What is cloud detection and response (CDR)?

Importance of cloud detection and response

Despite its many benefits in speed, scalability, and cost, the cloud is not immune to cyber threats. Because of these threats, businesses must prioritize security and invest in robust cloud threat detection and response capabilities. 

To effectively detect and respond in the cloud, CDR is a critical requirement for cloud-based organizations. CDR provides comprehensive detection capabilities against even the most advanced cloud cyber attacks, protecting sensitive information, increasing visibility, improving compliance, and shortening response times.

CDR improves cloud security for organizations because it:

• Protects sensitive data: Cloud systems often contain sensitive information such as personal data, financial information, and trade secrets. CDR helps organizations detect and respond to threats that target this information, reducing the risk of data breaches and other security incidents.
• Increases visibility: CDR helps organizations achieve greater visibility into the security of their cloud systems, making it easier to detect and respond to threats. This increased visibility also helps companies make more informed decisions about their security posture and identify areas for improvement.
• Enhances compliance: Many regulations and standards, such as the Payment Card Industry Data Security Standard (PCI DSS), require organizations to implement robust security measures. CDR helps meet these requirements and maintain compliance with relevant regulations.
• Improves response times: With CDR, organizations can detect and respond to threats faster, reducing the impact of security incidents and minimizing downtime. This is especially important in today’s fast-paced business environment, where every minute of downtime can result in lost revenue and damaged reputations.

Why do cloud-native resources need specialized security tools?

Suppose you’ve been using traditional VMs for a while and have grown accustomed to conventional security solutions like firewalls, intrusion detection systems, and endpoint detection and response (EDR) tools. In that case, you’re probably wondering why you need to add CDR tooling. 

Cloud-native resources possess a particular set of characteristics (such as their dynamic, complex, and highly distributed nature) that make traditional security tools inadequate for addressing cloud security needs. For example, it may be difficult to maintain a consistent security posture with containers and Kubernetes because their deployment and scaling processes are complex and fast. When containers are managed, deployed, and scaled quickly, a traditional security solution might struggle to keep track of all the security configurations involved. 

Furthermore, 60% of containers now only live for one minute or less. This ephemerality is kryptonite for EDR agent visibility. Using Kubernetes also introduces new attack surfaces that can be challenging to monitor and inspect. A traditional intrusion detection system or EDR may lack the end-to-end visibility into Kubernetes infrastructure necessary to address this type of threat.  

CDR tools are built natively for cloud resources, which gives them a significant advantage (and access to the cloud resources). For example, CDR tools can efficiently perform real-time security monitoring, threat detection, and response despite the dynamic nature of scalable cloud-based workloads. Traditional threat detection and response solutions like EDR have shortcomings in their ability to detect, correlate, and provide cloud context.

How cloud detection and response (CDR) works

CDR offers a solution to protect cloud systems from security threats by utilizing a variety of security tools and techniques. 

CDR monitors cloud workloads and activity in real time. CDR continuously inspects behavior across containers, VMs, serverless functions, and cloud control planes to surface suspicious activity as it happens. Think of it as an airplane’s onboard systems that constantly monitor air speed, temperature, engine performance, elevation, and so on. 

CDR also detects threats using curated rules, machine learning, and behavioral techniques to identify a broad range of attacks, including cryptomining, privilege escalation, and lateral movement. This elevates signals that are indicative of malicious activity, enabling analysts to initiate their response actions sooner. 

Correlations of signals from log, control, data, and identity planes enable analysts to understand the whole picture of an attack, and to mount a more comprehensive and effective response. In this way, CDR delivers more in-depth correlation capabilities than traditional tools such as EDR. 

CDR also enables fast, automated and manual responses in cloud environments. This helps to reduce dwell time and limit the impact of malicious threat actors. 

All of these components work together to provide organizations with comprehensive protection and resilience against security threats in cloud environments. Some of these are discussed in depth in the following sections.

