Case Study | SaaS / CRM

How We Secured a Leading SaaS CRM: Unmasking Exposed Docker Images with ASM

A $100M revenue SaaS CRM company discovered critical exposed Docker images containing sensitive financial data through Strobes ASM.

The Challenge

Hidden Vulnerabilities in a Complex Environment

Despite a strong security system, the client faced challenges managing their complex digital environment. The growing threat of cyberattacks meant vulnerabilities could be missed. Human error and misconfigurations were potential risks.

During a routine scan, the ASM system identified a critical anomaly: an exposed Docker image containing sensitive financial data.

The Solution

AI-Powered Attack Surface Management

Strobes ASM deployed an automated, AI-powered approach to identify, assess, and prioritize exposed assets.

1

Automated Discovery

Utilized keyword permutations to systematically search Internet repositories for publicly exposed Docker images.

2

AI-powered Risk Assessment

Analyzed content of identified images by executing pre-defined commands within the container.

3

LLM Analysis

AI-powered LLM analyzed extracted data, assessing the risk level associated with each image.

4

Prioritized Response

Based on the LLM's confidence score, the ASM platform prioritized critical vulnerabilities for immediate action.

The ASM system identified a critical anomaly that traditional scanning had missed: an exposed Docker image containing sensitive financial data.

Benefits and Outcomes

Early Threat Detection

Continuous monitoring through ASM allows for early identification and mitigation of vulnerabilities.

AI-Powered Prioritization

Leveraged AI to prioritize critical threats based on objective risk scoring.

Swift Response

Automated notifications and streamlined processes facilitated rapid response to vulnerabilities.

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