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Oracle® Fusion Middleware Administrator's Guide for Oracle Adaptive Access Manager
Release 11g (11.1.1)

Part Number E14568-06
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C Conditions Reference

This appendix provides information about the conditions available standard on Oracle Adaptive Access Manager.

Table C-1 OAAM Conditions

Condition Name Condition Description

Always On - User

This rule is always processed

Device: Browser header substring

Checks to see if the supplied string exists as a substring in the browser's header information

Device: Device in list

Checks to see if the device is in the list

Device: Device first-time for user

Checks to see if the device is used for the first time by the user

Device: Excessive use

Device is excessively used that has not been used before

Device: Is registered

Checks to see if the user has registered the device

Device: Login Count

Checks to see if unique user count using this device in past "x" seconds

Device: Timed not status

Maximum login attempts for all but the given status within the given time period

Device: Used count for user

Device used count. This condition ignores the current request for calculating the device count.

Device: User status count

Checks user count with the given status from this device in the specified duration

Device: Velocity from last login

Triggers when miles per hour is more than specified value

Device ID: Cookie state

Checks the cookie state for the given device and user

Device ID: Cookies match

Tracker node matches for both cookies

Device ID: Header data match

Determines if header data is match

Device ID: Header data match percentage

Determines if header data match percentage is within specified range

Device ID: Header data present

Determines if header data is present

Device ID: Is cookie disabled

Determines if cookie is disabled for the user based on history

Device ID: Is cookie empty

Determines if the cookie value is empty or not empty. Validation check is not included

Device ID: Is cookie from same device

Determines if the HTTP and flash cookies are from the same device. Automatically checks the old nodes if the current node is not found

Device ID: Is cookie old

Determines if the cookie sent is from an old cookie

Device ID: Is cookie valid

Determines if there is a valid node for the given cookie value.

Device ID: HTTP header data browser match

Determines if browser is matched based on HTTP header data

Device ID: HTTP header data browser upgrade

Determines if browser is upgraded based on HTTP header data

Device ID: HTTP header data operating system match

Determines if operating system match based on HTTP header data

Device ID: HTTP header data operating system upgrade

Determines if operating system is upgraded based on HTTP header data. Check is based on versions

Device ID: Known header data match percentage

Determines if the known header data match percentage is within the specified range

User: User ASN first time

Checks to see if the user has used this ASN successfully previously

User: User carrier first time

Checks to see if the user has successfully used this carrier previously

User: User city first time

Checks to see if the user has used this city successfully previously

User: User country first time

Checks to see if the user has used this country successfully previously

User: User IP first time

Checks to see if the user has used this IP successfully previously

User: User ISP first time

Checks to see if the user has used this ISP successfully previously

User: User state first time

Checks to see if the user has used this state successfully previously

Device ID: User used this fingerprint

Checks to see if the user has used this fingerprint previously

Entity: Entity is a member of the pattern bucket for the first time in a certain time period

Condition to find out whether this entity is member of the pattern bucket for the first time in a certain time period

Entity: Entity is a member of the pattern bucket less than some percent with all other entities involved

Checks to see if this entity has been a member of this pattern bucket based on percent basis, taking into account all other entities

Entity: Entity is a member of the pattern less than some percent times

Checks to see if this entity has been a member of this pattern condition based on percent basis

Entity: Entity is a member of the pattern N times

Checks to see if this entity has been a member of this pattern condition

Entity: Entity is a member of the bucket N times in a given time period

Checks to see if this entity has been a member of this bucket. You can compare if this entity has been belonging to this bucket before

Location: ASN in group

Checks to see if the ASN for the current IP address is (or is not) in the ASN group

Location: Domain in group

Checks to see if the second-level domain is in the group

Location: In carrier group

If the IP is in the given carrier group

Location: City in group

If the IP is in the given city group

Location: IP connection speed in group

Checks to see if the IP connection speed is in the group

Location: IP connection type in group

Checks to see if the IP connection type is in the group

Location: IP connection type

The connection type for the IP. The type could be DSL, Cable, ISDN, Dialup, fixed wireless, mobile wireless, satellite, frame relay, T1/T3, OCx, and others

Location: In Country group

If the IP is in the given country group

Location: IP excessive use

If IP is excessively used that has not been used before

Location: IP in group

If the IP is in the IP group

Location: IP in range group

If the IP is in the IP range specified in an IP range group. The condition checks to see if the IP of the activity belongs to one of the IP ranges specified in the list of ranges

Location: IP is AOL

Checks to see if the IP is from AOL Proxy

Location: IP line speed type

The connection line speed type for the IP. This is categorized into High, Medium, Low, or Unknown

Location: IP Maximum logins

Maximum number of logins using the current IP address within the given time duration. This condition ignores the current request during evaluation of the Max logins count

Location: IP Maximum users

Maximum number of users using the current IP address within the given time duration

Location: IP multiple devices

Maximum number of devices from IP address within the given time duration

Location: IP routing type

The routing type for the IP. The type could be fixed/static, anonymizer, AOL, POP, Super POP, satellite, cache proxy, international proxy, regional proxy, mobile gateway, or unknown

Location: IP routing type in group

Checks to see if the IP routing type is in the group

Location: IP type

If IP is valid, unknown, or private

Location: ISP in group

Checks to see if the ISP for the current IP address is (or is not) in the ISP group

Location: State in group

If the IP is in the given state group

Location: Timed not status

Maximum login attempts for all but the given status within the given time period

Location: Top-level domain in group

Checks to see if the top-level domain is in the group

Location: User status count

Checks user count with the given status from this location in specified duration

Session: Check parameter value

Checks to see if specified parameter value is more than specified value

Session: Check parameter value for regular expression

Checks to see if specified parameter value matches regular expression

Session: Check parameter value in group

Checks to see if specified parameter value is in group

Session: Check string parameter value

Compares string value

Session: Check two string parameter values

Compares two parameters string values

Session: Check value in comma-separated values

Checks to see if specified value is present in the comma-separated value list

Session: Compare two parameter values

Compares two parameter values

Session: Compare with current date time

Compares specified parameter value with current time

Session: Cookie mismatch

Checks to see if there is a mismatch between the supplied cookie and the expected cookie

Session: IP changed

IP address is changed since transaction is started

Session: Mismatch in browser fingerprint

Checks to see if there is a mismatch between the browser fingerprint and the fingerprint supplied during authentication. The fingerprint is constructed using the context values passed to the rules engine

Session: Time Unit

Checks to see if the current time unit matches the specified time unit criteria

System: Check Boolean Property

Checks system property

System: Check if enough pattern data is available

Checks if enough profiling data is available for given pattern. This condition will check if pattern data is available in the system for last several days.

System: Check if enough data is available for any pattern

Check if enough profiling data is available for any pattern. This condition will check if pattern data is available in the system for last several days.

System - Check Int Property

Check system property

System - Check Model Maximum Score

Checks the model's maximum score

System - Check Model Minimum Score

Checks the model's minimum score

System - Check Request Date

Checks request date

System - Check String Property

Check system property

System - Evaluate Policy

Process the policy as rule and evaluate results

Transaction: Check Count of any entity or element of a Transaction using filter conditions

Checks count of any entity or element of a transaction using filter conditions

Transaction: Check if consecutive transactions in given duration satisfy the filter conditions

Checks to see if consecutive transactions in given duration that satisfy the filter conditions

Transaction: Check current transaction using the filter conditions

Checks current transaction using filter conditions

Transaction: Check transaction aggregrate and count using filter conditions

Checks transaction aggregrate and count using filter conditions

Transaction: Check transaction count using filter conditions

Checks transaction count using filter conditions

Transaction: Check Unique Transaction Entity Count with the specified count

Checks unique transaction entity count with the specified count

Transaction: Compare transaction aggregrates (Sum/Avg/Min/Max) across two different durations

Compares transaction aggregrates (Sum/Avg/Min/Max) across two different durations

Transaction: Compare transaction counts across two different durations

Compares transaction counts across two different durations

Transaction: Compare transaction entity or element counts across two different durations

Compares transaction entity or element counts across two different durations

User: Account Status

Account status of the user

User: Action Count

Checks action counter for the given action. This condition has a dependency on action configuration

User: Action Count Timed

Checks to see if the given action count is more than the specified count. If runtime is not specified, the action is checked in all runtimes

User: Action Timed

Maximum number of actions in the past x seconds

User: User Agent Percentage Match

Checks to see if user agent percentage match is above specified percentage. Compares with UAS of previous login from same device

User: ASN first time for user

Is the user using this ASN for the first time

User: Authentication image assigned

Checks to see if an authentication image is assigned to the user

User: Authentication Mode

Check user authentication mode

User: Challenge Channel Failure

If a user has a failure counter value more than a specified value from specific channel

User: Challenge Failure

If a user has a failure counter value more than a specified value for more than a specific time

User: Challenge Maximum Failures

Checks to see if user failed to answer challenge question for specified number of times

User: Challenge Questions Failure

Checks how many questions have failures

User: Challenge timed

Checks to see if user answered challenge question successfully in last n days

User: Check first login time

Checks to see if the user first logged in within range. First login is the first successful login

User: Check information

Checks to see if the user information is set. Information data to check is sent as a key value pair

User: Check login time

Checks to see if user login time is within the specified time

User: Check Last Session Action

Checks to see if the given action is in the last session. If runtime is not specified, the action is checked in all runtimes of that session

User: Check login count

Checks user login count within specified duration

User: Check login time

Checks to see if user login time is within the specified time

User: Check OTP failures

Checks to see if user's OTP failure counter value is more than a specified value

User: Check User Data

Checks User Data for the given key

User: City first time for user

Is the user using this city for the first time

User: Client and Status

Account status of the user

User: Country failure count for user

Check failure count for the user from the given country

User: Country first time from list

If this country is used for the first time by this user from the given country list

User: Country first time for user

Is the user using this Country for the first time

User: Devices

Number of devices tried in given time

User: Distance from last successful login

Distance from last successful login within specified time

User: Distance from last successful login within limits

Checks to see if distance from last successful login within specified time is within in limits

User: Image Status

Image status of the user

User: In Group

If the user is in the given group

User: IP carrier first time for user

Is the user using this IP carrier for the first time

User: Is last IP match with current IP

Checks to see if user login IP address matches with that of previous login

User: Is User Agent Match

Checks to see if user agent matches with that of previous login from same device

User: Last login

Last login within specified time

User: Last login status

Checks to see if user login status is in specified list

User: Location Used Timed

If user used this location within the given time period

User: Login first time for user

Checks to see if user is logging in for the first time

User: Login In group

If the user login is in the given group

User: Login time between specified times

Login time between specified time

User: Max Countries

Number of countries within the given time period

User: Max IPs Timed

Max number of IPs within the given time period

User: Max Locations Timed

Max number of locations within the given time period

User: Max Cities

Number of cities within the given time period

User: Max States

Number of states within the given time period

User: Multiple failures

User failed multiple times

User: Phrase Status

Phrase status of the user

User: Preferences Configured

Checks to see if the user preferences are set

User: Question Status

Question status of the user

User: Runtime score

Checks to see if the score is within limits

User: Stale session

Checks to see if there is newer login after current login session is established.

User: State first time for user

Is the user using this State for the first time

User: Status Count Timed

User attempted multiple log ins in specified time

User: User Agent Percentage Match

Checks to see if user agent percentage match is above the specified percentage. Compares with UAS of previous login from same device

User: User Group in List

If the user group is in the given list

User: User is member of pattern N times

Checks to see if this user has been member of this pattern condition

User: Velocity from last successful login

Velocity from last successful login

User: Velocity from last successful login within limits

Triggers when velocity from last successful login is within specified limits


C.1 Descriptions

This chapter focuses on device, autolearning, location, transaction, in-session, system, and user conditions.

