Leveraging Neo4j for Effective Identity Access Management

A while ago, I explored Neo4j, a powerful graph database, earlier for the implementation of the "six degrees of separation" concept. I like the way it simplified the complexity of the relationship visually with the advantage of flexible schema representation.

After some time, while exploring another use case in Identity Access Management (IAM) policies, I revisited Neo4j. I was amazed by the analytical capabilities it offered and the potential for building Generative AI applications using Neo4j’s GraphRAG.

In this article, we will see how we can use Neo4j for IAM data modeling, its use cases, guidelines, and best practices, and how Neo4j can be integrated with existing IAM systems and tools.

Identity Access Management

Identity Access Management (IAM) doesn’t need an introduction or a justification for its need, with so much happening in the field of cybersecurity. Ensuring authorized individuals, groups, and systems have appropriate access to the right resources at the right times. The key pillars of IAM, Access Management, Identity Governance and Administration, and Active Directory Management, are not a luxury anymore. Rather, they have become the key necessities of any organization looking forward to managing effective access management.

Neo4J

Neo4j is a powerful graph database that stores data and represents the relationship between data objects in a flexible graph structure. What I personally liked about Neo4j is the visual representation of complex scenarios. This helps in understanding simple yet powerful concepts of nodes, relationships, and attributes to depict, analyze, and implement complex use cases.

Neo4j can be effectively utilized to model, analyze, and enforce IAM policies. It helps an organization improve IAM compliance with adherence and audits of the implemented policies.

Why Neo4j for IAM?

There is so much in common between the concepts of IAM and what Neo4j has to offer. The use case on fraud detection helped me understand and leverage the concepts for IAM.

Representation of IAM Entities Using Graph Model

Initially, I explored this for the concept of "six degrees of separation," where the relationships can be visually represented. Similarly, IAM involves complex relationships between users, roles, groups, resources, and access permissions. Neo4j's native graph model simplifies this complexity by directly representing entities as nodes and their associations as edges. We will see the representation in detail under the "Data Modelling" section.

Real-Time Query Capabilities

To be able to verify and validate access rights, user hierarchies, group memberships, and other critical access privileges, Neo4j provides real-time query capabilities.

Agility

The changes in roles, policies, and resources can be easily accommodated by Neo4j's schema-less model. It can also be used with a schema when needed. This flexibility is critical as the nature of IAM is so dynamic to be able to handle cyber threats and other challenges effectively.

Analytical Capabilities

As part of audit and compliance, it is important to be able to identify orphaned accounts, notify excessive permissions, and detect policy violations. Neo4j’s Cypher query language provides analytical capabilities to perform such complex tasks.

Data Modeling in Neo4j for IAM

We all know how crucial it is to have efficient and effective Data Modelling for any architecture. Neo4j leverages the concepts of graph theory, such as Vertices (also known as nodes), Edges (also known as relationships), and data points (also known as attributes).

Below are some examples of how nodes, relationships, and attributes can be represented in IAM.

Nodes

• User – represents an individual or service account
• Group – represents collections of users
• Role – represents a set of permissions
• Resource – represents a system, file, or service that requires access control
• Permission – represents access rights (e.g., READ, WRITE, EXECUTE)

Relationships

• (User)-[:MEMBER_OF]->(Group)
• (User)-[:ASSIGNED]->(Role)
• (Group)-[:ASSIGNED]->(Role)
• (Role)-[:GRANTS]->(Permission)
• (Permission)-[:APPLIES_TO]->(Resource)

Attributes

Each node and relationship can have attributes like timestamps, descriptions, and status flags for audit and compliance tracking.

A sample schema is given that depicts two scenarios:

1. When a user is assigned to a role:
   Plain Text

    

   (User)-[:ASSIGNED]->(Role)

2. When a user who is part of a certain group assigned to a role grants certain permission that applies to a certain resource:
   Plain Text

    

   (User)-[:MEMBER_OF]->(Group)-[:ASSIGNED]->(Role)-[:GRANTS]->(Permission)-[:APPLIES_TO]->(Resource)

I can’t think of any use case of IAM that may not be able to be implemented by Neo4j. In the next section, we will see some of them.

Use Cases

Access Control

This refers to being able to understand if a user has access to a certain resource.

Query: "Does user X have access to resource Y?"

Cypher query example:

MATCH (u:User {id: 'userX'})-[:ASSIGNED|MEMBER_OF*]->(r:Role)-[:GRANTS]->(p:Permission)-[:APPLIES_TO]->(res:Resource {id: 'resourceY'})

RETURN p

Compliance Audits

This refers to identifying users or roles with access to sensitive resources. Also, we can detect permission assignments that violate the policy of the organization.

It can help analyze role hierarchies and remove redundant roles.

MATCH (r:Role)-[:GRANTS]->(p:Permission)

WITH r, COUNT(p) as permissionCount

RETURN r, permissionCount ORDER BY permissionCount DESC

It can detect orphaned accounts with the query to find users not assigned to any group or role.

MATCH (u:User) WHERE NOT (u)-[:MEMBER_OF|ASSIGNED]->(:Group|:Role)

RETURN u

Access Hierarchy

This addresses one of the complex queries on "What are all the resources user X can access through group Y?"

Cypher query example:

MATCH (u:User {id: 'userX'})-[:MEMBER_OF]->(g:Group {id: 'groupY'})-[:ASSIGNED]->(r:Role)-[:GRANTS]->(p:Permission)-[:APPLIES_TO]->(res:Resource)

RETURN res

It is important to understand the guidelines and best practices to implement Neo4j effectively for IAM. Listing below some of the guidelines:

Guidelines and Best Practices

• Security. Neo4j provides built-in role-based access control (RBAC), which can be leveraged to ensure secure access to the graph database.
• Indexing. To be able to optimize query performance, the recommendation is to use indexes on frequently queried properties like User.id, Group.id, and Resource.id
• Ingestion. Since the data ingestion can impact the performance and load, the suggestion is to use batch imports or streaming tools like Neo4j’s ETL or Kafka Connectors for efficient data loading.
• Monitoring. Despite the effective architecture & implementation, over a while, due to various reasons, the performance may degrade. Below are some of the recommendations.
  • For visualization and tracking performance, Neo4j’s monitoring tools (e.g., Neo4j Bloom, Prometheus) can be leveraged.
  • As part of regular security audits and maintenance, the nodes and relationships are to be validated.

An organization can have multiple IAM systems and tools to strengthen its security posture. The below section details how Neo4j can be integrated with existing systems and tools.

Integration

Neo4j can be integrated with various IAM systems and tools, such as:

• OAuth and OpenID connect. To model and analyze token-based access, Neo4j can be used.
• Active directory. To achieve centralized access control, the user and group data can be imported.
• Security Information and Event Management (SIEM) tools. In one of my articles, I have detailed how Elastic can be used as an effective SIEM tool. Neo4j queries and analytics can be fed into such systems for real-time monitoring.
• Custom APIs. To enable IAM functionality in applications, Neo4j’s drivers can be used to build APIs using Neo4j’s drivers (e.g., Java, Python, or JavaScript). Please refer to Neo4j’s documentation on creating applications for further details.

Summary

As the complexity and challenging requirements of Identity Access Management increase, we need a system such as Neo4j that provides a robust, flexible, and scalable. The visual representation and graphical analytical capabilities are particularly well-suited for modeling relationships, real-time visibility, enhancing compliance, and optimizing IAM policies and processes of an organization.