As access rules rise in complexity, SAP’s role-based authorization model (RBAC) is reaching its limits. A “role-explosion” has been developed by introducing complexity and overhead to role management through one-off role derivations. And it requires unscalable customizations to enforce access controls, down to a field-value level, beyond the role of a user.
The SAP ERP (SAP ECC) and S/4HANA main components exploit static positions for access control. These positions have reached their limits in a dynamic workplace since static positions do not leverage contextual attributes. Besides, as users move around the enterprise, changing their scope of work, static positions remain unchanged. Static roles can quickly get redundant unless constantly provisioned, leaving an enterprise exposed to potential threats.
Businesses need data governance and business policies to be synchronized. By extending existing static functions with attribute-based controls, access management can be handled dynamically. In addition, access considered risky (only based on context) may be limited.
The Challenges of Access Management in SAP
The following are some of the critical challenges when it comes to the management of access in SAP:
Static Role-Based Policy
Users are divided into broad categories known as roles or permission lists by role-based access controls (RBAC). Restricted to these static categories, RBAC is unable to use dynamic information such as project ID, IP address, company code, location, device type, and more to authorize access. For highly sensitive transactions and data, RBAC alone does not provide the optimum safety level.
Role Explosion in SAP
Over time, SAP apps get crowded with thousands of positions and permission lists, a phenomenon known as role explosion. Maintaining these lists requires constant vigilance, and keeping them updated can quickly become one of the most time-consuming tasks. It can also become a source of security breaches.
Friction Created by Custom Role Development
There are circumstances where custom development is necessary to add access control constraints based on complex attributes such as IP address, nationality, location, business unit, and project affiliation. However, these customizations create user friction to accommodate even small discrepancies between static and dynamic rights.
Some steps that organizations should take to address the challenges listed above are as follows:
Transaction Policies and Granular Access
Customers can lower the amount of acceptable risk by deploying granular access controls to reinforce field and transaction-level security. You can block malicious activity in real-time and monitor privileges that are given by enforcing restrictions on who can access an application, where, when, how they can have access to it, and what they can do with it.
Attribute-Based Access Controls
The best approach is data-centric protection and compliance policy. A data-centered security model helps you align security policies with your business needs and limit the visibility of sensitive data and transactions. Your core SAP ERP data and transactions are an excellent starting point for incorporating access controls based on user activity attributes and monitoring and analytics, so you have more insight into who accesses and potentially modifies your data.
Data-Centric Security Policies
You need to restrict access to sensitive data and transactions if the background is suspicious. Such a context may, for example, be user attributes, data attributes, operation type, user location, IP address, time of day, amount of money transacted, number of transactions, user activity patterns, and duty segregation.
Extending SAP GRC Policies for Access Control
It is important to expand current access control policies for clients using SAP GRC and to improve reporting capabilities. Organizations need to use what they have already implemented to protect themselves.
Masking and Redaction of Data
Companies may opt to block, mask, or redirect access to sensitive data fields with available data protection solutions using a single policy. Data masking prevents sensitive data from being exposed; it enables users to access data with articulated intent. Thus, by reducing unnecessary disclosure of PII and other sensitive data, regulatory enforcement management is improved.