The appendix is organized as follows:

C.1.1 Device Conditions

These section provides information on the following device conditions:

C.1.1.1 Device: Browser Header Substring

Condition DEVICE: Browser header substring
Description Checks whether the supplied string exists as a substring in the browser's header information. The string comparison is performed by ignoring the case (uppercase or lowercase) of the strings.
Prerequisites  
Assumptions The rule is configured through a policy.
Available since version Pre-10.1.4.5
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
subString Substring to be checked with the string present in the browser.   Yes

C.1.1.2 Device: Device First Time for User

Condition DEVICE: Device firsttime for user
Description Checks to see if the user is using this device for the first time. Note that "device" is the combination of the physical device and the browser in most of the test scenarios. Check the page of the recent login to determine the Device ID associated with the login sessions to verify the rule. The user's current (session) device is also counted if is found to be used for the first time.
Prerequisites The rule should be configured through a policy.
Assumptions  
Available since version Pre-10.1.4.5
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
is Boolean that checks if the condition should return true or false if the user is using this device for the first time true (default) or false Cannot be Null.

Possible User Scenarios

This condition could potentially be used to determine if the user is logging in from a different device or different devices and to challenge him when it is the case.

C.1.1.3 Device: In Group

Condition DEVICE: In Group
Description Checks to see if the device is in the specified list.
Prerequisites A list defined already which has devices (IDs) as members.

You should have this rule configured through a policy.

Assumptions  
Available since version 10.1.4.5
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
isInList This is a boolean parameter that defines the default return value if the device is in the list. True / [False] Yes.
listId This is the list of IDs of a list of devices. OAAM Admin will display a menu with the possible lists of device lists. Use the Group editor in OAAM Admin to edit the device list.   Yes

Possible User Scenarios

This condition can be potentially used to determine if the device of the current activity belongs to a particular list of devices.

For example,

  • You may want to block users logging in from the device that is considered "compromised."

  • You may not want users to perform certain activities if they are logging in from a device that is a kiosk.

C.1.1.4 Device: Excessive Use

Condition DEVICE: Excessive Use
Description Checks to see if this device is used excessively. Basically, checks to see if a device was not active for several days and suddenly a large number of users are logging in from the same device in a short period (in a few hours). This condition can be potentially used to track the compromised device of automated programs that obtained access to the code and then tries to log in several users.
Prerequisites You should have this rule configured through a policy.
Assumptions  
Available since version 10.1.4.5
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
userCount Number of users logging in from a single device in a short period. positive integers No
withInHours This parameter defines the short period in which OAAM must find excessive use. positive integer No
notInDays This parameter describes the number of days the device was not in use. positive integer No

Possible User Scenarios

This condition can be potentially used to determine if the device used in the current activity is compromised. For example, you might have certain devices that are deemed as compromised and you may want to block users logging in from them. For example, an individual could be "hacking" into a bank computer and then trying to perform various activities. Typically, activity logging should be set up for that computer for several days.

C.1.1.5 Device: Is Registered

Condition DEVICE: Is registered
Description Condition checks to see if the device where that the user is logging in is registered for the user.
Prerequisites You should have this rule configured through a policy.
Assumptions  
Available since version 10.1.4.5
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
is Boolean parameter to decide if the default return value should be true or false if the device is registered. [True] / False Yes

Possible User Scenarios

This condition can be used to identify if the user is logging in from a device that he has not registered before. This can basically prevent a fraud where the user's login information is stolen and the thief tries to log in using the user's login information from another otherwise safe location.

C.1.1.6 Device: User Count

Condition DEVICE: User count
Description Check to see if this device is used by several unique users in the last few seconds. This can potentially be fraud since if this condition is true then it will be potentially a compromised device or compromised login information for a number of users.
Prerequisites You should have this rule configured through a policy.
Assumptions  
Available since version 10.1.4.5
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
numberOfUsers Number of users logging in from the same device in a short period. positive integers No
withinSeconds This parameter defines the short period in which the number of users try to log in to the system using that device. positive integer No

Possible User Scenarios

This condition can be potentially used to determine if the device used in the current activity is compromised. It could be possible that a fraudster had stolen the login information for several users and tried to ruin their accounts. The result is that many users are logging in from the same device in intervals that are a few seconds each.

C.1.1.7 Device: Timed Not Status

Condition DEVICE: Timed not status
Description This condition counts the attempts by users from the same device (the device used in the attempt) in the last few seconds where the authentication status is not the one given in the condition. If this count exceeds the count configured in the condition, then this condition evaluates to true.
Prerequisites You should have this rule configured through a policy.
Assumptions  
Available since version 10.1.4.5
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
status Count the attempts a status that is not equal to this specified status. auth.status.enum (auth.status.enum.success is the default) No
withinSeconds This parameter defines the short period in which the number of login attempts that use that device are counted. positive integer No
attempts Maximum number of attempts to watch for. If the attempt count in Oracle Adaptive Access Manager exceeds this number, then the condition will evaluate to true. positive integer No

Possible User Scenarios

This condition can be potentially used to determine if the device used in the current activity is compromised. A possible fraud scenario can be detected where:

  • An individual (or a automated program) uses the same device to make login attempts and the attempts are either failing or passing based on the data that was stolen.

  • A program is used to break the password in an automated fashion.

In these cases, there are repeated failed login attempts from the same device in a short amount of time.

C.1.1.8 Device: Used Count for User

Condition DEVICE: Timed Not Status
Description This condition counts the attempts by users from the same device (the device used in the attempt) in the last few seconds with an authentication status that is not the one that is specified in the condition. If this count exceeds the count configured in the condition, then this condition evaluates to true.
Prerequisites You should have this rule configured through a policy.
Assumptions  
Available since version 10.1.4.5
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
status Count the attempts with the status that is not equal to this status. auth.status.enum (auth.status.enum.success is the default) No
withinSeconds This parameter defines the short period in which login attempts using that device are counted. positive integer No
attempts Maximum number of attempts to watch for. If the attempt count exceeds this number then the condition will evaluate to true. positive integer No

Possible User Scenarios

This condition can be potentially used to determine if the device used in the current activity is compromised.

Possible fraud scenarios that can be detected are:

  • An individual (or an automated program) is using same device to make login attempts and the attempts are either failing or passing based on the data that was stolen

  • A program is trying to break the password for user in automated fashion

In these cases, repeated failed login attempts are made from the same device in a short period.

C.1.1.9 Device: Velocity from Last Successful Login

Condition DEVICE: Velocity from Last Successful Login
Description Condition evaluates if the user's velocity in miles per hour is more than the specified value. The location database is used to determine the location of the user for this login and previous login. It takes into account the current session as well. Note that the velocity calculation is dependent on the accuracy of the location data.
Prerequisites This rule is configured through a policy. Location database should be loaded for the rule.
Assumptions Location database is loaded.
Available since version 10.1.4.5
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
milesPerHour Positive number that indicates the user's speed in miles per hour. If the condition determines that the user has traveled faster than this value, then condition will evaluate to true. positive integer (default = 60) No
sinceSeconds Positive integer that specifies the time difference between this login and last successful login to calculate user's velocity. positive integer (default = 172800 which is 48 hours) No
Exclude IP List This parameter allows you to specify a list of IPs to ignore. If a user's IP is from that list, then this condition always evaluates to false. If the user's IP is not in that list or if the list is null or empty, then the condition evaluates the velocity of the user or the device from the last login and evaluates to true if the velocity exceeds the configured value.    

Possible User Scenarios

This condition can be used to determine the users' location and the risk it poses because of changes in the user's login location between the time of the current login and the last successful login.

Examples are shown below:

For a case with a user traveling by ground transportation, you can configure this rule so that 60 is the value for miles per hour and the time is in seconds for the last successful login (use default values).

Another case involves users traveling on air transport. You can use different values (for example, 500 miles an hour) to ensure that login locations and speed are within reason.

Note:

Be aware that the velocity calculation depends highly on location databases.

C.1.2 Autolearning Conditions

The section provides information on the following autolearning conditions:

C.1.2.1 Entity: Entity is Member of Pattern Bucket for the First Time in Certain Time Period

Condition Entity: Entity is Member of Pattern Bucket for the first time in Certain Time Period
Description Condition to find out whether this entity is member of a pattern bucket for the first time in a certain time period. First time is a relative function. So if you want to track the first time for the membership, then in rule configuration use "Years" as the "Time period type for bucket membership" and specify a long time such as 5 years or so for the "Time period for bucket membership."
Prerequisites You should have entities and patterns defined before you try to add this to rule / policy.
Assumptions Autolearning is enabled.
Available since version 10.1.4.5
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
Pattern Name Name of the pattern for which the "first time" bucket is to be checked.   Cannot be null.
Is Evaluate this condition to true if this parameter is true and "first time" bucket is true.   Cannot be null
Time period type for bucket membership The time period type (hours, days, months, and years) One of wotk.type.enum. That is (hour, day, month, year) Cannot be null.
Time period for bucket membership The time period over which the pattern membership is evaluated. The units of time Positive number. (Use numbers that would be valid for the time period type). Use 0..24 for hours, use 1 through 12 for months, 1 through 31 for days, and 1 through 8 for years. Cannot be null
Member type for pattern-bucket membership The member type (user, device, location, city, country) Type for members applicable for that transaction. For authentication type it is one of user, device, IP, city, state, country. Cannot be null.
First time count The count of occurrences to compare against If you are using this rule in a Pre-Authentication (or pre-transaction) scenario, then use a value of 0 since autolearning takes place on the trailing edge of authentication or transaction. For all other checkpoints, use a value of 1 for this parameter. (1 is also a default value) Cannot be null

Possible User Scenarios

Examples of how to use this condition are:

  • To develop first time rules. For example, define a user (city for each) pattern and attach this pattern to this condition-based rule in a policy, so that when the user logs in from a city the first time, the rule will be triggered.

  • To challenge users when they are performing an action for the first time in transactions. For example user tried to perform a bill transfer of 5000 dollars. This can be achieved using a pattern that has user and the transaction amount ranges 1..100, 1000...10000 and so on.

C.1.2.2 Entity: Entity is Member of Pattern Less Than Some Percent Time

Condition Entity: Entity is member of pattern less than some percent times
Description Condition to find out whether this entity is member of the pattern bucket for less than a certain percent in a certain time period.This condition checks the pattern membership percentage against the pattern usage of the same entity. With this condition, the entity's membership count for percentage is counted and not the number of entities that belong to that pattern.
Prerequisites You should have entities and patterns defined before you try to add this to rule / policy.
Assumptions Autolearning is enabled.
Available since version 10.1.4.5
Checkpoints All checkpoints

Parameters

Parameter Description Possible Values Can be Null?
Pattern Hit Percent less than Percent hit count of the pattern that will be used for comparison Make sure you pass "good" values. Providing values in decimal points is not recommended since the percentage values may be a Double type of values when calculated over a large number of login and pattern usage combination. For example, do not enter 10.45362. Instead enter 10.5 or 10 or 11. Cannot be null
Pattern name for membership Name of the pattern for which the membership count is to be checked.   Cannot be null
Is Membership Count Less than patternHitPercent Evaluate this condition to true if this parameter is true and the pattern percent is less than the given value   Cannot be null
Time period type for pattern membership The time period type (hours, days, months of years) One of wotk.type.enum. That is (hour, day, month, year) Cannot be null.
Time period for pattern membership The time period over which the pattern membership is to be evaluated; the units of time Positive number. (Use valid numbers depending on time period type). Use 0..24 for hours, use 1 through 12 for months, 1 through 31 for days, and 1 through 8 for years. Cannot be null
Member type for pattern membership The member type (user, device, location, city, country) Type of members applicable for that transaction. For authentication type, it is one of user, device, IP, city, state, country. Cannot be null.

Possible User Scenarios

This can be most effectively used in tracking the user's habits. For example, if the user usually logs in from a certain state and he starts logging in from other states also. In that case, he will be challenged on the first few times he logs in from those states since the percentage for those state will be lower than 10% (if 10 was entered as the Pattern Hit Percent less than). User (for each state) pattern can created for use in tracking the user's logins from different cities.

