# US 2020/0396237 A1 · Phishing data item clustering and analysis

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- Number: US 2020/0396237 A1
- Document ID: US20200396237A1
- Status: Published application
- Kind: A1
- Application number: 17/003,398
- Filed: 2020-08-26
- Published: 2020-12-17
- Earliest claimed: 2014-07-03
- Assignees: Palantir Technologies Inc.
- Applicants: Palantir Technologies Inc.
- Inventors: David Cohen; Jason Ma; Bing Jie Fu; Ilya Nepomnyashchiy; Steven Berler; Alex Smaliy; Jack Grossman; James Thompson; Julia Boortz; Matthew Sprague; Parvathy Menon; Michael Kross; Michael Harris; Adam Borochoff
- Web page: https://patentgrep.com/patent/US20200396237A1

## CPC

- H04L 63/1425: {Traffic logging, e.g. anomaly detection}
- G06F 16/285: {Clustering or classification}
- G06Q 40/12: Accounting
- H04L 63/1408: {by monitoring network traffic (monitoring network traffic per se H04L43/00)}
- H04L 63/145: {the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms}
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyses (also referred to herein as “summaries” or “conclusions”) of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures.

## Claims

### Claim 1

(canceled)

### Claim 2

A computer system comprising:
one or more computer readable storage devices configured to store:
a plurality of computer executable instructions;
a data clustering strategy; and
a plurality of data items including at least:
a plurality of email data items, each of the plurality of email data items including at least a subject and a sender, each of the plurality of email data items potentially associated with phishing activity; and
a plurality of phishing-related data items related to a communications network of an organization, the plurality of phishing-related data items including at least one of: internal Internet Protocol addresses of the communications network, computerized devices of the communications network, users of particular computerized devices, organizational positions associated with users of particular computerized devices, or URLs and/or external domains visited by users of particular computerized devices; and
one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the computer system to:
access an email data item transmitted to one or more of the users of respective computerized devices within the network of the organization, the email data item including at least a subject and a sender, the email data item potentially associated with phishing activity;
designate the accessed email data item as a seed; and
generate a data item cluster based on the data clustering strategy by at least:
adding the seed to the data item cluster;
determining the subject and the sender associated with the seed;
identifying one or more of the plurality of email data items having a same subject as the determined subject or a same sender as the determined sender;
adding the identified one or more email data items to the data item cluster;
parsing one or more URLs from the email data items of the data item cluster;
adding the parsed URLs to the data item cluster;
identifying one or more users who are both recipients of at least one of the email data items of the data item cluster and visitors of one of the URLs of the data item cluster; and
adding the identified one or more users, including data related to the one or more users, to the data item cluster.

### Claim 3 (depends on 2)

The computer system of claim 2, wherein generating the data item cluster based on the data clustering strategy further comprises:
determining any new subjects or new senders associated with email data items of the data item cluster that are different from the determined subjects or the determined senders;
identifying a second one or more of the plurality of email data items having a same subject as the determined new subject, or a same sender as the determined new sender; and
adding the identified second one or more email data items to the data item cluster.

### Claim 4 (depends on 2)

The computer system of claim 2, wherein the identified one or more email data items are added to the data item cluster only if received by one or more computerized devices within the network within a predetermined period of time from a time that the seed was received.

### Claim 5 (depends on 4)

The computer system of claim 4, wherein the period of time comprises at least one of a number of hours, a number of days, or a number of weeks.

### Claim 6 (depends on 4)

The computer system of claim 4, wherein the predetermined period of time is further determined based on other email data items in the data item cluster.

### Claim 7 (depends on 2)

The computer system of claim 2, wherein generating the data item cluster based on the data clustering strategy further comprises:
identifying additional one or more data items associated with any data items of the data item cluster; and
adding, to the data item cluster, the additional one or more data items.

### Claim 8 (depends on 2)

The computer system of claim 2, wherein identifying the one or more users further comprises:
scanning communications on the communications network of the organization so as to generate phishing-related data items including URLs visited by particular users;
extracting recipients of the email data items of the data item cluster associated with respective parsed URLs; and
for any parsed URL matching a URL visited by a particular user, if the extracted recipient of the email data item associated with the parsed URL matches the particular user, then identifying the user.

