Beyond the Endpoint: Why EDR/XDR Struggles in the Cloud

The cybersecurity landscape has dramatically shifted with the rise of cloud computing. While Endpoint Detection and Response (EDR) and Extended Detection and Response (XDR) have proven valuable in protecting traditional endpoints, the cloud introduces a new set of challenges. This post examines why these solutions, rooted in endpoint-centric approaches, may fall short in the cloud, highlighting the need for a new generation of cloud protection strategies designed for SaaS, IaaS, and PaaS environments.

Introduction to EDR/XDR: Evolution 

In the field of cybersecurity, Endpoint Detection and Response (EDR) and Extended Detection and Response (XDR) systems were developed to combat threats in digital environments. Originally evolving from traditional antivirus (AV) software, these systems have expanded their scope over time.

From Antivirus to EDR

Traditional antivirus solutions focus on detecting malicious activities by scanning for virus fingerprints, which are hashes of files that are known to contain malware. Their effectiveness depends on the database of known malicious hashes. This determines how much malware the agent can detect. It also depends on the impact on system resources. The agent should use as few resources as possible. As cyber threats evolved, the need for more adaptive solutions led to the development of EDR. EDR systems are designed to go beyond static file detection by monitoring for suspicious behaviors in real time.

Scope Expansion

EDR technologies have expanded from their initial focus on Windows PCs to encompass Mac and Linux systems, reflecting the diversity of today’s computing environments. However, due to the nature of the endpoint market, the main focus for both the attackers and defenders stayed on Windows endpoints throughout the 2010s. To show this asymmetry, let’s use the open-source ClamAV as an example. Even as late as 2024, around 95% of the records of its Virus fingerprint database are Windows malware, 3% are MacOS, and 2% are Linux. 

Introduction of XDR

In the mid-2010s, Nir Zuk, the founder of Palo Alto Networks, introduced the term XDR. XDR builds on EDR by combining data from different security layers, such as network traffic, to offer a holistic view of an organization’s security. However, it still relies on conventional endpoint detection methods.

Dependency on EDR and Network Insights

The effectiveness of XDR largely depends on the capabilities of underlying EDR systems and the integration of network monitoring. This reliance means that while XDR can offer a broader view of threats moving through a network, it still depends heavily on the detection capabilities at the endpoint level and the ability to access the network layer. This approach may fall short in environments where endpoint-centric visibility is insufficient, such as in highly distributed cloud architectures.

Differentiating Attack Vectors: Endpoints vs. Cloud Workloads

When trying to apply EDR/XDR systems to cloud environments, it is crucial to recognize that cloud attacks differ significantly from endpoint attacks.   EDR/XDR solutions focus on  addressing specific types of threats – those that commonly impact endpoints. However, the landscape of threats in cloud environments presents a different set of challenges that these systems are not inherently designed to mitigate.

Traditional Endpoint Attack Vectors

1. Malware Infections: Endpoints are often compromised through malware delivered via emails or malicious downloads from the internet. This vector relies heavily on user interaction and exploiting vulnerabilities within the endpoint’s operating system or applications.
2. Browser-Based and Phishing Attacks: These attacks exploit vulnerabilities in web browsers to execute malicious scripts, steal data, or install malware directly onto the device.
3. Physical Access: The theft or unauthorized use of physical devices provides direct access to an organization’s data and internal networks.
4. Lateral Movement: Once an endpoint is compromised, attackers often move laterally within the network, seeking to elevate privileges or access sensitive information. XDR systems detect this by observing anomalous behaviors and traffic patterns.

Cloud Workload and Service Attack Vectors

Cloud VMs, services, and workloads are fundamentally different. The main attack vectors are:

1. Application Vulnerabilities: Cloud-native applications can be exposed to a range of security vulnerabilities. These range from misconfigurations to software bugs that allow attackers to execute arbitrary code or steal credentials. These vulnerabilities require nuanced detection methods tailored to the specific environment and application architecture.
2. Supply Chain Attacks: These attacks occur when attackers inject malicious code into legitimate software packages or dependencies. Such incidents bypass traditional endpoint defenses. However, they can compromise entire systems when the affected software is deployed in a cloud environment.
3. Credential Theft and Misuse: Unlike direct malware infections, cloud environments are often compromised through the theft and misuse of credentials. Attackers might steal credentials from outside the cloud environment and use them to gain unauthorized access to cloud APIs and resources. This method does not necessarily involve compromising physical devices or endpoints directly.

These distinctions highlight a fundamental mismatch between the threat models that EDR/XDR systems are designed to address and the nature of attacks that target cloud workloads. EDR/XDR solutions excel in detecting and responding to malware and lateral movements within traditional computing and network environments. However, their capabilities do not directly translate to the cloud context. 

Cloud computing assets present a different security landscape than traditional endpoints. We don’t fear direct attacker access to the physical hardware, because loud providers handle the lower-level security. It’s highly unlikely that data center personnel would fall for phishing tactics like the infamous ‘Anna Kournikova’ email (In case you missed the reference to Friends). Thus reducing the human element of risk.

However, this shift introduces new vulnerabilities and attack methods. Cloud security requires specialized measures designed for its architecture and operational models. This raises questions about the effectiveness of standard EDR/XDR solutions. Cloud environments call for tailored tools and strategies to address their unique security challenges.

Expectations for Cloud Protection Systems

When considering protection systems designed for cloud assets, it’s important to differentiate between the security needs and approaches for Software as a Service (SaaS), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) environments. Each presents different challenges and requires different strategies to protect assets.