C.1.2.3 Entity: Entity is Member of Pattern Less Than Some Percent with All Entities in Picture

Condition ENTITY: Entity is member of pattern bucket less than some percent with all entities in picture
Description Condition to find out whether the entity is a member of a pattern bucket some percent of time as compared to all other entities that have been member of this pattern.

This condition considers all the other entities; therefore performance is affected more than for simpler conditions.

Prerequisites You should have entities and patterns defined before you try to add this to rule/policy.
Assumptions Autolearning is enabled.
Available since version 10.1.4.5
Checkpoints All checkpoints

Parameters

Parameter Description Possible Values Can be Null?
Pattern bucket hit percent less than Percent hit count of the pattern that will be used for comparison Try to use a sensible number. Use 10 or 11 in place of 10.7623591 as an example. Cannot be null
Pattern name for membership Name of the pattern for which bucket percentage is checked.   Cannot be null.
Is Membership Count Less than patternHitPercent Evaluate this condition to true if this parameter is true and percentage is less than the specified percentage.   Cannot be null
Time period type for pattern membership The time period type (hours, days, months of years) One of wotk.type.enum. That is (hour, day, month, year) Cannot be null.
Time period for pattern membership The time period over which the pattern membership is to be evaluated. Units of time. positive number. (Use valid numbers for the time period type). Use 0..24 for hours, use 1 through 12 for months, 1 through 31 for days, and 1 through 8 for years. Cannot be null
Member type for pattern membership The member type (user, device, location, city, country) Type of members applicable for that transaction. For authentication type it can be user, device, IP, city, state, or country. Cannot be null.

Possible User Scenarios

This condition can be used to find out whether users are performing actions that are not consistent with the action of other users. For example, a user is logging in from a city that most users do not log in from usually.

Non-popular states, cities, IPs, and others can be enforced using these condition.

C.1.2.4 Entity: Entity is Member of Pattern N Times

Condition ENTITY: Entity is member of pattern N times
Description Condition to find out whether this entity is a member of the pattern "n" number of times.
Prerequisites You should have entities and patterns defined before you try to add this to rule / policy.
Assumptions Autolearning is enabled.
Available since version 10.1.4.5
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
Pattern hit count more than Hit count of the pattern that will be used for comparison. If hit count for the pattern is more than this value, then the condition returns true. For Pre-Authentication execution, set the count one less than what you want the rule to trigger on. Cannot be null
Pattern name for membership Name of the pattern for which the membership count is to be checked.   Cannot be null.
Is Membership Count More than patternHitCountForUser Boolean value that is used to return true or false from the condition. It works as follows:

if (isMoreThan == true) and (hitCountMorethan returned true)

then condition evaluates to true.

ELSE if (isMoreThan == false) and (hitCountMorethan returned false)

then condition evaluates to false. and condition evaluates to false in all other cases.

  Cannot be null
Time period type for pattern membership The time period type (hours, days, months of years) One of wotk.type.enum. That is (hour, day, month, year) Cannot be null
Time period for pattern membership The time period over which the pattern membership is evaluated. Units of time positive number. (Specify valid values for the time period type). Use 0 through 24 for hours, 1 through 12 for months, 1 through 31 for days, and 1 through 8 for years. Cannot be null
Member type for pattern membership The member type (user, device, location, city, country) Type of members applicable for that transaction. For authentication type, the type can be user, device, IP, city, state, and country. Cannot be null.

Possible User Scenarios

Condition can be used to find out whether the user has performed a particular operation a few times and the operation is well defined. For example if user logged in from a group of IP that are tagged as anonymizer. If user logs in like that a few times, a policy can be configured to take an action.

C.1.2.5 Entity: Entity is Member of Pattern N Times in a Given Time Period

Condition ENTITY: Entity is member of bucket N times in a given time period
Description Condition to find out whether this entity has been a member of the bucket several times in a given time period. This condition can be used to check the current behavior against the pattern. Note that this is a count-based condition. So, if you configure to trigger it, for example, for a count less than three, it will trigger on the first login that matches the pattern.
Prerequisites Ensure that the following prerequisites are met:
  • 10.1.4.5.2 or later must be installed.

  • Entities and patterns must be defined before adding this condition to rules/ policies.

Assumptions Autolearning is enabled.
Available since version 10.1.4.5.2
Checkpoints All checkpoints

Parameters

Parameter Description Possible Values Can be Null?
Pattern name for membership Name of the pattern for which the bucket membership is to be checked. In the Rule's Condition tab, select the pattern from a drop-down of active patterns that will be presented.   Cannot be null.
Time period for bucket membership The time period over which the bucket membership is to be evaluated. This is in units of time. Use 1 through 23 for hours. 1 through 30 for days. 1 through 12 for months and 1 through 8 for years. Server will use the use the max values if you enter values more than the above specified. Cannot be null
Time period type for bucket membership The time period Type (hours, days, months of years) One of workflow.type.enum. That is (hour, day, month, year) Cannot be null
Member type for pattern membership The member Type (user, device, location [city, state, country], IP) It is one of the type of members applicable for that transaction. For authentication type it is one of user, device, IP, city, state, country. Cannot be null
Bucket hit count The number of request for the application which will be compared against. Hit count for the bucket and the compare operator used in Entity: Entity is Member of Pattern N Times in a Given Time Period evaluate the outcome of the condition together. For Pre-authentication execution set the count one less than what you want the rule to trigger on. Cannot be null
Compare operator for the count Comparison operator to be used for comparing the count in the system with bucketHitCountForEntity. For example if you specified the compare operator as "Less Than" and bucket hit count as 3, the condition will evaluate to true as long as hit count for that bucket is less than 3 for that authentication. Possible values are from enum bharosa.numeric.eval.operator.enum

equal_to

not_equal_to

less_than

less_than_or_equal_to

more_than

more_than_or_equal_to

are the possible values.

Cannot be null.
Return value if condition is true Value to return if the condition evaluates to true. If condition does not evaluate to true then opposite of the success value will be returned. True / False Cannot be null
Return value if condition encounters an error This is the value that will returned if the condition execution runs into issue. Possible errors might be that the pattern is not active, the parameters that were passed (configured) are incorrect or they do not have the values in the expected range. True / False Cannot be null.

Possible User Scenarios

This condition can be used to find out whether the user performed a particular operation a few times that was well defined. For example, if a user logged in from a city for a few times, the information can be used to challenge the user for the first few times.

C.1.3 Location Conditions

These section provides information on the following location conditions:

C.1.3.1 Location: ASN in Group

Condition LOCATION: ASN in group
Description Checks to see if the ASN for this IP location is in the group of ASNs that might be of interest. ASN is autonomous system number.
Prerequisites There should a list of ASNs already defined. You should have this rule configured through a policy.
Assumptions  
Available since version  
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
Is in group This is a boolean parameter that defines a default return value if the ASN is in the group. [True] / False Yes.
ASN in ASN group This is a list of ASN groups. The Rule's Conditions tab will display a menu of possible ASNs groups to for this parameter. Use Group editor in OAAM Admin to edit the ASN group.   Yes

Possible User Scenarios

This condition can be potentially used to determine if the ASN of the current activity (IP) belongs to a particular group of ASNs. For example you might have certain ASNs those can be deemed as dangerous and you may want to block users logging in from there. Or you might not want users to perform certain activity if they are logging in from an ASN that is from a particular country or region.

C.1.3.2 Location: IP in Range Group

Condition LOCATION: IP in Range group
Description Checks whether the IP of the current activity belongs to a list of IP-ranges specified.
Prerequisites There should a group defined already which has IP-ranges as members. You should have this rule configured through a policy.
Assumptions  
Available since version 10.1.4.5.1
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
Is IP in IP-range group Use this parameter to indicate a default return value. If the IP belongs to one of the IP ranges, and this parameter is set to true, condition will evaluate to true. If IP belongs to IP range and the parameter is set to false, the condition will return false [True] / False Yes.
IP range group Specify the group that contains the IP ranges. Condition checks if the IP belongs to one of the ranges from this group.   Yes

Possible User Scenarios

This condition can be potentially used to determine if the IP of the current activity belongs to one of several ranges of IPs that may be of interest. For example you might have ranges of IPs from a particular subnet and you might want to take action if that is the case.

C.1.3.3 Location: In Country Group

Condition LOCATION: In Country group
Description Checks whether the IP belongs to a given country group.
Prerequisites There should a group defined already which has countries as members. You should have this rule configured using a policy.

IP location data is useful for this condition. (Most production environments will have application database populated)

Assumptions  
Available since version  
Checkpoints All Checkpoints.

Parameters

Parameters Description Possible Value Can be null?
Is in group This is a boolean parameter that defines a default return value if the country is in country group. [True] / False Yes.
Country in country group This is a list of group of countries. The Rule's Condition tab will display a drop-down of possible groups.

Use the Group editor in OAAM Admin Console to edit the group.

(java Long values) Yes

Possible User Scenarios

This condition can be potentially used to find out if the current activity seems to originate from one of several countries of interest. For example you might have a list of countries and if the current IP used for the activity belongs to one of those countries, then you can configure the policy to take an action or generate an alert.

C.1.3.4 Location: IP Connection Type in Group

Condition LOCATION: IP Connection type in group
Description Find out whether the connection type of this IP location is in the group of connection types that might be of interest.
Prerequisites There should a list of connection types already defined. You should have this rule configured using policies.
Assumptions  
Available since version  
Checkpoints All Checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
Is in group This is a boolean parameter that defines a default return value if the IP's connection type is really in connection type group. [True] / False Yes.
Connection type in group This list of connection type groups. The Rule's Condition tab will display a drop-down of possible lists of connection types. Use group editor in administration user interface to edit this group list.   Yes

Possible User Scenarios

This condition can be used to find out whether the IP of the current activity comes from a connection type that can be of particular interest to determine fraud. For example, you might have connection type of "satellite link."

C.1.3.5 Location: IP Line Speed Type

Condition LOCATION: IP line speed type
Description Checks whether the current IP has connection line speed as one of the specified connection speed. This (connection speed) is categorized into High, Medium, Low or Unknown
Prerequisites You should have this rule configured using a policy. IP location data is useful for this condition. (Most production environments will have IP location database populated)
Assumptions  
Available since version  
Checkpoints All Checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
is This is a boolean parameter that defines a default return value if the connection speed is the one specified. [True] / False Yes.
speed type This is the enumeration value that indicates connection speed type. This (connection speed) is categorized into High, Medium, Low or Unknown

The enum that is used for this parameter is location.linespeed.enum

(Integer) Default value is location.linespeed.enum.low Yes

Possible User Scenarios

This condition can be used potentially to find out whether the current activity seems to originate from an IP that has a particular speed type. For example, you may want an alert generated if the speed type is high for the user who usually logs in from a dial-up network.

C.1.3.6 Location: IP Routing Type in Group

Condition LOCATION: IP Routing Type in group
Description Checks to see if the IP Routing Type is in the group.
Prerequisites There should a group defined already which has routing types as members. You should have this rule configured using a policy. IP location data is useful for this condition. (Most production environments will have IP location database populated)
Assumptions  
Available since version  
Checkpoints All Checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
Is in group This is a boolean parameter that defines a default return value if the IP routing type is in group. [True] / False Yes.
Routing type in group This is a list of groups of IP routing types. A drop-down of possible lists of IP routing type groups. Use the Group editor in OAAM Admin to edit this group list. (java Long values) Yes

Possible User Scenarios

This condition can be potentially used to find out whether the current activity is from an IP that belongs to a particular routing type. For example, you might have a list of routing types that can potentially lead to fraud and if the current IP of the activity has one of those routing types, you can configure to take an action or generate an alert.