Cloud threat prevention

Implementing effective cloud threat prevention strategies and technologies is crucial for organizations operating in the cloud, helping to protect sensitive data, maintain compliance, prevent disruption, and increase security resilience.

Strategies and technologies used for cloud threat prevention

The various strategies and technologies used for cloud threat prevention include:

Identity and access management (IAM) 

IAM is critical to managing organizational cloud posture. A common practice is to follow the principle of least privilege or POLP. This practice helps to ensure users, applications, and services have only the minimum access necessary, making malicious behavior more difficult. Organizations who implement these practices regularly audit permissions and remove unused or excessive privileges to mitigate risk. 

Multi-factor authentication (MFA) is another preventative control that can reduce risk. A proactive posture is to enforce MFA for all users, with extra focus on high-risk  identities with administrative privileges.

Federated identity and single sign-on (SSO) structures leverage centralized identity providers to manage access for their organization. 

Network security

Microsegmentation is where networks are divided into segments to limit lateral movement in case of a breach. Think of it as creating insulated silos. 

Virtual firewalls and security groups can be implemented to use cloud-native tools in order to strategically restrict access between workloads.

Secure VPN and private connectivity can work together to protect data through encryption and protection. Think of this as a virtual tunnel that transmits encrypted data from point A to point B. 

Threat monitoring and detection

Cloud-native monitoring tools operate like an always-on security camera system, recording behaviors across the organization’s cloud estate. 

Threat detection is implemented with rules, policy, machine learning, behavior, and AI-based detection capabilities to identify and alert on unusual and potentially malicious behavior patterns.

SIEM integration is utilized by many security teams to aggregate logs and events in a security information and event management (SIEM) system for correlation and alerting across many security inputs. 

Data protection in the form of encryption is a common practice. Many organizations encrypt their data in transit and also while at rest for strong encryption standards.

Data loss prevention or DLP tools are used to help mitigate the loss or leakage of sensitive information from either internal or external threats. 

Maintenance of backups and disaster recovery plans can be automated to ensure enterprise resilience in the event of an attack. These backups and plans should be tested and evaluated regularly. 

Configuration and compliance management enable teams to mitigate misconfigurations that may lead to a breach and help organizations stay on top of compliance and regulatory requirements 

Policy as code

Policy as code refers to implementing security policies using tools like HashiCorp Sentinel or Open Policy Agent.

Incident response, recovery, and forensics tooling enable security teams to utilize defined playbooks and automated workflows to eradicate threats. Forensic tooling allows the security or forensics teams to maintain logs and snapshots, among other forensic data, as they conduct their post-incident forensic investigation.  

Cloud detection and response service

A CDR service is a managed service provided by a third-party vendor that offers organizations security management for their cloud environments. The service can include capabilities such as real-time threat detection, automated response, and security management, as well as regular reporting and analysis of security events. A CDR service is ideal for organizations that do not have the internal resources or expertise to manage their cloud security in-house. 

Benefits of using a cloud threat detection and response service

The benefits of using a CDR service include:

• Faster cloud threat detection: CDR services provide organizations with 24/7 threat detection, allowing them to identify and respond to potential threats quickly and effectively. This round-the-clock protection increases the probability of catching malicious behaviors like lateral movement, privilege escalation, and data exfiltration sooner. 
• Cloud expertise and team cost savings: Organizations moving to the cloud can face skill gaps, as teams that previously implemented traditional security may lack the specialized knowledge needed to secure cloud infrastructure. Building a new team or training a current one takes time and money. It can also pull individuals away from their core business initiatives and important tasks in their security roles. 

Cloud detection and response (CDR) tools

Cloud detection and response (CDR) tools are used to detect and respond to threats in their cloud environments. These tools offer features like threat intelligence, real-time threat detection, automated response, analytics and reporting, and integration with existing security solutions. CDR tools are ideal for organizations that have the internal resources and expertise to manage their cloud security in-house.

