Extracting forensic indicators from activity logs

• US 20170026395A1
• Filed: 10/06/2016
• Published: 01/26/2017
• Est. Priority Date: 01/16/2013
• Status: Abandoned Application

• Current Assignee: Light Cyber Ltd.
• Original Assignee: Light Cyber Ltd.
• Inventors: Mumcuoglu, Michael, Engel, Giora, Firstenberg, Eyal
• Application Number:
  US15/286,674
• Publication Number:
  US 20170026395A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 21/552 involving long-term monitoring or reporting
• CPC Class Codes: G06F 21/566 Dynamic detection, i.e. detection performed at run-time, e.g. emulation, suspicious activities
• CPC Class Codes: H04L 2463/121 Timestamp cryptographic mechanisms or cryptographic arrangements involving time stamps H04L9/3297
• CPC Class Codes: H04L 61/4511 using domain name system [DNS]
• CPC Class Codes: H04L 63/0227 Filtering policies mail message filtering H04L51/212
• CPC Class Codes: H04L 63/1416 Event detection, e.g. attack signature detection
• CPC Class Codes: H04L 63/1425 Traffic logging, e.g. anomaly detection
• CPC Class Codes: H04L 63/1441 Countermeasures against malicious traffic countermeasures against attacks on cryptographic mechanisms H04L9/002

Abstract

A method for computer system forensics includes receiving an identification of a time of occurrence of an anomalous event in a computer network including multiple host computers. Logs of activity of entities in the computer network are collected. A comparison is made between first entries in at least one of the logs collected within a predefined time interval of the time of the occurrence of the anomalous event, and second entries in the at least one of the logs collected outside the predefined time interval. Based on the comparison, a forensic indicator associated with the anomalous event is extracted from the logs.

Claims

1. A method for computer system forensics, comprising:

receiving an identification of a time of occurrence of an anomalous event in a computer network comprising multiple host computers;

collecting logs of activity of entities in the computer network;

making a comparison between first entries in at least one of the logs collected within a predefined time interval of the time of the occurrence of the anomalous event, and second entries in the at least one of the logs collected outside the predefined time interval; and

based on the comparison, extracting from the logs a forensic indicator associated with the anomalous event.

2. The method according to claim 1, wherein collecting the logs comprises collecting information from a log selected from a set of logs consisting of host computer logs, system event logs, system-wide application event logs, security logs, audit logs, application-specific logs, file system tables, and browsing histories.

3. The method according to claim 1, wherein the identification specifies at least one of the host computers that is associated with the anomalous event, and wherein making the comparison comprises processing log information with respect to the at least one of the host computers.

4. The method according to claim 1, wherein receiving the identification comprises receiving a timestamp associated with an anomalous message transmitted by one of the host computers.

5. The method according to claim 1, wherein extracting the forensic indicator comprises assigning respective scores to lines of the logs in the first entries, and extracting the forensic indicators from the lines that meet a predefined scoring criterion.

6. The method according to claim 1, wherein extracting the forensic indicator comprises providing at least one identifier selected from a group of identifiers consisting of filenames, paths, registry paths, process names, module names, application names, and e-mail GUIDS that appear in the logs.

7. Apparatus for computer system forensics, comprising:

an interface, which is configured to receive an identification of a time of occurrence of an anomalous event in a computer network comprising multiple host computers; and

a processor, which is configured to collect logs of activity of entities in the computer network, to make a comparison between first entries in at least one of the logs collected within a predefined time interval of the time of the occurrence of the anomalous event, and second entries in the at least one of the logs collected outside the predefined time interval, and based on the comparison, to extract from the logs a forensic indicator associated with the anomalous event.

8. The apparatus according to claim 7, wherein the collected logs comprise information from a log selected from a set of logs consisting of host computer logs, system event logs, system-wide application event logs, security logs, audit logs, application-specific logs, file system tables, and browsing histories.

9. The apparatus according to claim 7, wherein the identification specifies at least one of the host computers that is associated with the anomalous event, and wherein the processor is configured to make the comparison by processing log information with respect to the at least one of the host computers.

10. The apparatus according to claim 7, wherein the identification comprises a timestamp associated with an anomalous message transmitted by one of the host computers.

11. The apparatus according to claim 7, wherein the processor is configured to extract the forensic indicator by assigning respective scores to lines of the logs in the first entries, and taking the forensic indicators from the lines that meet a predefined scoring criterion.

12. The apparatus according to claim 7, wherein the extracted forensic indicator comprises at least one identifier selected from a group of identifiers consisting of filenames, paths, registry paths, process names, module names, application names, and e-mail GUIDS that appear in the logs.

13. A computer software product, comprising a computer-readable medium in which program instructions are stored, which instructions, when read by a computer, cause the computer to receive an identification of a time of occurrence of an anomalous event in a computer network comprising multiple host computers, to collect logs of activity of entities in the computer network, to make a comparison between first entries in at least one of the logs collected within a predefined time interval of the time of the occurrence of the anomalous event, and second entries in the at least one of the logs collected outside the predefined time interval, and based on the comparison, to extract from the logs a forensic indicator associated with the anomalous event.

14. The product according to claim 13, wherein the collected logs comprise information from a log selected from a set of logs consisting of host computer logs, system event logs, system-wide application event logs, security logs, audit logs, application-specific logs, file system tables, and browsing histories.

15. The product according to claim 13, wherein the identification specifies at least one of the host computers that is associated with the anomalous event, and wherein the instructions cause the computer to make the comparison by processing log information with respect to the at least one of the host computers.

16. The product according to claim 13, wherein the identification comprises a timestamp associated with an anomalous message transmitted by one of the host computers.

17. The product according to claim 13, wherein the instructions cause the computer to extract the forensic indicator by assigning respective scores to lines of the logs in the first entries, and taking the forensic indicators from the lines that meet a predefined scoring criterion.

18. The product according to claim 13, wherein the extracted forensic indicator comprises at least one identifier selected from a group of identifiers consisting of filenames, paths, registry paths, process names, module names, application names, and e-mail GUIDS that appear in the logs.