTELLECTUAL PROPERTY SECURITY INTEREST RECORDED AT REEL/FRAME 51059/0911 Recorded Nov 21, 2025
From: ACQUIOM AGENCY SERV ICES LLC
To: FORTRA, LLC (F/K/A HELP/SYSTEMS, LLC)
Reel/Frame 073662/0442 →
NEW MONEY FIRST LIEN INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Nov 21, 2025
From: ALERT LOGIC, INC.; DIGITAL GUARDIAN LLC; ECRIME MANAGEMENT STRATEGIES, INC.; FORTRA, LLC; GLOBALSCAPE, INC.; TRIPWIRE, INC.; VERA SECURITY, INC.
To: ARES CAPITAL CORPORATION, AS COLLATERAL AGENT
Reel/Frame 073683/0534 →
EXTENDED FIRST LIEN INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Nov 21, 2025
From: FORTRA, LLC
To: JEFFERIES FINANCE LLC, AS COLLATERAL AGENT
Reel/Frame 073663/0914 →
EXTENDED RCF FIRST LIEN INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Nov 21, 2025
From: FORTRA, LLC
To: JEFFERIES FINANCE LLC, AS COLLATERAL AGENT
Reel/Frame 073663/0327 →
ASSIGNMENT OF INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Aug 14, 2025
From: GOLUB CAPITAL MARKETS LLC (AS EXISTING AGENT)
To: ACQUIOM AGENCY SERVICES LLC (AS SUCCESSOR COLLATERAL AGENT)
Reel/Frame 072471/0665 →
RELEASE OF SECURITY INTEREST Recorded Feb 3, 2025
From: PNC BANK, NATIONAL ASSOCIATION
To: DAMBALLA, INC.
Reel/Frame 070086/0189 →
CHANGE OF NAME Recorded Dec 15, 2022
From: HELP/SYSTEMS, LLC
To: FORTRA, LLC
Reel/Frame 062136/0777 →
ASSIGNMENT OF INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded May 20, 2021
From: JEFFERIES FINANCE LLC, AS EXISTING AGENT
To: GOLUB CAPITAL MARKETS LLC, AS SUCCESSOR AGENT
Reel/Frame 056322/0628 →
SECOND LIEN INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Nov 19, 2019
From: HELP/SYSTEMS, LLC
To: JEFFERIES FINANCE LLC, AS COLLATERAL AGENT
Reel/Frame 051059/0911 →
FIRST LIEN INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Nov 19, 2019
From: HELP/SYSTEMS, LLC
To: JEFFERIES FINANCE LLC, AS COLLATERAL AGENT
Reel/Frame 051059/0861 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 20, 2019
From: DAMBALLA, INC.
To: HELP/SYSTEMS, LLC
Reel/Frame 048386/0329 →
RELEASE OF SECURITY INTEREST Recorded Feb 8, 2019
From: PNC BANK, NATIONAL ASSOCIATION
To: COURION INTERMEDIATE HOLDINGS, INC.; CORE SECURITY SDI CORPORATION; CORE SECURITY TECHNOLOGIES, INC.; CORE SDI, INC.; CORE SECURITY LIVE CORPORATION; CORE SECURITY HOLDINGS, INC.; DAMABLLA, INC.
Reel/Frame 048281/0835 →
RELEASE OF SECURITY INTEREST Recorded Jan 4, 2018
From: SARATOGA INVESTMENT CORP. SBIC LP
To: DAMBALLA, INC.
Reel/Frame 044535/0907 →
SECURITY INTEREST Recorded Dec 27, 2017
From: DAMBALLA, INC.
To: PNC BANK, NATIONAL ASSOCIATION
Reel/Frame 044492/0654 →
PATENT SECURITY AGREEMENT Recorded Oct 10, 2016
From: DAMBALLA, INC.
To: SARATOGA INVESTMENT CORP. SBIC LP, AS ADMINISTRATIVE AGENT
Reel/Frame 040297/0988 →
RELEASE OF SECURITY INTEREST Recorded Sep 8, 2016
From: SILICON VALLEY BANK
To: DAMBALLA, INC.
Reel/Frame 039678/0960 →
SECURITY INTEREST Recorded May 14, 2015
From: DAMBALLA, INC.
To: SILICON VALLEY BANK
Reel/Frame 035639/0136 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 25, 2013
From: WARD, JOSEPH; HOBSON, ANDREW
To: DAMBALLA, INC.
Reel/Frame 031672/0513 →
Cited By (4)
US 12,267,299 US 12,499,218 US 12,511,386 US 12,526,309