ServiceNow GRC/IRM and ComplianceCow Continous Controls Monitoring (CCM) of IT and Cybersecurity Compliance & Risk Controls in ServiceNow GRC/IRM
Guide Summary: Enabling Policy-to-Control Automation in ServiceNow via ComplianceCow
This technical guide explains how to automate and scale Continuous Controls Monitoring (CCM) within ServiceNow GRC/IRM using ComplianceCow.It begins by outlining core compliance concepts (policies, control objectives, entities, and indicators) then walks through how ServiceNow manages them. The document then details how ComplianceCow integrates with ServiceNow to streamline evidence collection, automate control testing, and support CCM across hybrid and cloud infrastructure.Topics include:- Policy-to-control-objective mapping in ServiceNow
- Indicator templates, scripted indicators, and control issue workflows
- How ComplianceCow automates assessments and generates structured evidence
- Integration steps for pushing ComplianceCow results into ServiceNow indicators
- Customization of supporting data
- Key challenges in scaling CCM, and how ComplianceCow addresses them
1. Understanding Compliance Management: From Authority Documents to Controls
As the IT infrastructure becomes more complex, interconnected, dynamic and changing frequently with workload demands, user needs, and emerging technologies, managing security and compliance risks have also become complex.Regulatory bodies publish authority documents defining compliance laws, regulations (such as SOX, NIS2), standards(such as NIST CSF, PCI-DSS 4.0), and guidelines that organizations must follow to manage the security risks. These documents serve as the foundation for the risk and compliance programs, helping businesses align with legal and industry-specific requirements.Organizations develop policies that specify how their business units would comply with the requirements of the authority documents. These requirements are known as citations (a passage, expression, individual requirement within an authority document). For example, to implement the NIST CSF PR citation : Safeguards to manage the organization’s cybersecurity risks are used, the organization may implement data security, access control and platform security policies.Once the internal organizational policies are established, control objectives are set up to implement the policies. The control objectives define exactly how to adhere to those policies and citations in the authority documents. For example: To implement the access control policy, a control objective may specify that Users, services, and hardware are always authenticated. To implement the encryption policy, a control objective may specify that the files and disks containing Personally Identifiable Information (PII) must be encrypted with industry recognized algorithms and protocols, such as AES (Advanced Encryption Standard). A control is a specific implementation of a control objective on an entity. A CRM database should be encrypted using an industry recognized algorithm is an example of a control. Encryption of another database containing customer complaints is another control.2. Key Terms and Core Concepts in Cybersecurity Compliance and ServiceNow GRC
| S.No | Key Acronyms | Description |
|---|---|---|
| 1 | CSF | Cybersecurity Framework. Provides guidelines for cybersecurity assessments. Example, NIST CSF, HiTrust CSF |
| 2 | CCM | Continuous Controls Monitoring. Refers to the continuous monitoring of Cybersecurity controls |
| 3 | ServiceNow GRC | ServiceNow IRM: Integrated Risk Management |
| 4 | Control Objectives | An objective, direction, or standard that acts as guidance for company interactions and operation |
| 5 | Entity | An Entity can be person, people, process(es), department(s), application(s),object(s),, server(s), external network device(s), data server(s), data warehouse(s) – essentially any asset that falls within the scope of compliance checks |
| 6 | Entity Type | A group of entities that have to comply with the same set of compliance standards. |
| 7 | Control | A control is a specific implementation of a control objective for each entity. |
| 8 | Indicators | Indicators monitor and assess controls to determine if an entity is compliant or non-compliant |
| 9 | CMDB | Configuration Management Database (CMDB) to build logical representations of assets, services, and the relationships between them that comprise the infrastructure of your organization |
| 10 | RDS | Relational Database System. Generally refers to the RDS service in AWS |
3. Implementing Policy and Compliance Management in ServiceNow GRC/IRM
ServiceNow’s Governance, risk, and compliance (GRC) (also called, ServiceNow IRM: Integrated Risk Management) empowers businesses to build effective governance frameworks. With the ServiceNow’s GRC framework, users can import regulations, identify policies, and establish policy lifecycles, assign, and test controls, create attestations, schedule regular tests, and perform issue and task management procedures to respond to compliance failures as they arise.The following diagram illustrates the steps to be performed in ServiceNow to get started with Compliance Management in ServiceNow
Image from Control Objectives and Requirements in ServiceNow GRC/IRM
This section describes how ServiceNow GRC/IRM can be configured for Continuous Controls Monitoring.Control objectives are specific goals that the controls are meant to achieve. For example: To implement platform security policy, one of the control objectives could be – Log records are generated and made available for continuous monitoringThis control objectives can have next level sub control objectives such as- Logging should be enabled
- Logs should be encrypted
- Log analysis is done periodically
- Log retention plan is maintained
- Log access is controlled
- Log file validation is enabled
Configuring Entities and Entity Types in ServiceNow GRC/IRM
Entity
An Entity can be people, departments, applications, objects, servers, external network devices, data servers, data warehouses – essentially any asset that falls within the scope of compliance checks. Usually, Entities are configuration items from the ServiceNow’s CMDB database.Entity Type
Entity type is a group of entities that have to comply with the same set of compliance standards. All instances of AWS RDS databases are an example of an Entity Type as all RDS databases need to be compliant with the same set of policy and compliance standards. Please note: An individual RDS database is an Entity in this case.In the figure below from ServiceNow, the Entity Type is AWS:S3:Bucket (all AWS S3 buckets) and Entities are individual AWS S3 buckets.