### Claim 9 (depends on 8)

The computer system of claim 8, wherein the communications are continuously scanned via a proxy.

### Claim 10 (depends on 2)

The computer system of claim 2, wherein the one or more hardware computer processors are further configured to execute the plurality of computer executable instructions in order to cause the one or more hardware computer processors to:
continuously receive email data items from users of respective computing devices of the organization, designate the received email data items as seeds, and generate data items clusters based on the data clustering strategy.

### Claim 11 (depends on 2)

The computer system of claim 2, wherein the data related to the one or more users includes an organizational position associated with the user.

### Claim 12

A computer system comprising:
one or more computer readable storage devices configured to store:
a plurality of computer executable instructions;
a data clustering strategy; and
a plurality of data items including at least:
a plurality of email data items, each of the plurality of email data items including at least a subject and a sender, each of the plurality of email data items potentially associated with phishing activity; and
a plurality of phishing-related data items related to customers of an organization, the plurality of phishing-related data items including indicators of at least one of: customers of the organization or URLs identified as malicious by a third-party service; and
one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the computer system to:
receive a plurality of email data items from customers of the organization, each of the email data items including at least a subject and a sender, each of the email data items potentially associated with phishing activity;
designate each of the received email data items as seeds; and
for each of the designated seeds, generate a data item cluster based on the data clustering strategy by at least:
adding the seed to the data item cluster;
determining the subject and the sender associated with the seed;
accessing the one or more computer readable storage devices and identifying one or more of the plurality of email data items having a same subject as the determined subject or a same sender as the determined sender;
adding the identified one or more email data items to the data item cluster;
parsing one or more URLs from the email data items of the data item cluster;
adding the URLs to the data item cluster; and
in response to determining that the data item cluster includes at least a predetermined threshold quantity of email data items, designating the data item cluster as a campaign cluster.

### Claim 13 (depends on 12)

The computer system of claim 12, wherein the one or more hardware computer processors are further configured to execute the plurality of computer executable instructions in order to cause the one or more hardware computer processors to:
for each campaign cluster, initiate further automated investigation including at least:
comparing URLs included in the campaign cluster with URLs previously identified as malicious by a third-party service;
based on the comparing, identifying any URLs included in the campaign cluster not previously identified as malicious by the third-party service; and
notifying the third-party service of the identified URLs.

### Claim 14 (depends on 12)

The computer system of claim 12, wherein the predetermined threshold quantity is 1, 2, 3, 4, or 5.

### Claim 15 (depends on 12)

The computer system of claim 12, wherein generating the data item cluster based on the data clustering strategy further comprises:
determining any new subjects or new senders associated with email data items of the data item cluster that are different from the determined subjects or senders;
identifying a second one or more of the plurality of email data items having a subject that is the same as the determined new subject, or a sender that is the same as the determined new sender; and
adding the identified second one or more email data items to the data item cluster.

### Claim 16 (depends on 12)

The computer system of claim 12, wherein the identified one or more email data items are added to the data item cluster only if they were received by an initial recipient within a period of time determined based on the seed.

### Claim 17 (depends on 16)

The computer system of claim 16, wherein the period of time comprises at least one of a number of hours, a number of days, or a number of weeks, and wherein the received email data item designated as the seed was received by an initial recipient within the time period.

### Claim 18 (depends on 16)

The computer system of claim 16, wherein the period of time is further determined based on other email data items in the data item cluster.

### Claim 19 (depends on 12)

The computer system of claim 12, wherein generating the data item cluster based on the data clustering strategy further comprises:
identifying additional one or more data items associated with any data items of the data item cluster; and
adding, to the data item cluster, the additional one or more data items.

### Claim 20 (depends on 12)

The computer system of claim 12, wherein the one or more hardware computer processors are further configured to execute the plurality of computer executable instructions in order to cause the one or more hardware computer processors to:
continuously receive email data items from customers of the organization, store the received email data items, designate the received email data items as seeds, and generate, for each of the designated seeds, data items clusters based on the data clustering strategy.