C.1.3.7 Location: In Carrier Group

Condition LOCATION: Carrier in group
Description Checks to see if the IP is in the given carrier group
Prerequisites There should a list of carriers already defined. You should have this rule configured using a policy. Location data is helpful for the condition.
Assumptions  
Available since version  
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
Is in group This is a Boolean parameter that defines the return value if the carrier is in group or not. [True] / False Yes.
IP in carrier group This is a list of the groups of carriers. The Rule's Condition tab displays drop-down of possible lists of carriers groups to configure for this parameter. Use the Group editor in OAAM Admin Console to edit carrier group.   Yes

Possible User Scenarios

This condition can be potentially used to check to see if the carrier of the current activity (IP) belongs to a particular list of carriers. For example you might have certain carriers that can be deemed as "dangerous" (hackers stole all of a carrier's phone numbers recently) and you may want to block users logging in from a carrier, or you might not want users to perform a certain activity if they are logging in from a carrier that is from a particular country or region.

C.1.3.8 Location: IP Maximum Users

Condition LOCATION: IP Maximum Users
Description Condition checks to see if the maximum number of distinct users using the current IP address within the given time duration exceeds the configured condition attribute value. Notice that the current request is also counted in finding the number of unique users from the IP.
Prerequisites You should have this rule configured using a policy.
Assumptions  
Available since version  
Checkpoints All Checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
Seconds elapsed This is the time period in which the number of users from this IP is to be counted. integer [Default = 300] No
The maximum number of users Maximum number of users allowed. integer [Default = 5] No

Possible User Scenarios

Use this condition to find out if a particular IP is used by fraudsters to perform logins / transactions by using different login IDs they have stolen. In such cases you see a number of different logins from the same IP during a relatively short period.

C.1.3.9 Location: Is IP from AOL

Condition LOCATION: Is IP from AOL
Description Find out whether the IP is from AOL proxy
Prerequisites You should have this rule configured using a policy to test it.
Assumptions  
Available since version  
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
Is AOL This is the default return value is IP is indeed from AOL. If the IP is not from AOL then opposite of this attribute is returned. Boolean [true] / false No

Possible User Scenarios

This condition can be used to figure out if the IP is from an AOL proxy. Customers may want to set up the system to take certain actions for users logging in from AOL.

C.1.3.10 Location: in City Group

Condition LOCATION: in city group
Description Checks whether the current activity belongs to a given city group.
Prerequisites There should a group defined already which has cities as members. You should have this rule configured using a policy. IP location data is useful for this condition. (Most production environments will have IP location database populated)
Assumptions  
Available since version  
Checkpoints All Checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
Is in group This is a Boolean parameter that defines a default return value if the city is really in country group. [True] / False Yes.
City in city group This is a list of city groups. The Rule's Conditions tab displays a drop-down of possible groups of cities. Use Group editor in OAAM Admin Console to edit this group list. (java Long values) Yes

Possible User Scenarios

This condition can be used to figure out if the current activity seems to originate from one of several cities of interest. For example you might have a list of cities and if the current IP of the activity occurs in one of those cities, you can configure the system to take an action or generate an alert.

C.1.4 Transactions Conditions

These section provides information on the following transaction conditions:

Note:

The filter operators "like" and "not like" work only on transaction data and entity data where the data type is string.

C.1.4.1 Transaction: Check Current Transaction Using Filter Condition

Condition TRANSACTION: Check Current Transaction Using Filter
Description Check to see whether the current transaction matches ALL the conditions specified. Up to 6 conditions can be specified.
Prerequisites
  1. Transactions should be defined.

  2. Transaction type of the current transaction should be the same as the transaction type specified in the rule condition

Assumptions If there are multiple transactions in the current session, then this condition is applied on the last transaction
Available since version 10.1.4.5.1
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
trxDefKey Transaction type of the transaction to be counted. It represents the Transaction Definition fully qualified key. This is specified using the list box that has the list of transaction definitions   No
filter1Key

filter2Key

filter3Key

filter4Key

filter5Key

filter6Key

These parameters specify the left hand side of the filter conditions. The left hand side represents the fully qualified key of the transaction field.

This field could be an entity field or data field or transaction attribute or request attribute.

  Yes
filter1Condition

filter2Condition

filter3Condition

filter4Condition

filter5Condition

filter6Condition

These parameters represent the operator and right hand side of the filter condition. The operator and the right hand side represent the fully qualified key of the filter condition.

The right hand side is the value, which could be a simple value, the value of the current transaction, or a group.

  • Value: A simple value that is entered into a field

  • Current: A value from the current transaction. A value is selected from a list of values based on the current entities.

  • Group: Group is automatically selected if you chose the condition as IN or NOT IN. After Group is selected, you will have to select a type of group. Then, based on type, a list box appears with other values to select from, and so on.

  Wherever the filterKey is specified, an appropriate condition has to be specified

Possible User Scenarios

This condition can be used whenever you want to trigger a rule based on checks on the current transaction.

For example, you have configured a transaction called purchase and you want to trigger a rule whenever the amount field of the purchase transaction is greater than $1000 and country is in the list of High Risk countries (that you have configured).

Dollar amounts must be integer values.

For achieving this, you must use this rule with two filter conditions: one for checking if the amount field is greater than 1000 and the second filter condition for checking if the country of the current session is in the list of High Risk countries.

This condition can be used to specify up to six (6) filter conditions on the current transaction.

C.1.4.2 Transaction: Check Transaction Count Using Filter Condition

Condition TRANSACTION: Check Transaction Count Using Filter
Description Check the transaction count with a specified value. You can specify the criteria for the transaction to be counted using the filter conditions (up to 6 conditions) and you can also specify the other parameters like the duration to be considered and the transaction status to consider and so on.
Prerequisites
  • Transactions should be defined.
  • Transaction type of the current transaction should be same as the transaction type specified in the rule condition

Assumptions If there are multiple transactions in the current session, then this condition is applied on the last transaction
Available since version 10.1.4.5.1
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
trxDefKey Transaction type of the transaction to be counted. It represents the Transaction Definition fully qualified key. This is specified using the list box that has the list of transaction definitions   No
specifiedConditionEnumForCount Operator to be applied for the count condition. Specify greater than, greater than or equals, less than, less than or equals   No
specifiedValueForCount Transaction count numeric value to check   No
durationDescriptor Specify the duration during which the transactions have to be counted. The duration descriptor enables you to specify the duration.

Important: By default, durationType is "rolling," meaning it takes the current time as the end point to count backward to the start point.

Whenever the duration is described as "last" x seconds/minutes/hours/days, the rolling type duration has to be used.

So if you specify 1 day using "rolling" durationType, the "rolling" day starts 24 hours (exactly 1 day) from the current time. For example, if it is 11:33 am, and you specify 1 day, the "rolling" day will start from 11:33 am of the previous day and end at the current time today.

There will be occasions where you want to have the duration window start at 0.00. For those occasions, you should use the durationType as "calendar".

So if you specify 1 day using "calendar" as the durationType, the "calendar" day will start at 0.00 (12:00 am) of that day and end at the current time.

Examples of "rolling" and "calendar":

A "calendar" week starts from Sunday regardless of the current day, whereas the "rolling" week starts from 7 days from the current day.

A "calendar" month starts from the 1st of the current month, whereas the "rolling" month starts from the same day of the previous month.

A "calendar" year starts from January 1st of the current year, whereas the "rolling" year starts from the same day of the previous year.

In both the "calendar" and "rolling," the end date/time is the current time. The durationType affects how the startTime of the duration is computed.

The "Before" option is used when you want to skip over an interval of time before you begin counting backward to the start point. For example, if you want to calculate 7 days worth of data, but you do not want the data from the last 7 days, you would specify the interval of time you want to skip. If today is February 6, and you want to look at data from January 17 to the 23rd, you would specify "Before" 15 days.

  No
transactionStatusEnum Specify the transaction status that has to be considered for counting.

Do not specify any status if you want to consider all transactions regardless of their status.

  Yes
ignoreCurrentTransactionInCount Specify if you want to ignore the current transaction (if any) in the count.

If there are multiple transactions and if this is specified as true, only the last transaction is ignored.

  Yes
applyFilterOnCurrentTransaction Specify if you want to check the filter conditions on the current transaction before performing the count.

If the filter conditions fail on the current transaction, then the rule condition is evaluated to false without performing the count.

   
filter1Key

filter2Key

filter3Key

filter4Key

filter5Key

filter6Key

These parameters specify the left hand side of the filter conditions. The left hand side represents the fully qualified key of the transaction field.

This field could be an entity field or data field or transaction attribute or request attribute.

  Yes
filter1Condition

filter2Condition

filter3Condition

filter4Condition

filter5Condition

filter6Condition

These parameters represent the operator and right hand side of the filter condition. The operator and the right hand side represent the fully qualified key of the filter condition.

The right hand side is the value, which could be a simple value, the value of the current transaction, or a group.

  • Value: A simple value that is entered into a field

  • Current: A value from the current transaction. A value is selected from a list of values based on the current entities.

  • Group: Group is automatically selected if you chose the condition as IN or NOT IN. After Group is selected, you will have to select a type of group. Then, based on type, a list box appears with other values to select from, and so on.

  Wherever the filterKey is specified, appropriate condition has to be specified

Possible User Scenarios

Use this condition whenever you want to trigger a rule based on transaction count condition.

For example, suppose you have configured a transaction called "purchase" and you want to challenge the user if the user is performing a lot of purchases (for example more than 2 per hour with amount greater than 1000 for each purchase) from a high risk country, you may want to use this condition.

For achieving this, you must use this rule with the following:

  1. Specify Count condition as "Greater Than Equals."

  2. Specify Count to check as "2."

  3. Specify the duration with durationType as rolling and duration as 1 hour.

  4. Specify false for "Ignore Current Transaction in count?" since you want to consider current transaction in count.

  5. Specify true for "Apply FilterOnCurrentTransaction?" field.

  6. Configure two filter conditions:

    • One for checking if the amount field is greater than 1000.

    • Another for checking if the country of the current session is in the list of High Risk countries.

This condition can be used to specify up to six (6) filter conditions that are applied on transactions that are considered for counting.

C.1.4.3 Transaction: Check Transaction Aggregrate and Count Using Filter Conditions

Condition TRANSACTION: CheckTransactionAggregrateAndCountUsingFilter.xml
Description Check the aggregrate of a numeric field and transaction count. You can specify the criteria for transaction to be counted using the filter conditions (up to 6 conditions) and you can also specify the other parameters like duration to be considered and the transaction status to consider and so on.
Prerequisites Transactions should be defined.

Transaction type of the current transaction should be same as the transaction type specified in the rule condition

Assumptions Aggregrate can be applied only on numeric fields. So the transaction definition should have at least one numeric field.
Available since version 10.1.4.5.1
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
aggregrateFunctionEnum Aggregrate function to check. Available functions are sum, min, max, avg    
elementDefFQKey Numeric element on which aggregrate check has to be performed. It represents fully qualified key of the numeric field. This is specified using list box that has list of all numeric data fields.   No
specifiedConditionEnumForAggregrate Operator to be applied for the aggregrate condition. Specify greater than, greater than or equals, less than, less than or equals   No
specifiedValueForAggregrate Aggregrate numeric value to check   No
specifiedConditionEnumForCount Operator to be applied for the count condition. Specify greater than, greater than or equals, less than, less than or equals   Yes
specifiedValueForCount Transaction count numeric value to check   Yes
durationDescriptor Specify the duration during which the transactions have to be counted. The duration descriptor enables you to specify the duration.

Important: By default, durationType is "rolling," meaning it takes the current time as the end point to count backward to the start point.

Whenever the duration is described as "last" x seconds/minutes/hours/days, the rolling type duration has to be used.

So if you specify 1 day using "rolling" durationType, the "rolling" day starts 24 hours (exactly 1 day) from the current time. For example, if it is 11:33 am, and you specify 1 day, the "rolling" day will start from 11:33 am of the previous day and end at the current time today.