Control Objective and Entity Type Association
Control objectives, or goals, are always implemented on Entity types. For example, the control objective: Versioning is enabled would be implemented on Entity Types such as Files, Database Instances, Application Services, and S3 buckets. Associating an entity type – S3 buckets with the control objective: Versioning is enabled means that all S3 buckets should have versioning enabled for this control objective to be compliant.
Controls
A control is a specific implementation of a control objective. Controls are automatically generated when a policy or a control objective is associated with an entity type. As a result of this association, a control is created for each entity listed in the entity type for the policy or control objective.For example, when we associate the control objective: Versioning is enabled on an entity type such as S3 bucket, a control ‘Versioning is enabled’ is created for each S3 bucket (ie each entity)In the figure below, we see that a control is created for each entity
Controls can also be manually created. All the controls associated with the control objective are tested to see if they are successful in achieving the intended control objective.4. Why Continuous Controls Monitoring (CCM) Is Essential for Modern Cybersecurity and Compliance
Manual control audits, to ensure that each organizational asset and entity complies with all the industrial and governmental regulatory standards, is complex, time consuming, demanding and error prone. The IT landscape is evolving continuously and IT assets are being commissioned and released dynamically based on workloads and are more often deployed across the globe to ensure reliability and availability. A point in time audit can, by no means, provide organizational wide cyber and compliance risk posture. As a result, many organizations fail to identify vulnerabilities, security breaches and compliance failures in time, resulting in loss of millions of dollars, customer trusts, litigation and governmental fines. Hence it is imperative to perform Continuous Controls Monitoring (CCM)Continuous Control Monitoring is an automated process that continuously assesses and validates an organization’s controls to ensure compliance, security, and risk management effectiveness. It uses automation to detect control failures, identify risks, and enforce policies without manual intervention across enterprise applications, cloud environments, and security tools.The key benefits of Continuous Control Monitoring are
- Faster Issue Detection and Remediation
- Reduced Compliance Fines and Penalties
- Lower Audit Cost
- Optimized Resource Allocation
- Improved Decision-Making
- Decreased Operational Risk
- Improved Operational Efficiency
- Increased Customer Satisfaction
5. Implementing CCM in ServiceNow GRC/IRM
ServiceNow implements Continuous Control Monitoring(CCM) through Indicators. Businesses can deploy control indicators to automatically test controls on a set schedule with minimal or no manual effort. Indicators are like the control test recipe that contains instructions on what to test for the control, how to test and specifies the outputs that needs to be produced as result of the tests etc. ServiceNow’s Indicator based CCM enhances efficiency, effectiveness, and agility to bolster risk management, security, and compliance for organizations worldwide.Configuring Indicator Templates and Indicators in ServiceNow GRC/IRM for CCM
Indicator Templates
Indicator templates are associated with the control objectives, thereby allowing the creation of multiple indicators for similar controls. The Indicator template defines the parameters of the IndicatorsIn the figure below, we see that the control objective ‘Versioning is enabled’ is associated with an Indicator Template ‘ComplianceCow Dynamic Indicator Template’
Indicator Templates are of the following types – Manual, Basic and Scripted. The figure below shows a scripted indicator
- Manual: Manual indicators are used for data that cannot be retrieved from a ServiceNow instance because it comes from an external system, such as customer data from a third-party sales system. A task is sent to the user to check whether the control is compliant, and the indicator can be marked as Pass or Fail.
- Basic: Basic indicators are automated indicators based on an indicator data source. The indicator source specifies a table and a frequency at which the scores from this table are saved.