Key components of cloud detection and response tools

The key components of CDR tools include:

• Threat intelligence: Threat intelligence allows analysts to identify and prioritize potential threats, enabling organizations to focus their resources on the most critical security issues.
• Real-time threat detection: CDR tools provide real-time threat detection, allowing organizations to quickly identify and respond to potential threats.
• Automated response: Automated response capabilities allow organizations to quickly isolate affected systems and take remediation actions to prevent further damage.
• Analytics and reporting: CDR tools provide organizations with analytics and reporting capabilities, enabling them to track and monitor their security posture and identify areas for improvement.
• Integration with existing security solutions: Integrations with existing security solutions allow organizations to take a holistic approach to security management.

Choosing a cloud detection and response tool

When choosing a CDR tool, you should ensure that you select the tool that is right for you and that it is aligned with your organization’s needs. Here are some best practices to keep in mind when choosing a CDR tool:

1. Runtime threat detection in real time with advanced response capabilities

Any aspect of cybersecurity requires speed in both threat detection and response because time is of the essence. Cloud threats and their environments are more sensitive to speed due to automation fueling faster cloud attacks. CDR solutions should have strong automation capabilities to reduce the time it takes to detect and respond to potential threats before they escalate and spread to other sensitive workloads.

2. Real-time context, correlation, and prioritization with low false positives

Many security teams are inundated by noisy alerts. An effective CDR solution should deliver deep cloud context and correlate signals to create a prioritized list of threats. Low false positive rates further reduce noise ratios, but transparency in detection logic is necessary to rapidly adjust rules and policies for prevention of further incidents. 

3. Deep Kubernetes and cloud-native integration 

While traditional security tools such as EDR often lack visibility into orchestrated environments like Kubernetes, CDR excels at providing deep visibility into these ephemeral environments. An effective CDR solution will be built from the ground up to support containers, Kubernetes, and multi-cloud environments. They should automatically enrich events and larger threats with Kubernetes metadata such as the namespace, pod, cluster, and more.

4. Independent multi-cloud and hybrid support

Most organizations have adopted multiple cloud platforms (including public, private, and hybrid cloud infrastructures) to cater to different organizational use cases and regulations. This can  create complex cloud environments that require specialized CDR tools to provide adequate visibility for meaningful protection. Adopting a CDR tool that is independent of a specific cloud provider with multiple levels of environmental support will simplify security management across even the most complex environments, all while enhancing flexibility and visibility.

5. Integrated threat intelligence

Threat intelligence is essential, and should enhance CDR solutions by providing real-time, curated indicators of compromise (IOCs) from public, proprietary, and community sources. These IOCs should be correlated with relevant runtime context such as system calls, Kubernetes metadata, and network activity in order to deliver high-confidence, high-fidelity alerts. 

6. Unified platform for security, compliance, and forensics

CDR solutions should go beyond just threat detection in order to support investigation and compliance. An effective solution should combine detection, incident response, compliance, and forensic capabilities into a single platform. These capabilities should enable teams to capture detailed activity records for post-mortem analysis with process-level visibility. An effective CDR solution should be capable of executing security workflows independently, but also should integrate with SIEM, ticketing, and SOAR tooling to be adaptable to any established workflows. 

7. Protect AI, accelerate with AI

Effective solutions should also protect AI workloads with deep runtime visibility, real-time threat detection, and compliance controls tailored for containerized and Kubernetes-based environments where AI applications often run. AI-powered security assistants should be thoughtfully integrated into CDR solutions to help teams investigate incidents faster, surface critical risks, and generate remediation suggestions. AI-powered security assistants should reduce alert noise, enable teams to rapidly understand complex threats, and automate routine tasks. This dual approach ensures that AI systems are protected and that security operations are augmented by AI for greater speed and precision. 

Conclusion 

CDR is an essential component of a comprehensive security strategy for organizations operating in the cloud. CDR solutions provide organizations with the protection and resilience they need against the growing threat landscape in the cloud by combining threat prevention, detection, and response.