Adding setup templates to the ML rules (#3798)

* Added setup instructions for ml rules

(cherry picked from commit 51b9717)

Author: sodhikirti07

rules/integrations/aws/ml_cloudtrail_error_message_spike.toml

@@ -2,7 +2,7 @@
 creation_date = "2020/07/13"
 integration = ["aws"]
 maturity = "production"
-updated_date = "2024/05/21"
+updated_date = "2024/06/18"
 
 [rule]
 anomaly_threshold = 50
@@ -23,6 +23,27 @@ interval = "15m"
 license = "Elastic License v2"
 machine_learning_job_id = "high_distinct_count_error_message"
 name = "Spike in AWS Error Messages"
+setup = """## Setup
+
+This rule requires the installation of associated Machine Learning jobs, as well as data coming in from AWS.
+
+### Anomaly Detection Setup
+
+Once the rule is enabled, the associated Machine Learning job will start automatically. You can view the Machine Learning job linked under the "Definition" panel of the detection rule. If the job does not start due to an error, the issue must be resolved for the job to commence successfully. For more details on setting up anomaly detection jobs, refer to the [helper guide](https://www.elastic.co/guide/en/kibana/current/xpack-ml-anomalies.html).
+
+### AWS Integration Setup
+The AWS integration allows you to collect logs and metrics from Amazon Web Services (AWS) with Elastic Agent.
+
+#### The following steps should be executed in order to add the Elastic Agent System integration "aws" to your system:
+- Go to the Kibana home page and click “Add integrations”.
+- In the query bar, search for “AWS” and select the integration to see more details about it.
+- Click “Add AWS”.
+- Configure the integration name and optionally add a description.
+- Review optional and advanced settings accordingly.
+- Add the newly installed “aws” to an existing or a new agent policy, and deploy the agent on your system from which aws log files are desirable.
+- Click “Save and Continue”.
+- For more details on the integration refer to the [helper guide](https://www.elastic.co/docs/current/integrations/aws).
+"""
 note = """## Triage and analysis
 
 ### Investigating Spike in AWS Error Messages
@@ -76,10 +97,6 @@ This rule uses a machine learning job to detect a significant spike in the rate
 - Take the actions needed to return affected systems, data, or services to their normal operational levels.
 - Identify the initial vector abused by the attacker and take action to prevent reinfection via the same vector.
 - Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
-
-## Setup
-
-The AWS Fleet integration, Filebeat module, or similarly structured data is required to be compatible with this rule.
 """
 references = ["https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html"]
 risk_score = 21

rules/integrations/aws/ml_cloudtrail_rare_error_code.toml

@@ -2,7 +2,7 @@
 creation_date = "2020/07/13"
 integration = ["aws"]
 maturity = "production"
-updated_date = "2024/05/21"
+updated_date = "2024/06/18"
 
 [rule]
 anomaly_threshold = 50
@@ -23,6 +23,27 @@ interval = "15m"
 license = "Elastic License v2"
 machine_learning_job_id = "rare_error_code"
 name = "Rare AWS Error Code"
+setup = """## Setup
+
+This rule requires the installation of associated Machine Learning jobs, as well as data coming in from AWS.
+
+### Anomaly Detection Setup
+
+Once the rule is enabled, the associated Machine Learning job will start automatically. You can view the Machine Learning job linked under the "Definition" panel of the detection rule. If the job does not start due to an error, the issue must be resolved for the job to commence successfully. For more details on setting up anomaly detection jobs, refer to the [helper guide](https://www.elastic.co/guide/en/kibana/current/xpack-ml-anomalies.html).
+
+### AWS Integration Setup
+The AWS integration allows you to collect logs and metrics from Amazon Web Services (AWS) with Elastic Agent.
+
+#### The following steps should be executed in order to add the Elastic Agent System integration "aws" to your system:
+- Go to the Kibana home page and click “Add integrations”.
+- In the query bar, search for “AWS” and select the integration to see more details about it.
+- Click “Add AWS”.
+- Configure the integration name and optionally add a description.
+- Review optional and advanced settings accordingly.
+- Add the newly installed “aws” to an existing or a new agent policy, and deploy the agent on your system from which aws log files are desirable.
+- Click “Save and Continue”.
+- For more details on the integration refer to the [helper guide](https://www.elastic.co/docs/current/integrations/aws).
+"""
 note = """## Triage and analysis
 
 ### Investigating Rare AWS Error Code
@@ -78,10 +99,6 @@ Detection alerts from this rule indicate a rare and unusual error code that was
 - Take the actions needed to return affected systems, data, or services to their normal operational levels.
 - Identify the initial vector abused by the attacker and take action to prevent reinfection via the same vector.
 - Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
-
-## Setup
-
-The AWS Fleet integration, Filebeat module, or similarly structured data is required to be compatible with this rule.
 """
 references = ["https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html"]
 risk_score = 21

rules/integrations/aws/ml_cloudtrail_rare_method_by_city.toml

@@ -2,7 +2,7 @@
 creation_date = "2020/07/13"
 integration = ["aws"]
 maturity = "production"
-updated_date = "2024/05/21"
+updated_date = "2024/06/18"
 