Protection in SaaS Environments

In SaaS setups, the security perimeter extends to the cloud service provider’s infrastructure, over which customers have no control. Consequently, protection strategies focus on monitoring and analyzing API usage, the primary interaction point with SaaS applications. Since customers have no direct visibility into the SaaS infrastructure:

• API Monitoring: The primary method to detect threats involves scrutinizing API logs to identify malicious or unusual activity. This approach depends heavily on the quality and granularity of the logs provided by the SaaS provider.
• Cloud Identities and Behavior Analysis: Protection solutions can use API logs and identity management systems to spot anomalies. These can manifest as unauthorized access or unusual patterns, and may indicate a breach in cloud services.

Protection in IaaS/PaaS Environments

For IaaS and some PaaS models, where customers control VMs, networks, and containers, more intrusive security measures—like workload-monitoring agents—can be deployed:

• Behavioral Monitoring: Agents in VMs or containers can monitor for signs of exploitation. They detect unexpected system calls or changes in application behavior. This is especially effective in Kubernetes environments since the predictable nature of containerized apps makes deviations easier to spot.
• Vulnerability Exploitation Detection: These systems are designed to detect both the attempt and the successful exploitation of vulnerabilities within the cloud infrastructure. Thus, providing an early warning and response mechanism.
• Supply Chain Attack Detection: These systems monitor workload configurations and software updates and can detect malicious changes from compromised supply chains. This is key for spotting sophisticated attacks that often bypass traditional perimeter defenses.
• Correlation of Security Signals: For modern cloud architectures that rely on microservices. security systems must aggregate and analyze data from diverse sources. This includes network traffic, system logs, and application metrics. Together, they provide a holistic view of security status and potential threats.

Protection systems for cloud assets must match the risks of SaaS, IaaS, and PaaS environments. They should use unique cloud features like APIs, identity systems, and containers. This builds a defense strategy against direct and indirect attack vectors.

Tailored strategies help organizations defend against sophisticated cloud threats. They ensure cloud environments stay secure, compliant, and resilient. This protects against disruptions and safeguards cloud-based resources.

Frequently Asked Questions: EDR/XDR and Cloud Security

What are EDR and XDR, and how do they differ from traditional antivirus?

EDR (Endpoint Detection and Response) and XDR (Extended Detection and Response) are cybersecurity systems that go beyond traditional antivirus. Antivirus relies on known malware signatures, while EDR monitors endpoint behavior in real-time for suspicious activity. XDR expands on EDR by integrating data from multiple security layers, such as network traffic, for a more holistic view.

Why are EDR/XDR solutions considered less effective in cloud environments?

EDR/XDR solutions are primarily designed to protect endpoints from threats like malware and lateral movement. Cloud environments have different attack vectors, such as application vulnerabilities, supply chain attacks, and credential theft, which EDR/XDR systems are not inherently designed to address.

What are the main attack vectors that target cloud workloads and services?

The main attack vectors include:

• Application Vulnerabilities: Exploiting bugs or misconfigurations in cloud-native applications.
• Supply Chain Attacks: Injecting malicious code into software dependencies.
• Credential Theft and Misuse: Stealing and using valid credentials to gain unauthorized access.

How do cloud attack vectors differ from traditional endpoint attack vectors?

Endpoint attacks often involve malware delivered via email or malicious downloads, browser-based exploits, and physical access to devices. Cloud attacks typically bypass the endpoint and focus on exploiting application vulnerabilities, compromising software supply chains, or stealing credentials.

Is EDR/XDR useless in the cloud?

Not entirely. EDR/XDR can still provide some value in cloud environments, particularly for protecting virtual machines that function like traditional endpoints. However, they are not sufficient as a standalone solution and should be complemented with cloud-native security measures.

What types of protection systems are more effective for cloud assets?

Effective cloud protection systems are tailored to the specific characteristics of SaaS, IaaS, and PaaS environments. They leverage cloud-native elements like API interfaces, identity and access management, and containerized deployments. They also need to consider that for SaaS environments, the customer has no control of the lower level security, and should focus on API monitoring.

What specific security measures should be implemented in IaaS/PaaS environments?

In IaaS/PaaS, consider:

• Behavioral Monitoring: Agents in VMs/containers to detect unexpected system calls or application behavior changes.
• Vulnerability Exploitation Detection: Systems to detect attempts to exploit vulnerabilities.
• Supply Chain Attack Detection: Monitoring workload configurations and software updates for malicious changes.
• Correlation of Security Signals: Aggregating and analyzing data from diverse sources (network traffic, logs, metrics).

How can organizations enhance their cloud security posture?

Organizations can enhance their cloud security by implementing tailored strategies that address the risks associated with their specific cloud environments. This includes using cloud-native security tools, focusing on API monitoring, implementing robust identity and access management, and continuously monitoring for threats.

What is API monitoring, and why is it important in SaaS environments?

API (Application Programming Interface) monitoring involves scrutinizing API logs to identify malicious or unusual activity. It’s crucial in SaaS environments because the API is the primary interaction point between the customer and the SaaS application.

How do tailored cloud security strategies ensure compliance and resilience?

Tailored strategies address the specific compliance requirements and potential disruptions associated with cloud environments. By focusing on these unique aspects, organizations can minimize risks and ensure their cloud environments remain secure, compliant, and resilient.