Using Managed Detection and Response Services for Cloud SecOps

By Paladion

January 20, 2020

Cloud SecOps face numerous challenges. Organizations must be prepared to defend against new cloud-specific threats, balance the shared responsibility security model, and handle hybrid architectures – just to name a few things. Couple this with an industry-wide cybersecurity employee shortage, and organizations are ultimately left vulnerable to serious cyber threats.

Next-Generation Managed Detection and Response (Next-Gen MDR) brings an effective solution to managing cloud security challenges. Having already proven its success in the data center, MDR is now improving cloud security management.

Next-Gen MDR solutions bring broad threat detection and comprehensive response capabilities to cloud-based, on-premises, and hybrid architectures. They leverage cloud-native tools and employ artificial intelligence (AI) to fill detection gaps and unify input from multiple security tools. On the response side, the platforms automate responses to enable SecOps teams to concentrate on the most severe threats and work more efficiently.

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A Quick Review: Next-Gen MDR vs Traditional MDR

MDR services vary, of course, but in general, they take a reactive approach. The service provider monitors the customer’s infrastructure and digital assets. When they receive an alert, they respond to it. They typically use tools like Security, Incident, and Event Management (SIEM) solutions to manage multiple security systems such as IDSs.

In contrast, Next-Gen MDR takes a proactive approach to both detection and response. It performs the same monitoring functions as earlier MDR service offerings but adds a critical new element: threat hunting. Next-Gen MDR is continually looking for evidence of attacks.

Why Next-Gen Managed Detection and Response Services?


Next-Gen MDR solutions have been developed specifically with cloud use cases in mind and integrate deeply into an organization’s entire cloud stack. This means that they can work seamlessly across multiple clouds, including containers, microservices, cloud consoles, and data repositories while leveraging existing security tools. For example, a Next-Gen MDR solution can provide threat detection by using unified SIEM, EDR, user access, and flow data across AWS, Azure, private clouds, and traditional data centers.

With complete integration, the MDR solution can access data about the status of each element of the stack to detect and respond to threats. The offering also includes a regular review of their configurations to ensure that no new solutions have created unintended vulnerabilities.

For robust security in the cloud, Next-Gen MDR solutions must completely integrate into the entire solution stack.

Automation and Artificial Intelligence

A security operations center (SOC) is typically on the receiving end of outputs from multiple security systems, including NGFW, unified threat management (UTM), and more. This security data piles up, even with analytics systems like SIEM in place. An underresourced SecOps team may be overwhelmed by the deluge of security data.

Next-Gen MDR automates the handling of huge volumes of security data, which helps reduce the workload placed on SecOps teams. It pulls data from a wide range of existing security products like IPSs, firewalls, UTMs, anti-virus, SIEMs, endpoint detection and response solutions, web application firewalls (WAFs), user behavior analytics (UBA), and cloud security solutions.

Continuous Security Posture Management (CSPM)

To be successful, cloud security and countermeasures must be continuous rather than episodic. Next-Gen MDR services should offer continuous security posture management (CSPM). CSPM continuously tracks cloud assets and configurations for compliance with security policies.

Full Response

Next-Gen MDR contains threats and orchestrates a complete response to evict the attacker. Some responses can even be fully automated, with the client’s agreement. The SOC’s goal is to avoid the unfortunate but common scenario where a managed security service spots a threat, opens a ticket, and sends it over the wall to the customer. Given the pace of attacks and the overloaded nature of SOCs, that can be a formula for disaster.

Use Cases

Next-Gen MDRs manage a wide variety of cloud cybersecurity use cases, filling in detection and response gaps created by shortages of personnel and tool limitations. In addition to cyber defense countermeasures like mitigating APTs and securing SaaS apps, common cloud use cases include:

  • Stopping data leakage
  • Detecting fraud
  • Preventing insider attacks
  • Ensuring security compliance with security frameworks

Next-Gen Managed Detection and Response Services in Action

A Next-Gen MDR platform should be able to provide the detection and response service timeline depicted in the “Left-of-Hack” and “Right-of-Hack” diagram. The diagram below offers a useful way to visualize the timing of threat detection and response actions. Each of the six steps within this workflow represents processes occurring along the timeline of an attack. The “Left-of-Hack” portion includes the proactive steps taken to detect threats before they occur. The earliest form of detection is threat anticipation, followed by threat hunting, which happens closer to the time of a hack, while security monitoring serves as the detection capability occurring up to the moment of a possible compromise.


The “Right-of-Hack” includes the time-to-respond workflows, which follow a similar time-based pattern. The incident analysis takes place immediately after an attack, followed by auto-containment, and then response orchestration.

A robust MDR solution includes both pre- and post-attack activities.

Ensure Security with Managed Detection and Response Services

AI-driven Next-Gen MDR makes it possible to establish a robust and enduring security posture in the cloud. With deep detection and full response capabilities, advanced Managed Detection and Response services help organizations overcome limitations on staffing as well as the effects of a reactive mindset and proliferating security technologies. It enables SecOps to stay on top of complex, constantly evolving cloud environments. AI and ML power the detection capability and inform the automated incident response processes, complementing, and augmenting the in-house SecOps team’s ability to secure its assets in the cloud.

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