There will be occasions where you want to have the duration window start at 0.00. For those occasions, you should use the durationType as "calendar".

So if you specify 1 day using "calendar" as the durationType, the "calendar" day will start at 0.00 (12:00 am) of that day and end at the current time.

Examples of "rolling" and "calendar":

A "calendar" week starts from Sunday regardless of the current day, whereas the "rolling" week starts from 7 days from the current day.

A "calendar" month starts from the 1st of the current month, whereas the "rolling" month starts from the same day of the previous month.

A "calendar" year starts from January 1st of the current year, whereas the "rolling" year starts from the same day of the previous year.

In both the "calendar" and "rolling," the end date/time is the current time. The durationType affects how the startTime of the duration is computed.

The "Before" option is used when you want to skip over an interval of time before you begin counting backward to the start point. For example, if you want to calculate 7 days worth of data, but you do not want the data from the last 7 days, you would specify the interval of time you want to skip. If today is February 6, and you want to look at data from January 17 to the 23rd, you would specify "Before" 15 days.

  No
transactionStatusEnum Specify the transaction status that has to be considered for counting. If you want to consider all transactions regardless of their status, do not specify any status   Yes
ignoreCurrentTransactionInCount Specify if you want to ignore current transaction (if any) in the count. If there are multiple transactions and if this is specified as true, only the last transaction is ignored.   Yes
applyFilterOnCurrentTransaction Specify if you want to check the filter conditions on the current transaction before performing the count. If the filter conditions fail on the current transaction then the rule condition is evaluated to false without performing the count.    
filter1Key

filter2Key

filter3Key

filter4Key

filter5Key

filter6Key

These parameters specify the left hand side of the filter conditions. The left hand side represents the fully qualified key of the transaction field.

This field could be an entity field or data field or transaction attribute or request attribute.

   
filter1Condition

filter2Condition

filter3Condition

filter4Condition

filter5Condition

filter6Condition

These parameters represent the operator and right hand side of the filter condition. The operator and the right hand side represent the fully qualified key of the filter condition.

The right hand side is the value, which could be a simple value, the value of the current transaction, or a group.

  • Value: A simple value that is entered into a field

  • Current: A value from the current transaction. A value is selected from a list of values based on the current entities.

  • Group: Group is automatically selected if you chose the condition as IN or NOT IN. After Group is selected, you will have to select a type of group. Then, based on type, a list box appears with other values to select from, and so on.

  Wherever the filterKey is specified, appropriate condition has to be specified

Possible User Scenarios

Use this condition whenever you want to trigger a rule based on an aggregrate of a transaction numeric value and transaction count.

This is designed to reduce the number of conditions since you can specify checks for both aggregrate and count in a single condition

For example, suppose you have configured a transaction called purchase and you want to challenge if a user is performing a lot of purchases (for example, more than 2 per hour with average amount that is greater than 500) from a high-risk country.

For achieving this, you must use this rule with the following:

  1. Specify Aggregrate condition as "Average."

  2. Specify Aggregrate value to check as "500."

  3. Specify Count condition as "Greater Than Equals."

  4. Specify Count to check as "2."

  5. Specify the duration with durationType as rolling and duration as 1 hour.

  6. Specify false for "Ignore Current Transaction in count?" since you want to consider current transaction in the count.

  7. Specify true for "Apply FilterOnCurrentTransaction?" field.

  8. One filter condition: for checking if the country of the current session is in the list of High Risk countries.

This condition can be used to specify up to six (6) filter conditions that are applied on transactions that are considered for counting

C.1.4.4 Transaction: Check Count of Any Entity or Element of a Transaction Using Filter Conditions

Condition TRANSACTION: Check Count of any entity or element of a Transaction using filter conditions
Condition TRANSACTION: Check Count of any entity or element of a Transaction using filter conditions
Description Check to see whether the count of a transaction entity or entity/data element with a given count where transactions matches ALL the conditions specified. Up to 6 conditions can be specified.
Prerequisites Ensure that you are using 10.1.4.5.2 or later.

Transactions should be defined; Transaction type of the current transaction should be same as the transaction type specified in the rule condition

Assumptions  
Available since version 10.1.4.5.2
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
trxDefKey Transaction Definition fully qualified key. This is specified using list box that has list of transaction definitions   No
elementDefFQKey Transaction Entity/Element that must be counted for checking   No
durationDescriptor Duration Descriptor   No
forTheSameCurrentUserId Boolean flag to indicate whether only transactions belonging to the current user to be counted or not   Yes
ignoreCurrentTransactionInCount Flag to indicate if the current transaction has to be ignored in the count    
specifiedConditionEnumForCount Condition for the count check. Select only valid operators that are relevant to numeric values   No
specifiedValueForCount Count value to check. Specify only valid positive integers.   No
applyFilterOnCurrentTransaction Flag to indicate if the filter conditions have to validated on current transaction before doing the count   No
filter1Key

filter2Key

filter3Key

filter4Key

filter5Key

filter6Key

These parameters specify the left hand side of the filter conditions. It represents fully qualified key of the transaction field.

This field could be an entity field or data field or transaction attribute or request attribute.

Note: There is a widget for this that renders list box with all the data fields.

  Yes
filter1Condition

filter2Condition

filter3Condition

filter4Condition

filter5Condition

filter6Condition

These parameters represent the operator and right hand side of the filter condition. It represents fully qualified key of the filter condition.

Note: There is a widget for this that renders the list box of operators and a way to specify simple value or group name (in case of IN or NOT IN operator) or select another field in the transaction.

  Wherever the filterKey is specified, appropriate condition has to be specified

Possible User Scenarios

Use this condition whenever you want to trigger a rule based on the count of an entity or entity/data element of the transaction.

For example, you configured a transaction called "purchase" and want to trigger a rule if the same user is trying to use more than 5 different credit cards in the last 2 hours and the amount of purchase is more than $100.

To achieve this:

  1. Select the "Credit Card" entity name as the one to be counted, so that the rule counts the distinct number of credit cards used.

  2. Then, select "For the same current user" flag as true.

  3. Then, select the duration as 2 rolling hours and the filter condition as "Amount" greater than 100.

There is provision to specify up to six (6) conditions for filtering the transactions that need to be considered for counting.

C.1.4.5 Transaction: Check if Consecutive Transactions in Given Duration Satisfy the Filter Conditions

Condition TRANSACTION: Check if consecutive Transactions in given duration satisfy the filter conditions
Description Check to see whether consecutive transactions in a given duration satisfy the specified filter conditions
Prerequisites
  • Transactions should be defined
  • Transaction type of the current transaction should be same as the transaction type specified in the rule condition

  • Ensure that you are using 10.1.4.5.2 or later.

Assumptions  
Available since version 10.1.4.5.2
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
trxDefKey Transaction Definition fully qualified key. This is specified using list box that has list of transaction definitions   No
durationDescriptor Duration Descriptor   No
transactionStatusGroupId Group of Transaction Statuses that should be considered. If no group is specified then Transaction Status is ignored in the query.   Yes
ignoreCurrentTransactionInQuery Flag to indicate if the current transaction has to be ignored    
forTheSameCurrentUserId Flag to indicate if only transactions belonging to the current user to be counted.

If this flag is false then transactions irrespective of users will be considered.

  No
allowGapsForChecks Flag to indicate if gaps are allowed while checking for conditions.

If this value is TRUE then gaps would be allowed while checking for conditions.

  No
noOfTransactionsToCheckFor1stCheck Number of transactions that should satisfy the 1st check. Specify positive integers.   No
filter101Key

filter102Key

filter103Key

filter104Key

filter105Key

filter106Key

Filter Keys for 1st check.

These parameters specify the left hand side of the filter conditions. It represents fully qualified key of the transaction field.

This field could be an entity field or data field or transaction attribute or request attribute.

Note: There is a widget for this that renders list box with all the data fields.

  Yes
filter101Condition

filter102Condition

filter103Condition

filter104Condition

filter105Condition

filter106Condition

Filter Conditions for 1st check.

These parameters represent the operator and right hand side of the filter condition. It represents fully qualified key of the filter condition.

Note: There is a widget for this that renders the list box of operators and a way to specify simple value or group name (in case of IN or NOT IN operator) or select another field in the transaction.

  Wherever the filterKey is specified, appropriate condition has to be specified
noOfTransactionsToCheckFor2ndCheck Number of transactions that should satisfy the 2nd check. Specify positive integers.   No
filter201Key

filter202Key

filter203Key

filter204Key

filter205Key

filter206Key

Filter Keys for 2nd check.

These parameters specify the left hand side of the filter conditions. It represents fully qualified key of the transaction field.

This field could be an entity field or data field or transaction attribute or request attribute.

Note: There is a widget for this that renders list box with all the data fields.

   
filter201Condition

filter202Condition

filter203Condition

filter204Condition

filter205Condition

filter206Condition

Filter Conditions for 2nd check.

These parameters represent the operator and right hand side of the filter condition. It represents fully qualified key of the filter condition.

Note: There is a widget for this that renders the list box of operators and a way to specify simple value or group name (in case of IN or NOT IN operator) or select another field in the transaction.

  Wherever the filterKey is specified, appropriate condition has to be specified

Possible User Scenarios

Use this condition whenever you want to trigger a rule based on checks that are satisfied on consecutive transactions in a given duration.

For example, you configured a transaction called purchase and want to trigger a rule if the current/last transaction amount is greater than $1000 and there were at least 3 transactions before that where the amount was less than $10.

So, the rule is looking at the last 4 transactions and checking for a fraud pattern of small transactions first and then a big transaction.

Configure a rule with this rule condition and select the appropriate transaction type.

  1. Select the number of transactions for the first check as "1" and select the condition to check as "Amount" "Greater Than" 1000, since you want to check only one transaction for the large amount.

  2. Select the number of transactions for the second check as "3" and select the condition to check as "Amount" "Less Than" 10, since you want to check 3 transactions for smaller amounts.

  3. If you want to allow other transactions in between the checks for the first check and the second check, select "Allow Gaps in Transactions during checks?" as TRUE otherwise select FALSE.

C.1.4.6 Transaction: Compare Transaction Aggregrates (Sum/Avg/Min/Max) Across Two Different Durations

Condition TRANSACTION: Compare Transaction Aggregrates (Sum/Avg/Min/Max) across two different durations
Description Compare transactions aggregrates across two different durations
Prerequisites
  • Transactions should be defined
  • Transaction entity/data field that has to be aggregrated should be of type numeric

  • Transaction type of the current transaction should be same as the transaction type specified in the rule condition

  • Ensure that you are using 10.1.4.5.2 or later.

Assumptions  
Available since version 10.1.4.5.2
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
trxDefKey Transaction Definition fully qualified key. This is specified using list box that has list of transaction definitions   No
aggregrateFunctionEnum Aggregrate function that has to be used   No
elementDefFQKey Transaction Entity/Data Element that must be aggregrated   No
durationDescriptorFor1stDuration Select duration for the first aggregrate   No
durationDescriptorFor2ndDuration Select duration for the second aggregrate   No
comparisonConditionEnum Comparison condition   No
multiplierFor2ndDurationValue Multiplier value for the second aggregrate. Only non-zero and null values will be considered   Yes
forTheSameCurrentUserId Boolean flag to indicate whether only transactions belonging to the current user to be counted or not   Yes
ignoreCurrentTransactionInQuery Flag to indicate if the current transaction has to be ignored   No
specifiedConditionEnumForCount Condition for the count check. Select only valid operators that are relevant to numeric values   No
specifiedValueForCount Count value to check. Specify only valid positive integers.   No
applyFilterOnCurrentTransaction Flag to indicate if the filter conditions have to validated on current transaction before doing the count   No
filter1Key

filter2Key

filter3Key

filter4Key

filter5Key

filter6Key

These parameters specify the left hand side of the filter conditions. It represents fully qualified key of the transaction field.

This field could be an entity field or data field or transaction attribute or request attribute.

