Zscaler > Case Studies > Goulston & Storrs Enhances Client Data Security with Zscaler Workload Segmentation

Goulston & Storrs Enhances Client Data Security with Zscaler Workload Segmentation

Technology Category

Analytics & Modeling - Machine Learning
Cybersecurity & Privacy - Network Security

Applicable Industries

National Security & Defense
Telecommunications

Applicable Functions

Maintenance

Use Cases

Inventory Management
Tamper Detection

Services

Cloud Planning, Design & Implementation Services
Data Science Services

About The Customer

Goulston & Storrs is an Am Law 200 law firm with offices in Boston, New York, and Washington, DC. The firm has more than 200 lawyers across multiple disciplines and is well known as a real estate powerhouse with leading-edge corporate, capital markets and finance, litigation, and private client and trust practices. The firm has been facing challenges in securing its client data due to evolving threats and outdated security mechanisms. Since partnering with Zscaler, the firm has been able to keep pace with the demands of its modern application environment and secure its network beyond the visibility and control offered by traditional firewalls.

The Challenge

Goulston & Storrs, an Am Law 200 law firm, faced several challenges in securing its client data. The firm needed to continually increase its level of protection to keep up with evolving threats. Operational inefficiencies due to outdated security mechanisms that did not align with modern applications were also a concern. The firm's security measures were complicated by policy management issues. The firm's private and public clouds, which are data-rich targets for cybercriminals, were often secured with firewall-based controls. These controls allowed malicious communications to piggyback on permitted network policies due to a lack of visibility beyond primitive network attributes. The firm needed a solution that could provide application-level enforcement and continuous trust assessments for gap-free security coverage.

The Solution

Goulston & Storrs partnered with Zscaler to secure its network beyond the visibility and control offered by traditional firewalls. Zscaler Workload Segmentation provided a level of security sophistication that was previously unavailable. Unlike perimeter defense security mechanisms, Zscaler Workload Segmentation modernized network security by using Trusted Application Networking to protect the cloud and data center where traditional methods were ineffective. The solution reduced the attack surface and mitigated two major risks—exposure of credentials and penetration of the network perimeter. Zscaler Workload Segmentation's topology mapping provided an accurate representation of the ever-changing environment and eliminated potential attack paths. The solution also safeguarded the firm's most valuable applications and financial software with a new trust model that approves communications based on the trustworthiness of software, hosts, and users.

Operational Impact

The implementation of Zscaler Workload Segmentation has resulted in several operational benefits for Goulston & Storrs. The firm has experienced a significant reduction in the risk of client data exfiltration. Operational efficiencies have been created by machine learning, reducing work associated with protection policy creation and management. The firm no longer has to balance security and business agility priorities. With one-click enforcement of automatically generated policies, the time it takes to implement zero trust has been drastically reduced. The ease of implementation and maintenance of Zscaler Workload Segmentation compared to other security deployments has made it an obvious choice for the firm.

Quantitative Benefit

Reduced the network attack surface to cover 99.99 percent with optimal protection policies
Implemented Zscaler Workload Segmentation without requiring changes to applications or network infrastructure, leading to faster time-to-value
Machine learning automatically modeled the firm’s application communication patterns in less than 72 hours