 [rule]
 anomaly_threshold = 50
@@ -24,6 +24,27 @@ interval = "15m"
 license = "Elastic License v2"
 machine_learning_job_id = "rare_method_for_a_city"
 name = "Unusual City For an AWS Command"
+setup = """## Setup
+
+This rule requires the installation of associated Machine Learning jobs, as well as data coming in from AWS.
+
+### Anomaly Detection Setup
+
+Once the rule is enabled, the associated Machine Learning job will start automatically. You can view the Machine Learning job linked under the "Definition" panel of the detection rule. If the job does not start due to an error, the issue must be resolved for the job to commence successfully. For more details on setting up anomaly detection jobs, refer to the [helper guide](https://www.elastic.co/guide/en/kibana/current/xpack-ml-anomalies.html).
+
+### AWS Integration Setup
+The AWS integration allows you to collect logs and metrics from Amazon Web Services (AWS) with Elastic Agent.
+
+#### The following steps should be executed in order to add the Elastic Agent System integration "aws" to your system:
+- Go to the Kibana home page and click “Add integrations”.
+- In the query bar, search for “AWS” and select the integration to see more details about it.
+- Click “Add AWS”.
+- Configure the integration name and optionally add a description.
+- Review optional and advanced settings accordingly.
+- Add the newly installed “aws” to an existing or a new agent policy, and deploy the agent on your system from which aws log files are desirable.
+- Click “Save and Continue”.
+- For more details on the integration refer to the [helper guide](https://www.elastic.co/docs/current/integrations/aws).
+"""
 note = """## Triage and analysis
 
 ### Investigating Unusual City For an AWS Command
@@ -80,10 +101,6 @@ Detection alerts from this rule indicate an AWS API command or method call that
 - Take the actions needed to return affected systems, data, or services to their normal operational levels.
 - Identify the initial vector abused by the attacker and take action to prevent reinfection via the same vector.
 - Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
-
-## Setup
-
-The AWS Fleet integration, Filebeat module, or similarly structured data is required to be compatible with this rule.
 """
 references = ["https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html"]
 risk_score = 21

rules/integrations/aws/ml_cloudtrail_rare_method_by_country.toml

@@ -2,7 +2,7 @@
 creation_date = "2020/07/13"
 integration = ["aws"]
 maturity = "production"
-updated_date = "2024/05/21"
+updated_date = "2024/06/18"
 
 [rule]
 anomaly_threshold = 50
@@ -24,6 +24,27 @@ interval = "15m"
 license = "Elastic License v2"
 machine_learning_job_id = "rare_method_for_a_country"
 name = "Unusual Country For an AWS Command"
+setup = """## Setup
+
+This rule requires the installation of associated Machine Learning jobs, as well as data coming in from AWS.
+
+### Anomaly Detection Setup
+
+Once the rule is enabled, the associated Machine Learning job will start automatically. You can view the Machine Learning job linked under the "Definition" panel of the detection rule. If the job does not start due to an error, the issue must be resolved for the job to commence successfully. For more details on setting up anomaly detection jobs, refer to the [helper guide](https://www.elastic.co/guide/en/kibana/current/xpack-ml-anomalies.html).
+
+### AWS Integration Setup
+The AWS integration allows you to collect logs and metrics from Amazon Web Services (AWS) with Elastic Agent.
+
+#### The following steps should be executed in order to add the Elastic Agent System integration "aws" to your system:
+- Go to the Kibana home page and click “Add integrations”.
+- In the query bar, search for “AWS” and select the integration to see more details about it.
+- Click “Add AWS”.
+- Configure the integration name and optionally add a description.
+- Review optional and advanced settings accordingly.
+- Add the newly installed “aws” to an existing or a new agent policy, and deploy the agent on your system from which aws log files are desirable.
+- Click “Save and Continue”.
+- For more details on the integration refer to the [helper guide](https://www.elastic.co/docs/current/integrations/aws).
+"""
 note = """## Triage and analysis
 
 ### Investigating Unusual Country For an AWS Command
@@ -80,10 +101,6 @@ Detection alerts from this rule indicate an AWS API command or method call that
 - Take the actions needed to return affected systems, data, or services to their normal operational levels.
 - Identify the initial vector abused by the attacker and take action to prevent reinfection via the same vector.
 - Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
-
-## Setup
-
-The AWS Fleet integration, Filebeat module, or similarly structured data is required to be compatible with this rule.
 """
 references = ["https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html"]
 risk_score = 21

rules/integrations/aws/ml_cloudtrail_rare_method_by_user.toml

@@ -2,7 +2,7 @@
 creation_date = "2020/07/13"
 integration = ["aws"]
 maturity = "production"
-updated_date = "2024/05/21"
+updated_date = "2024/06/18"
 