Note: There is a widget for this that renders list box with all the data fields.

  Yes
filter1Condition

filter2Condition

filter3Condition

filter4Condition

filter5Condition

filter6Condition

These parameters represent the operator and right hand side of the filter condition. It represents fully qualified key of the filter condition.

Note: There is a widget for this that renders the list box of operators and a way to specify simple value or group name (in case of IN or NOT IN operator) or select another field in the transaction.

  Wherever the filterKey is specified, appropriate condition has to be specified

Possible User Scenarios

Use this condition whenever you want to trigger a rule based on the comparison of aggregrates of a transaction entity/data element across two different durations.

For example, you configured a transaction called purchase and want to trigger if the sum of the transaction amount for the current day is 20% more than the sum of all transactions amount of the previous day for that user.

To achieve this:

  1. Select the "Amount" as the element to be aggregrated and "Sum" as the aggregrate function.

  2. Then, select first duration as 1 calendar day and the second duration as 1 calendar day before 1 day.

  3. Then select the comparison condition as "Greater than" and multiplier value as 1.2 (100%+20%).

C.1.4.7 Transaction: Compare Transaction Counts Across Two Different Durations

Condition TRANSACTION: Compare Transaction counts across two different durations
Description Compare transactions counts across two different durations
Prerequisites
  • Transactions should be defined
  • Transaction type of the current transaction should be same as the transaction type specified in the rule condition

  • Ensure that you are using 10.1.4.5.2 or later.

Assumptions  
Available since version 10.1.4.5.2
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
trxDefKey Transaction Definition fully qualified key. This is specified using list box that has list of transaction definitions   No
durationDescriptorFor1stDuration Select duration for the first count   No
durationDescriptorFor2ndDuration Select duration for the second count   No
comparisonConditionEnum Comparison condition   No
multiplierFor2ndDurationValue Multiplier value for the second aggregrate. Only non-zero and null values will be considered   Yes
forTheSameCurrentUserId Boolean flag to indicate whether only transactions belonging to the current user to be counted or not   Yes
ignoreCurrentTransactionInCount Flag to indicate if the current transaction has to be ignored   No
specifiedConditionEnumForCount Condition for the count check. Select only valid operators that are relevant to numeric values   No
specifiedValueForCount Count value to check. Specify only valid positive integers.   No
applyFilterOnCurrentTransaction Flag to indicate if the filter conditions have to validated on current transaction before doing the count   No
filter1Key

filter2Key

filter3Key

filter4Key

filter5Key

filter6Key

These parameters specify the left hand side of the filter conditions. It represents fully qualified key of the transaction field.

This field could be an entity field or data field or transaction attribute or request attribute.

Note: There is a widget for this that renders list box with all the data fields.

  Yes
filter1Condition

filter2Condition

filter3Condition

filter4Condition

filter5Condition

filter6Condition

These parameters represent the operator and right hand side of the filter condition. It represents fully qualified key of the filter condition.

Note: There is a widget for this that renders the list box of operators and a way to specify simple value or group name (in case of IN or NOT IN operator) or select another field in the transaction.

  Wherever the filterKey is specified, appropriate condition has to be specified

Possible User Scenarios

Use this condition whenever you want to trigger a rule based on the comparison of transaction counts across two different durations.

For example, you configured a transaction called "purchase" and want to trigger the rule if the number of transactions for the current day is 20% more than the number of all transactions of the previous day for that user.

To achieve this:

  1. Select the first duration as 1 calendar day and the second duration as 1 calendar day before 1 day.

  2. Then, select the comparison condition as "Greater than" and multiplier value as 1.2 (100%+20%).

C.1.4.8 Transaction: Compare Transaction Entity/Element Counts Across Two Different Durations

Condition TRANSACTION: Compare Transaction Entity/Element counts across two different durations
Description Compare transaction entity/element counts across two different durations
Prerequisites
  • Transactions should be defined
  • Transaction type of the current transaction should be same as the transaction type specified in the rule condition

  • Ensure that you are using 10.1.4.5.2 or later.

Assumptions  
Available since version 10.1.4.5.2
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Values Can be Null?
durationDescriptorFor1stDuration Select duration for the first count   No
durationDescriptorFor2ndDuration Select duration for the second count   No
comparisonConditionEnum Comparison condition   No
multiplierFor2ndDurationValue Multiplier value for the second aggregrate. Only non-zero and null values will be considered   Yes
forTheSameCurrentUserId Boolean flag to indicate whether only transactions belonging to the current user to be counted or not   Yes
ignoreCurrentTransactionInCount Flag to indicate if the current transaction has to be ignored   No
specifiedConditionEnumForCount Condition for the count check. Select only valid operators that are relevant to numeric values   No
specifiedValueForCount Count value to check. Specify only valid positive integers.   No
applyFilterOnCurrentTransaction Flag to indicate if the filter conditions have to validated on current transaction before doing the count   No
filter1Key

filter2Key

filter3Key

filter4Key

filter5Key

filter6Key

These parameters specify the left hand side of the filter conditions. It represents fully qualified key of the transaction field.

This field could be an entity field or data field or transaction attribute or request attribute.

Note: There is a widget for this that renders list box with all the data fields.

  Yes
filter1Condition

filter2Condition

filter3Condition

filter4Condition

filter5Condition

filter6Condition

These parameters represent the operator and right hand side of the filter condition. It represents fully qualified key of the filter condition.

Note: There is a widget for this that renders the list box of operators and a way to specify simple value or group name (in case of IN or NOT IN operator) or select another field in the transaction.

  Wherever the filterKey is specified, appropriate condition has to be specified

Possible User Scenarios

Use this condition whenever you want to trigger a rule based on the comparison of any transaction entity/element counts across two different durations.

For example, you configured a transaction called "purchase" and want to trigger if the number of distinct credit cards used in the current day is 20% more than the number of distinct credit cards used on the previous day for that user.

To accomplish this:

  1. Select "Credit card" as the element to be counted and select the first duration as 1 calendar day and the second duration as 1 calendar day before 1 day.

  2. Then, select the comparison condition as "Greater than" and the multiplier value as 1.2 (100%+20%).

C.1.5 In-Session Conditions

The following in-session conditions are documented in this section:

C.1.5.1 Session: Check Param Value

Condition Session: Check param value
Description Check to see whether the specified parameter value is above the given threshold. This condition can be used to find out whether the value of a particular parameter in the transaction is above some known threshold and then action can be taken accordingly. Basically provided a mathematical function for integrators. This will be very useful in native integration.
Prerequisites None for condition as such. But you must have rule configured with this condition to experience the behavior.
Assumptions  
Available since version 10.1.4.5
Checkpoints All Checkpoints.

C.1.5.1.1 Parameters
Parameter Description Possible Values Can be Null?
Is If the "Is" is true and the value is above the threshold provided then condition evaluates to true.

If the "Is" is false and the value is below the threshold provided then condition evaluates to true.

[True] / False No
ValueKey The "key" or the look up name of the parameter in the transaction. For example if the transaction is purchase and the name of the attribute is "creditcard" and whose value at Checkpoint is going to be populated by users credit card, then key is "creditcard" in this case. If key is null then defaultError return value is the result of the condition.   Yes
ValueAbove This is basically the threshold value. A string that can be parsed into a number. (all numeric characters and "+", "-" and "." Also time can be used here in "HH24:MM:SS:MS" format. This can be used to see if the time is greater than the time parameter present in the transaction.   Yes

C.1.5.1.2 Possible User Scenarios

Use this condition whenever you want to find out whether the value of a particular attribute of the transaction exceeds some threshold.

For example, you configured a transaction called purchase want to trigger a rule whenever the customer purchase exceeds $1000 mark.

For accomplish this, you must use this rule with this condition.

  1. Configure the "ValueKey" of your transaction to "purchase.orderTotal" assuming that you have such an attribute in your transaction.

  2. Configure "ValueAbove" to "1000". Configure an alert that says "Too Big Purchase."

  3. Process a transaction by providing a few total value numbers above 1000 and a few below 1000.

  4. Verify that for the ones above 1000 the rule is triggered.

C.1.5.2 Session: Check Param Value for Regex

Condition Session: Check param value for regex
Description Find out whether the specified parameter value matches regular expression. This condition can be used to find out whether a string value of a particular parameter in the transaction matches a known pattern and then action can be taken accordingly. This provided a mathematical function for integrators and is useful in native integration.
Prerequisites None for condition as such. But you must have rule configured with this condition to experience the behavior.
Assumptions  
Available since version 10.1.4.5
Checkpoints All Checkpoints.

C.1.5.2.1 Parameters
Parameter Description Possible Values Can be Null?
Is If the "Is" is true and regular expression matches to the provided criteria then condition evaluates to true.

If the "Is" is false and regular expression does not match to the provided criteria then condition evaluates to true.

[True] / False No
ValueKey The "key" or the look up name of the parameter in the transaction. For example if the transaction is purchase and the name of the attribute is "creditcard" and whose value at Checkpoint is going to be populated by users credit card, then key is "creditcard" in this case. If key is null then defaultError return value is the result of the condition. You should be able to find this key in the Internal ID column in Transaction Source Data tab in transaction details.   Yes
Regular Expression The character pattern with which you want to match the "value" whose look up name is given by "ValueKey". In same credit card example. Check to see whether the user entered all correct in credit card so you might look for pattern "[0-9]".   Yes
Error Return value If there is any error then return (evaluate to) this value. If this value is not specified (null) then "False" is assumed. [False] / True Yes

C.1.5.2.2 Possible User Scenarios

Use this condition to find out whether the value of a particular attribute of the transaction matches some character pattern.

For example, you configured a transaction called "purchase" and want to trigger a rule whenever the customer email field ends with ".gov" or ".mil" so you can track government and military business for your firm.

For accomplish this, you must use this rule with this condition.

  1. Configure the "ValueKey" of your transaction to "customer.email" assuming that you have such a attribute in your transaction.

  2. Configure "Regular Expression" to "*[.gov][.mil]".

  3. Configure an alert that says "Government/Military business."

  4. Process a few transaction by providing email addresses ending with ".gov" or ".mil".

  5. Verify that the alert is generated.

  6. Process a few transactions by giving another email address ending with ".com" or any ending other than ".gov" or ".mil".

    Notice that alert is not generated.

C.1.5.3 Session: Check Param Value in Group

Condition Session: Check param value in group
Description Checks to see if specified parameter value matches the regular expression and the group identified by the expression matcher is in the list of strings. Regular expression matching is not sensitive to case (uppercase and lowercase letters are treated same)
Prerequisites None for condition as such, but you must have a rule configured with this condition for it to work.
Assumptions  
Available since version 10.1.4.5
Checkpoints All checkpoints.

Parameters

Parameter Description Possible Value Can be Null
Is If the "Is" is true and the key's value matches the regular expression and the first group string found by the regex matcher is in the string group, then the condition evaluates to "true." [True] / False Yes
Parameter Key The "key" or the look up name of the parameter in the transaction. For example, if the transaction is "internet banking" and the name of the attribute is "bankName" and its value at checkpoint is to be populated by users, then key is "Transaction.bankName" in this case. You should be able to find this key in the Internal ID column in the Transaction Source Data tab in transaction details. If the key is null, then defaultReturnValue is the result of the condition.   Yes
Regular Expression The character pattern with which you want to match the "value" which has its look up name given by "Parameter Key". In same banking example, if you want to find out whether the bankName equals "SomeBank," you should define this pattern in the policy/rule as "(SomeBank)" without the quotation marks. If the regular expression is null, then defaultReturnValue is the result of the condition.   Yes
In list The condition checks to see if the character group obtained by the regular expression matcher belongs to this string group. If the list name is null or if the list specified by the name is empty, then defaultReturnValue is the result of the condition.   Yes
Default Return value If there is any error or if the condition cannot be evaluated because of insufficient data, then return (evaluate to) this value. If this value is not specified (null) then "False" is assumed. [False] / True Yes

Possible User Scenarios

Use this condition whenever you want to find out whether some part of the value of a particular attribute of the transaction matches some character pattern, and to see if this part of the value is present in the pre-determined group of strings.