- Scripted: Scripted indicators use a custom script to conduct the test. The data is collected automatically by the logic specified in the script. If the indicator task fails, then the control is not compliant, and an issue is created. If the indicator passes the test, then the control is compliant until the next scheduled test.
Issue
If a gap is identified while testing a control, then that gap is termed as an issue. Issues are created when a control test fails and is non-compliant.Remediation Task
After an issue is confirmed, the organization identifies necessary steps to remediate the issue. To mitigate a risk you can create a remediation task to track the remediation work. If a triage was performed, the triage issue is converted into an actual issue or risk event. You can also track the issue as a recommendation or close it as a non-issue.Challenges with implementing CCM through Indicators in ServiceNow
Continuous control monitoring with ServiceNow offers several benefits
- If a gap is identified while monitoring the control, an issue is reported. This issue can be shared among various ServiceNow applications such as the Policy and Compliance Management, Risk Management, Security Operations Vulnerability Response and Audit Management GRC applications providing an enterprise-wide view of risk and compliance to quickly detect effectively detect, access, remediate and correlate risk information in an integrated way across the business.
- Issue Management life cycle is facilitated by automated, cross-functional workflows for to create issues, assign control owners, triage, remediate, review and monitor the issues
- Dashboards to view overall compliance percentage and total issues, control failures by entity and policy exceptions.
Continuous control monitoring challenges with ServiceNow
However, the GRC teams still face an uphill task in implementing CCM in ServiceNow. Here are some of the key challenges:- What data should be collected by the indicator? – Each IT asset or entity, whether a database instance or network router, generates a huge amount of real time data. The indicator has to collect the right data to evaluate the entity compliance posture
- How to access the data? – Indicators should access data from entities across geographical and cloud platforms. Data collection mechanism for each entity varies with the entity type and the cloud platforms.
- How to map the data to the required entity and control in ServiceNow – Each entity has to comply with various control objectives. Indicator has to map the collected data to the right entity and control objective to determine the compliance posture of the entity towards the control objective.
- How to evaluate and interpret the data? – The indicator should also assess whether the data fulfills the control requirements and objectives and determine the compliance status.
6. Integrating ComplianceCow to Automate CCM Workflows in ServiceNow GRC
ComplianceCow is a Security GRC Middleware providing better, contextual data to your ServiceNow GRC/IRM for Continuous Controls Monitoring. ComplianceCow integrates with complex infrastructure to perform control checks, gather evidence, analyze risks, and implement remediation measures. Customers can use pre-built assessments and controls automated for CCM for Cloud and On-premise applications, or customize or add new ones using our high-code, low-code and no-code automation studio.For more information visitConfiguring and Running Compliance Assessments in ComplianceCow
An Assessment is a collection of controls in ComplianceCow, executed for automated or manual evidence collection, evaluated for compliance. Users can run assessments on-demand or schedule as needed or simply invoke them through an API call. Users can use any of the pre-built industry assessments such as NIST 800-53, CIS Controls v8, PCI-DSS 4.0 or can build their own custom assessment.The following figure shows a NIST CSF 1.1 assessment configured for AWS. The controls are nested, and each “Leaf” control maps to the control tied to the control objective in ServiceNow.Assessments in ComplianceCow are run by providing the following information:
- Scope of assets (infrastructure, applications and services)
- Control period for which the controls are assessed
Automating Evidence Collection in ComplianceCow
An Assessment can contain manual, semi-automated or fully automated controls
- Manual controls rely on users to manually provide inputs and evidence for assessing the controls
- Semi-automated controls collect data from SYSTEMS and present them to humans-in-the-loop for review and approval. Once the workflow reaches the finality, evidence for the control is created and is evaluated for compliance.
- Fully automated controls collect data from SYSTEMS and do not require human-in-the-loop feedback.
In fully automated controls, ComplianceCow generates evidence data in standard and extended formats
- The Standard Evidence presents compliance data in standard, uniform format irrespective of the type of assessment, entity or cloud platform. The Standard Evidence also contains other contextual data such as entity location, url and other metadata to enrich the compliance data. This enables GRC team members to apply rules to determine compliance, irrespective of the underlying entity: technology or infrastructure or application.
- The Extended evidence presents raw data collected from the entity. This evidence format is dependent on the type of entity, the data source and cloud platform. This data is useful when the GRC team wants to deep dive into the entity’s setup to investigate and triage a non-compliance issue.
How do the Control Evidence files from ComplianceCow integrate with ServiceNow GRC/IRM Indicators for CCM?
The following steps outline how ComplianceCow evidence is collected, mapped, and pushed into ServiceNow to drive automated indicator evaluation and issue lifecycle management.- A custom scheduled job in ServiceNow triggers a pre-configured assessment in ComplianceCow. This job can also be run on demand.