 [rule]
 anomaly_threshold = 75
@@ -23,6 +23,27 @@ interval = "15m"
 license = "Elastic License v2"
 machine_learning_job_id = "rare_method_for_a_username"
 name = "Unusual AWS Command for a User"
+setup = """## Setup
+
+This rule requires the installation of associated Machine Learning jobs, as well as data coming in from AWS.
+
+### Anomaly Detection Setup
+
+Once the rule is enabled, the associated Machine Learning job will start automatically. You can view the Machine Learning job linked under the "Definition" panel of the detection rule. If the job does not start due to an error, the issue must be resolved for the job to commence successfully. For more details on setting up anomaly detection jobs, refer to the [helper guide](https://www.elastic.co/guide/en/kibana/current/xpack-ml-anomalies.html).
+
+### AWS Integration Setup
+The AWS integration allows you to collect logs and metrics from Amazon Web Services (AWS) with Elastic Agent.
+
+#### The following steps should be executed in order to add the Elastic Agent System integration "aws" to your system:
+- Go to the Kibana home page and click “Add integrations”.
+- In the query bar, search for “AWS” and select the integration to see more details about it.
+- Click “Add AWS”.
+- Configure the integration name and optionally add a description.
+- Review optional and advanced settings accordingly.
+- Add the newly installed “aws” to an existing or a new agent policy, and deploy the agent on your system from which aws log files are desirable.
+- Click “Save and Continue”.
+- For more details on the integration refer to the [helper guide](https://www.elastic.co/docs/current/integrations/aws).
+"""
 note = """## Triage and analysis
 
 ### Investigating Unusual AWS Command for a User
@@ -78,10 +99,6 @@ Detection alerts from this rule indicate an AWS API command or method call that
 - Take the actions needed to return affected systems, data, or services to their normal operational levels.
 - Identify the initial vector abused by the attacker and take action to prevent reinfection via the same vector.
 - Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
-
-## Setup
-
-The AWS Fleet integration, Filebeat module, or similarly structured data is required to be compatible with this rule.
 """
 references = ["https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html"]
 risk_score = 21

rules/ml/command_and_control_ml_packetbeat_dns_tunneling.toml

@@ -2,7 +2,7 @@
 creation_date = "2020/03/25"
 integration = ["endpoint", "network_traffic"]
 maturity = "production"
-updated_date = "2024/05/21"
+updated_date = "2024/06/18"
 
 [rule]
 anomaly_threshold = 50
@@ -24,6 +24,50 @@ interval = "15m"
 license = "Elastic License v2"
 machine_learning_job_id = "packetbeat_dns_tunneling"
 name = "DNS Tunneling"
+setup = """## Setup
+
+This rule requires the installation of associated Machine Learning jobs, as well as data coming in from one of the following integrations:
+- Elastic Defend
+- Network Packet Capture
+
+### Anomaly Detection Setup
+
+Once the rule is enabled, the associated Machine Learning job will start automatically. You can view the Machine Learning job linked under the "Definition" panel of the detection rule. If the job does not start due to an error, the issue must be resolved for the job to commence successfully. For more details on setting up anomaly detection jobs, refer to the [helper guide](https://www.elastic.co/guide/en/kibana/current/xpack-ml-anomalies.html).
+
+### Elastic Defend Integration Setup
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+#### Prerequisite Requirements:
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the [documentation](https://www.elastic.co/guide/en/fleet/current/fleet-server.html).
+
+#### The following steps should be executed in order to add the Elastic Defend integration to your system:
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. [Helper guide](https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html).
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the [helper guide](https://www.elastic.co/guide/en/fleet/current/agent-policy.html).
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the [helper guide](https://www.elastic.co/guide/en/security/current/install-endpoint.html).
+
+### Network Packet Capture Integration Setup
+The Network Packet Capture integration sniffs network packets on a host and dissects known protocols. Monitoring the network traffic is critical to gaining observability and securing your environment — ensuring high levels of performance and security. The Network Packet Capture integration captures the network traffic between your application servers, decodes common application layer protocols and records the interesting fields for each transaction.
+
+#### The following steps should be executed in order to add the Elastic Agent System integration "network_traffic" to your system:
+- Go to the Kibana home page and click “Add integrations”.
+- In the query bar, search for “Network Packet Capture” and select the integration to see more details about it.
+- Click “Add Network Packet Capture”.
+- Configure the integration name and optionally add a description.
+- Review optional and advanced settings accordingly.
+- Add the newly installed “network_traffic” to an existing or a new agent policy, and deploy the agent on your system from which network log files are desirable.
+- Click “Save and Continue”.
+- For more details on the integration refer to the [helper guide](https://docs.elastic.co/integrations/network_traffic).
+"""
 references = ["https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html"]
 risk_score = 21
 rule_id = "91f02f01-969f-4167-8f66-07827ac3bdd9"