For example, you have configured a transaction called internet banking and you want to trigger a rule if the bank name is "bank1" or "bank2."

To achieve this, you must use this rule with this condition:

  1. Configure the "Parameter Key" of your transaction to "Transaction.bankName" (assuming that you have such an attribute in your transaction).

  2. Configure "Regular Expression" to "(bank.)". Configure an alert that says "Some specified bank transaction".

  3. Create a group of generic strings called "interesting banks" and add "bank1" and "bank2" to it.

  4. Configure the group name as "In List" parameter for this condition.

  5. Configure "Is" to true and default return value to false.

  6. Process a few transaction by providing bank names, "bank1" and "bank2","bank3", and so on. Verify that the alert is generated for "bank1" and "bank2" only.

  7. Verify that alerts are generated for "BANK1". This shows that the regular expression matching is not case-sensitive.

C.1.5.4 Session: Check String Value

Condition Session: Check String Value
Description Check to see whether the specified parameter value is equal to a given character string. This condition can be used to find out whether the value of a particular parameter in the transaction matches an expected string so that action can be taken accordingly. Basically the condition provided a string equality function for integrators. This is useful in native integration.

Note that the comparison is case-sensitive. That is "Good" is not equal to "GOOD".

Prerequisites None for condition as such, but you must configure a rule with this condition for the behavior.
Assumptions  
Available since version 10.1.4.5
Checkpoints All Checkpoints.

C.1.5.4.1 Parameters
Parameter Description Possible Value Can be Null?
ValueKey The "key" or the look up name of the parameter in the transaction. For example if the transaction is purchase and the name of the attribute is "creditCardType" and whose value at Checkpoint is going to be populated by users credit card type, then key is "creditCardType" in this case.   Yes
StringValue This is basically the value to compare with.   Yes

C.1.5.4.2 Possible User Scenarios

Use this condition whenever you want to find out whether the value of a particular attribute of the transaction equals a given string.

For example, you have configured a transaction called purchase and you want to trigger a rule whenever the customer credit card is American Express.

To accomplish this, you must use this rule with this condition:

  1. Configure the "ValueKey" of your transaction to "purchase.creditCardType" assuming that you have such an attribute in your transaction.

  2. Configure "StrValue" to "AMEX". Configure an alert that says "Amex Card Used"

  3. Process a few transactions by providing the card type as AMEX and a few with another card type.

  4. Verify that when AMEX is used, the rule is triggered.

C.1.5.5 Session: Time Unit Condition

Table C-2 Day of Week

Condition Day of Week

Description

Checks to see if time unit in current date matches certain criteria. The condition determines if a particular time unit (that is part of the current time) belongs to a particular position in the time unit.

This condition uses the request date if available to evaluate the date function requested with the help of parameters.

If the request date is not available, then current server date time will be used.

Example

This condition can determine if the day of the week is equal to (or not equal to or …) Monday or Tuesday and so on.

It can also determine if the day of the month matches certain criteria of the day of the month.

It can also try to match the same criteria if month of the year is X or not X or in or not in X.


Parameters

Parameters Description Possible Values
Time Unit Enum

What is the time unit you are looking for?

The default value is Day Of The Week

Possible values are:
  • Day Of the Week

  • Day Of the Month

  • Day of the year

  • Month of the Year

  • Hour of the day

  • Week Of the Month

  • Week Of The year

  • Year

Comparison operator Enum

What comparison you want to make with the time unit.

The default value=Equal To

Possible values are:
  • Equal To

  • Not Equal To

  • Less than

  • More Than

  • Less than equal to

  • more than equal to

  • IN

  • not IN

Comparison value String

The default value = "" (empty string), that represents integer or string that represents comma separated integers. Example: "1" or "1,2,3,4".

The user can use comma-separated values when using IN or NOT in operator.

If comma-separated values are used for any other operators, it will be determined as an error and value of the number 5 parameter (shown in Error Return) will be returned.

If the string does not represent number (or a list of comma separated numbers) then it is determined as error and value of parameter number 5 will be returned.

Correct values of this parameter for different time units.
  • Day Of The week: 1 through 7 (1 = Sunday).

  • Day Of the month: 1 through 31

  • Day of the year: 1 through 366

  • Month of the year: 0 through 11 (0 = January)

  • Hour of the day: 0 through 23

  • Week of the Month: 0 through 6

  • Week of the Year 1 through 53

  • Year: Positive integer

IS Condition True Boolean

Default value = true

This will the return value if the comparison is true.

 
Error Return value Boolean

Default value = false

If the user has configured the value of Comparison Value (#3) incorrectly, or if there is any other error determining date then this value will be returned.

The days of the weeks are:

  • 1 = sunday

  • 2 = monday

  • 3 = tuesday

  • 4 = wednesday

  • 5 = thursday

  • 6 = friday

  • 7 = saturday

The week day is 2,3,4,5,6

Time Unit = Day of the Week

Comparison Operator = "IN"

Comparison Value = "1,2,3,4,5"

Is Condition True = true

Error Return value = "false"

 

C.1.6 System Conditions

The following transaction conditions are documented in this section:

C.1.6.1 System - Check Boolean Property

Condition System - Check Boolean Property
Description Verify if specified property equals true of false.
Prerequisites None for condition as such. But you must have rule configured with this condition to experience the behavior.
Assumptions  
Available since version 10.1.4.5
Checkpoints All Checkpoints.

C.1.6.1.1 Parameters
Parameter Description Possible Value Can be Null?
Property The complete name of the property that must be checked.   Yes
PropertyValue The expected value of the property. If the property has this value then the condition will evaluate to true. [True] / false Yes
Defaultvalue The value of the property to be used if the property is not found in the system. [True] / false Yes

C.1.6.1.2 Possible User Scenarios

Use this condition whenever you want to find out whether the value of a particular property is true or false.

For example, you have a property "trigger.sample.rule" and its value is true.

You want to trigger some rule based on this property.

For accomplish this, you must use this rule with this condition.

  1. Configure the "Property" of this condition to "trigger.sample.rule".

  2. Configure the PropertyValue to "true".

  3. Configure DefaultValue to "false"

  4. Run authentication of users to see if the rule triggers.

  5. Use the property editor to change the value of the property "trigger.sample.rule" to false.

  6. Run authentication of users again and notice that the rule does not trigger.

C.1.6.2 System - Check Enough Pattern Data

Table C-3 System - Check enough pattern data

Details Description

Condition

System - Check enough pattern data

Description

Checks if enough profiling data is available for a given pattern. This condition checks if pattern data is available in the system for the last several days.

It checks only for a particular pattern. So if data is available that is collected by the given pattern for more than the specified number of days, this condition evaluates to true.

Prerequisites

None for condition as such. But you must have a rule configured with this condition to experience the behavior.

Available since version

11.1.1.5.0

RunTimes

All Runtimes.


Parameters

Table C-4 System - Check enough pattern data parameters

Parameter Description Possible Values Can be null?

patternGlobalIdCheckData

Name of the pattern for which the data availability is to be checked.

Pattern names from drop down list

No

numDaysOfDataToCheck

How many days should the condition "look back" from the current login's request time. Typical value is 90 (days).

The condition checks these many number of days of data. If pattern profiling data is available for at least these number of days, the condition evaluates to true

Positive integer

No

isPatternDataAvailableDataCheck

Condition evaluates to true if this value is true and there is enough autolearning data OR if this value is false and there is not enough autolearning data. In all other cases, the condition evaluates to false. This parameter basically can be used to decide the outcome of the condition.

[True] / False

Yes

errorReturnValueDataCheck

Value to return if the condition runs into an error.

[False] / True

Yes


Possible User Scenarios

Use this condition to check if enough autolearning data exists in the system that had been collected by a given pattern.

"Enough data" can be termed as data gathered over the last several days, depending on the customer scenarios.

For example, this condition can determine if the given autolearning pattern has gathered the data for the last 90 days and based on that, the autolearning rules are used.

The condition provides time for autolearning data to reach statistical stability. If autolearning rules work on a very small set of data, the results may be skewed, depending on how small data sample is.

For example, on a system that just had the pattern enabled today, a customer may want the OAAM Server to gather pattern data for three months before starting testing.

In that case, this condition is useful because it will evaluate to true only after three months (90 days). Then, autolearning rules can trigger and evaluate the risk.

C.1.6.3 System - Check If Enough Data is Available for Any Pattern

Table C-5 System - Check If Enough Data is Available for Any Pattern

Details Description

Condition

System - Check If Enough Data is Available for Any Pattern

Description

Checks if enough profiling data is available for any pattern. This condition will check if pattern data is available in the system for the last several days.

This condition does not check for a particular pattern. So if data is available that is collected by any pattern for more than specified number of days, this condition will evaluate to true.

Prerequisites

None for condition as such, a rule must be configured with this condition to experience the behavior.

Assumptions

Autoleaning is enabled. Without active patterns collecting profiling data, this conditions will not be meaningful.

Available since version

11.1.1.5.0

RunTimes

All Runtimes.


Parameters

Table C-6 System - Check If Enough Data is Available for Any Pattern Parameters

Parameter Description Possible Value Can be Null?

numDaysOfDataToCheckAnyPattern

How many days should condition "look back" from the current login's request time. Typical value is 90 (days).

Condition checks these many number of days of data. If pattern profiling data is available for at least these number of days, the condition will evaluate to true.

Positive integer

No

isPatternDataAvailableDataCheckAnyPattern

Condition evaluates to true if this value is true and there is enough autolearning data OR if this value is false and there is not enough autolearning data. In all other cases, the condition evaluates to false. This parameter can be used to decide the outcome of the condition.

[True] / False

Yes

errorReturnValueDataCheckAnyPattern

Value to return if the condition runs into an error.

[False] / True

Yes


Possible Scenarios

Use this condition to check if enough autolearning data exists in the system.

"Enough data" can be termed as data gathered over the last several days depending on the customer scenarios.

This condition can determine if any of the autolearning pattern have gathered data for the last 90 days, and based on that, auto learning rules can be used.

This provides time for autolearning data to reach statistical stability. Otherwise, if autolearning rules work on a very small set of data, the results may be skewed depending on how small the data sample is.

For example: on a system that has patterns enabled today, customers may want OAAM Server to gather pattern data for three months before starting to use autolearning rules. In that case, this condition is useful. It evaluates to true only after three months (90 days) and then autolearning rules can trigger and evaluate the risk.

C.1.6.4 System - Check Int Property

Condition System - Check Integer Property
Description Verify if specified property equals expected integer value
Prerequisites None for condition as such. But you must have rule configured with this condition to experience the behavior.
Assumptions  
Available since version 10.1.4.5
Checkpoints All Checkpoints.

Parameters

Parameter Description Possible Value Can be Null?
Property The complete name of the property that must be checked.   Yes
PropertyValue The expected value of the property. If the property has this value then the condition will evaluate to true. Integer Yes
Defaultvalue The value of the property to be used if the property is not found in the system. Integer Yes

Possible Scenarios

Use this condition whenever you want to find out whether the value of a particular property equals the expected integer value.

For example, you might have a property "trigger.sample.rule.test.integer" and its value to 25.

You want to trigger some rule based on this property.

For accomplish this, you must use this rule with this condition.

  1. Configure the "Property" of this condition to "trigger.sample.rule.test.integer". Configure the PropertyValue to "25".

  2. Configure DefaultValue to "30"

  3. Run authentication users to see the rule triggers.

  4. Use the Property editor to change the value of the property "trigger.sample.rule.test.integer" to 88.

  5. Run authentication users again.

    Notice that the rule does not trigger.