- The ComplianceCow assessment connects to the entities and gathers required data to check for the entity’s compliance to the control. It also contains the metadata to facilitate ServiceNow Indicator to map the compliance data to the required entity and control, evaluate and interpret the data.
- Once the ComplianceCow assessment ends and the evidence files are generated, ComplianceCow Platform API Service for ServiceNow pushes the evidence data to the custom tables in ServiceNow.
- The ServiceNow’s out of the box scheduled job ‘GRC indicator nightly run‘ executes the indicators.
- ComplianceCow provides a script based custom indicator template, the ComplianceCow Dynamic Indicator Template, that reads data from the ServiceNow’s custom tables(populated by ComplianceCow Platform API service) and maps the data to the rightful entities, controls and control requirements and determines the compliance status of the control.
- The ComplianceCow indicators(created off the ComplianceCow Dynamic Indicator Tempate) communicates the compliance status of the control to ServiceNow.
- ServiceNow creates an issue upon a control failure.
- If the next ComplianceCow assessment indicates that the failure has been remediated, then ServiceNow declares that the control as compliant and automatically closes the issue.
On clicking the Indicator Result link, we get the Indicator Results screen. This screen shows that the Result check is unchecked indicating a control test failure.
Customizing Supporting data for Control objectives
ComplianceCow displays the compliance status and meta data collected in the standard format as evidence for the control. However, at times, the users may need additional supporting data to know more about the control’s compliance posture. For the same reasons, ComplianceCow assessments generate more than one evidence for few assessments.In such cases, the evidence which has the complaince status and meta data is configured as the primary evidence and additional evidences generated for the control are configured as supporting evidences. In such cases, the primary and supporting evidences are together displayed as links in the Supporting data section for the Indicator results.
7. Closing Summary: How ComplianceCow Extends ServiceNow GRC for Scalable Compliance Automation
ComplianceCow is a ServiceNow Build Partner, and can help you maximize your ServiceNow GRC/IRM investment by making it super easy to automate IT and Security controls for GRC, and to continuously monitor them on an ongoing basis.ComplianceCow integrates with 100s of Cloud Infrastructure Services and Applications, and allows you to easily customize existing automation or build net new ones for your On-Premise Applications and Services as well.Your GRC team no longer has to herd emails to manually collect, curate and upload evidence into ServiceNow. ComplianceCow does all the repetitive evidence collection and controls testing tasks, so that you and your team can focus on higher value functions such as analysis and remediation.ComplianceCow, through its unique Compliance Graph and Large Language Model and GenAI integration, allows your users to become significantly productive with analysis, remediation and response of your Cybersecurity Risk, Compliance and Governance estate.Appendix: ComplianceCow Architecture and CCM Workflow Diagrams
Appendix – A – ComplianceCow Architecture and CCM Workflow Diagrams
This architecture diagram shows ComplianceCow as a Security GRC Middleware
It integrates with:- Security controls frameworks (CIS, OWASP, PCI, FFIEC)
- Systems (AWS, Azure, GCP, Kubernetes)
- Collaboration tools (Slack, Teams, Gmail)
- DevOps platforms
- Consumption layers (Postman, VS Code, Jupyter, TensorFlow),
- Reporting tools (Power BI, Tableau, Google Data Studio),
- Remediation systems (Jira, ServiceNow, Git).
This architecture diagram shows ComplianceCow as a Security GRC Middleware
The process shows a GRC user initiating assessments in ServiceNow, which then calls ComplianceCow to collect evidence from customer applications (cloud, on-prem, SaaS, PaaS). ComplianceCow sends the evidence back to ServiceNow for compliance reporting. Advanced users can perform customization and analytics. Labeled steps include GRC user actions, system interactions, and evidence routing between platforms.Appendix – B – ComplianceCow Powering Agentic Security GRC for the Enterprise
This Platform Architecture diagram shows ComplianceCow’s capabilities across Core APIs and GenAI Plugins
Modules include:- Controls Catalog with Common Controls Framework (CCF)
- Evidence Collection via Automation Studio (high-code, low-code, no-code)
- Workflow Studio for human-in-the-loop collaboration
- Webhooks for Remediation and Response
- Graph Insights using Neo4j
- An LLM Parser for standards and policy ingestion
- Natural Language Q&A and summarization
- SQL and Workflow Co-Pilots
- Rule automation agents based on natural language input
Security GRC Automation
That Works
and remediate issues across complex infrastructure
before audits, not after.