C.1.6.5 System - Check String Property

Condition System - Check String Property
Description Verify if specified property equals expected string value
Prerequisites None for condition as such. But you must have rule configured with this condition to experience the behavior.
Assumptions  
Available since version 10.1.4.5
Checkpoints All Checkpoints.

Parameters

Parameter Description Possible Value Can be Null?
Property The complete name of the property that must be checked.   Yes
PropertyValue The expected value of the property. If the property has this value then the condition will evaluate to true. String Yes
Defaultvalue The value of the property to be used if the property is not found in the system. String Yes

Possible User Scenarios

Use this condition whenever you want to find out whether the value of a particular property equals the expected the string value.

For example, you have a property "trigger.sample.rule.test.string" and its value is "test_string". You want to trigger a rule based on this property.

For achieving this, you must use this rule with this condition.

  1. Configure the "Property" of this condition to "trigger.sample.rule.test.string".

  2. Configure the PropertyValue to "test_string" and configure DefaultValue to "some_other_string"

  3. Run authentication on users to trigger the rule.

  4. Use the Property editor to change the value of the property "trigger.sample.rule.test.instringteger" to "completely different string value".

  5. Run authentication on users again.

    Notice that the rule does not trigger.

C.1.6.6 System - Check Request Date

Condition System - Check Request Date
Description Verify if the request date of the transaction or authentication is after a specific date. Notice that only the year, month and day part of the date is used. So basically the "time" portion of the date is ignored when comparing dates.
Prerequisites None for condition as such. But you must have rule configured with this condition to experience the behavior.
Assumptions  
Available since version 10.1.4.5
Checkpoints All Checkpoints.

Parameters

Parameter Description Possible Value Can be Null?
Date (MM/dd/yyyy) The date string which the user wants to check the request date against.   No
Is After Request Date To check to see whether the request date is after the specified date or not after specified date. [True] / False Yes

Possible User Scenarios

Use this condition whenever you want to find out whether the transaction or authentication occurred after a certain date.

For example, if you want to direct users to a certain other policy after a given date, you might use this rule.

To do this, you must use this rule with this condition.

  1. Configure the "Date" of this condition to "12/22/2009" if you want to trigger a rule starting the 23rd December of 2009.

  2. Configure the "Is After"to "true".

  3. Run authentication on users.

    If the date is after 12/22/2009, the rule triggers.

  4. Using the Policy editor, change the date in this condition to a future date.

  5. Run authentication on the users again.

    Notice that the rule does not trigger.

C.1.7 User Conditions

The following user conditions are documented in this section:

C.1.7.1 User: Check User Data

Condition User: Check User Data
Description Verify if specified key has any related data for the user
Prerequisites None for condition as such, but you must have rule configured with this condition to experience the behavior.
Assumptions  
Available since version 10.1.4.5
Checkpoints All Checkpoints.

Parameters

Parameter Description Possible Value Can be Null?
User Data Key The complete name of the key which may have associated data for that user.

Consider this a property or a configuration property for only that user.

[Strings] Default= email Yes

Possible User Scenarios

This condition can be used whenever you want to check to see whether the user has associated data for the key. For example, you may want to find out whether the user has an email defined in his OTP configuration, so you want to trigger a rule based on whether this email field is defined (non-empty) for the user. To do this, you must use this rule with this condition.

  1. Configure the "User Data Key" of this condition with "user_otpContactInfo_email" (for mobile phone, use key to "user_otpContactInfo_mobile").

  2. Use the new out-of-the-box base policies that are shipped with 11g. This will force user to register for OTP on the first or second login.

  3. Run authentications with the registered users.

    You can see the rule triggering when they are registered for the OTP email (or mobile if you have used that as key).

  4. Then go to policy editor and change the value of the key "zoom.some.item.that.is.not.supposed.to.exist."

  5. Run authentication users again and notice that the rule does not trigger.

    Notice that the rule does not trigger. (The assumption is that no such key data exists for this usual key)

C.1.7.2 User: Stale Session

Condition User: Stale Session
Description Verify if a newer session is established after this session is created
Prerequisites None for condition as such. But you must have a rule configured with this condition to experience the behavior.
Assumptions  
Available since version 10.1.4.5
Checkpoint All checkpoints.

Possible User Scenarios

This condition can be used whenever you want to find out whether the user has established a successful login from another channel while this authentication is in progress.

C.1.7.3 User: Velocity from Last Success

Table C-7 User: Velocity from Last Success

Condition User: Velocity from Last Success

Description

Condition evaluates to check to see if

  • The user's login was successful earlier, and

  • The velocity in miles per hour is more than the specified value, and

  • The user belongs to the same Device ID

Prerequisites

None for condition as such, but you must have the rule configured with this condition

Assumptions

 

Available since version

10.1.4.5

Checkpoints

All Checkpoints.


Parameter Description Possible Value Can be Null?
Miles per hour is more than The velocity in miles per hour is more than specified value Positive integer

Default: 60

No
ignore if last login device is same See possible value. True/False

The flag is set to true

  • if there are more than one successful login from the same user from the same Device ID. The condition returns false and no action/alert is triggered.

  • if there are more than one successful login from the same user from different Device IDs and the condition returns true and an action/alert is generated.

The flag is set to false

False ignores the parameter and the condition evaluates based on miles per hour only.

Yes
Exclude IP List This parameter allows you to specify a list of IPs to ignore. If a user's IP is from that list, then this condition always evaluates to false. If the user's IP is not in that list or if the list is null or empty, then the condition evaluates the velocity of the user or the device from the last login and evaluates to true if the velocity exceeds the configured value.    

Scenario

Condition evaluates if the users login was successful earlier and the velocity in miles per hour is more than specified value and user belong to the same Device ID. If there are multiple logins of the same user from the same device, then the parameter "ignore if last login device is same" will act. In order for the condition to be false, there must be multiple logins that are successful from the same user that is using the same Device ID. The location database is used to determine the location of the user for this login and the previous login.

Use Case 1

User: karen1, Device ID: 2106, Previous Device ID: None, rule-flag: true

  1. Log in from device from IP1

  2. Log in from the same device from IP2 (which is 60 miles away). There is no alert generated.

  3. Log in from the same device and IP2 (which is 60 miles away). There is no alert generated.

Table C-8 Use Case 1

Username Auth Status Device ID Location IP Alert

karen1

Success

2106

US, Texas, Austin

IP1

No alert

karen1

Success

2106

US, Arizona, Gila Bend

IP2

No alert. An alert is not generated since the same user has the same device and the flag is set to true.

karen1

Success

2106

US, Arizona, Gila Bend

IP2

No alert. An alert is not generated since the same user has the same device and the flag is set to true.


Use Case 2

User: karen1, Device ID: 2107, Previous Device ID: 2106, rule-flag: true

  1. Log in from the same device from IP1.

  2. Log in from the same device from IP2 (which is 60 miles away). There is no alert triggered.

  3. Log in from the same device and IP2 (which is 60 miles away). There is no alert triggered.

Table C-9 Use Case 2

Username Auth Status Device ID Location IP Alert

karen1

Success

2107

US, Arizona, Gila Bend

IP1

New device

karen1

Success

2107

US, Texas, Austin

IP2

No alert. An alert is not generated since the same user has the same device and the flag is set to true.

karen1

Success

2107

US, Texas, Austin

IP2

No alert. An alert is not generated since the same user has the same device and the flag is set to true.


Use Case 3

User: karen1, Device ID: 2109, Previous Device ID: 2108, rule-flag: false

  1. Log in from Device 2108 from IP1.

  2. Log in from Device 2109 from IP2 (which is 60 miles away). Alerts are triggered.

  3. Log in from the same device (Device 2109) and IP2 (which is 60 miles away). No alert is triggered.

Table C-10 Use Case 3

Username Auth Status Device ID Location IP Alert

karen1

Success

2108

US, Texas, Austin

IP1

New device

karen1

Success

2109

US, Arizona, Gila Bend

IP2

Device High Velocity

User High Velocity

karen1

Success

2109

US, Arizona, Gila Bend

IP2

No alert


C.1.7.4 Understanding How the OAAM Device Max Velocity Rule Settings Work

The "Device Max Velocity" rule is used to detect "man in the middle" attacks where a hacker obtains the MAC address for devices that users log in from. Hackers replay the user's login and provide the user's computer MAC address. By doing this they fool the system into thinking the user is logging in from a known and trusted device that is in the user's OAAM profile.

The "Device Max Velocity" rule can detect this type of attack, trigger an alert and block the hacker from successfully signing in. This is accomplished in conjunction with the Quova subscription data. The rule checks to see if the MAC address is in the list of known devices the user is logged in from. Then it examines the IP address location where the user is logged in from. If a hacker then tries to log in by replaying the user's session and also using the user's device MAC address from another location, such as 100 miles away, the rule uses a formula that determines the possibility of that user's device traveling at that velocity.

It is possible for a user to log in to his application, then take a Jet to fly to another city and once again log in to the same application. Therefore you want to be able to adjust the variables of the formula to allow for a portable device to travel at least the speed of a Jet. The "Device Max Velocity" rule has two values that the administrator can configure. Those value fields are called "Last Login Within (Seconds)" and "Miles Per Hour is More Than". Using these two field values you can customize the allotted velocity that a physical device can travel before an alert is triggered.

How the Rule Formula Works

  1. The rule first picks up the last successful login in the last N seconds. (If there are multiples, the last one (with the highest timestamp) is picked.

  2. The rule looks at cityLastLogin and currentCurrentLogin and calculate the distance between them which "= the distance."

  3. Then it calculates thisDistance divided by the difference in login times. That becomes the velocityCalculated.

  4. If velocityCalculated is more than velocityConfigured in the rule (from the user interface), the rule triggers.

Solution

Using the following testing assumptions and steps you can make the "Device Max Velocity" rule alert trigger, and also see how to avoid not triggering the rule alert. Before starting your test:

The user's auth status should be "success" in the previous login (N seconds ago).

Assume you only have one minute to test the "Device Max Velocity" rule. Assuming that point A and point B are 900 miles apart, in order to travel from point A to point B in 60 seconds, you need to be traveling at 54000 miles an hour.

  1. Set your "Miles Per Hour is More Than" to 54000

  2. Set the "Last Login Within (Seconds)" to 60 seconds.

Setting up the Test:

Pick two IP addresses for the test that you know are far away from each other. You are using the following IP addresses from the Quova data:

63.232.120.161 Austin, Texas

63.229.250.34 Phoenix, Arizona

These two cities are a distance of 867 miles apart.

Make sure that the rule is not triggered by logging in twice and not exceeding the "Device Max Velocity" settings you already set to 60 seconds and 54000 miles per hour. Log in twice with the same user and device with logins no less than 75 seconds apart. Make sure that each time you log in you use a tool like Firefox "Modify Headers" to change the IP address between logins using the two IP Addresses mentioned earlier in this section. This simulates a device logging in from two different locations 867 miles apart. The Device Max Velocity alert does not trigger.

Now perform the same test again where you log in twice less than 30 seconds apart, again, changing the IP address between logins. The Device Velocity alert is triggered.

Understanding the relationship between the "Miles Per Hour is More Than" and the "Last Login Within (Seconds)" settings: You cannot change one of these settings and not consider what the other needs to be set to. In other words, you cannot only set the "Mile Per Hour is More Than" setting and not properly adjust the "Last Login within (Seconds)" setting. These two settings work together with the formula to calculate a devices velocity. The relationship between these two settings is not an "OR". It is an "AND". Last Login AND Mile per hour work together. Remember the following two rules before changing these two settings.

  1. You cannot only consider the "Miles Per hour" when setting the velocity. You must also consider the "Last Login within (Seconds)" setting.

  2. When testing, you must consider and calculate the distance between point A and point B, the time taken to conduct the test, and further factor in the distance between the two points and how long the testing takes. If you want to use one minute as the time allotted for the testing, then make sure you know the distance between point A and Point B. You must also know how long it takes to get from point A and point B in 60 seconds, again, if you plan to conduct your test in less than one minute.