The Shared Responsibility Model in Cloud Security: Who Owns What?

The fragmented nature of responsibilities in cloud security — shaped by the specific cloud service model — means CSPs may secure infrastructure, operating systems, or platforms, while customers are responsible for protecting their data, applications, and configurations. However, nuanced differences and enforcing policies across clouds often throw a wrench into this otherwise straightforward division of responsibilities. Misalignments of these boundaries often result in visibility gaps, misconfigurations, and compliance risks. In this article, we will examine the nuances of the Shared Responsibility Model and its implications.

Cloud Security Evolution and Shared Responsibility

The Shared Responsibility Model in cloud security defines the division of security ownership between cloud service providers (CSPs) and their customers. By transferring certain security obligations — such as physical infrastructure protection — to CSPs, the model allows businesses to focus on securing their applications, data, and configurations. However, that division of responsibilities also creates new complexities that need careful management to avoid security gaps. 

Here’s a real-world example:

In AWS, the shared responsibility model clearly states that AWS is responsible for securing the physical servers, network, and hypervisor. Customers are responsible for securing their S3 buckets, including configuring proper access controls. For example, if an S3 bucket is mistakenly left open to the public, that misconfiguration is the customer’s responsibility.

Compare this to Google Cloud, which offers more built-in controls for its Cloud Storage equivalent. Google Cloud provides features like default bucket-level access prevention and organization policies that can help enforce stricter access configurations across the board, reducing the likelihood of such misconfigurations.

In the Google cloud, if customers disable these features or misconfigure IAM roles, they will bear the responsibility for resulting vulnerabilities.

Where Did the Shared Responsibility Model Come From? 

The Shared Responsibility Model emerged alongside the rapid adoption of cloud computing, pioneered by early cloud providers like Amazon Web Services (AWS) to clarify security roles. 

Multi-cloud is the norm, and its use goes beyond large CSPs. Across industries, the average organization uses more than 10 clouds across their workflows.

Unlike traditional on-premises environments — where organizations owned the entire stack from physical infrastructure to applications — the cloud introduced a new paradigm where infrastructure responsibilities shifted to CSPs and companies were left to trust all those providers with large portions of their infrastructure.

The shift allowed businesses to scale faster and reduce operational overhead, but it also created the need for clear boundaries on risk ownership. 

For the first time, organizations were using servers in physical spaces they couldn’t access. Moreover, they were trusting providers to keep those servers, and their customers’ private data, safe.

The transition redefined security, calling for companies to adapt to an environment where vulnerabilities are often introduced through mismanagement on the part of the customer, such as overly permissive IAM policies or misconfigured storage buckets. 

Still, delegating infrastructure security to CSPs didn’t absolve customers of their role in protecting data and workloads. Misunderstanding or neglecting these boundaries can lead to costly security incidents, compliance violations, and operational disruptions.

The model also reflects the evolving complexity of modern cloud environments. Today’s businesses rely on hybrid and multi-cloud architectures, which make consistent enforcement of security practices across providers a significant challenge. As a result, organizations must approach cloud security not as a passive benefit of using a CSP but as an active responsibility that requires the right tools, policies, and processes to effectively reduce risk.

Breaking Down Cloud Provider vs Customer Responsibilities

The model is a quite nuanced framework that shifts depending on the provider, the service model, and how organizations use the cloud. 

Understanding its boundaries is critical for identifying security gaps and aligning internal efforts with the provider’s capabilities. 

A clear breakdown of responsibilities enables organizations to focus their resources effectively, reduce risk, and improve their overall cloud security posture. So what does a typical division of responsibility look like? 

Security Aspect	Cloud provider Responsibilities	Customer Responsibilities
Infrastructure Security Ownership	Secures physical data centers, networking, hardware, and virtualization layers, ensuring availability and redundancy.	Manages the security of operating systems, virtual machines, and workloads running on the provider’s infrastructure.
Application Layer Responsibilities	May provide tools or platforms for application hosting (e.g., PaaS), but does not directly secure customer applications.	Develops, configures, and maintains secure application code, dependencies, and configurations.
Data Protection Requirements	Provides encryption options for data at rest and in transit, and may offer data redundancy and backup tools.	Ensures data classification, applies encryption where required, and manages secure access to sensitive data.
Access Management Duties	Offers identity and access management (IAM) frameworks and role-based access controls for CSP-native services.	Configures IAM policies, enforces least privilege principles, and monitors the activities of users, APIs, and machine identities.
Compliance Obligations	Ensures compliance for the underlying infrastructure (e.g., SOC 2, ISO 27001 certifications).	Demonstrates compliance for customer-owned data, workloads, and configurations, aligning with regulatory requirements.

Are there Provider-Specific Responsibility Models?

Understanding the Shared Responsibility Model is only the first step; implementing it effectively requires recognizing how different providers define and support these responsibilities. Let’s examine how the three major cloud providers — AWS, Azure, and GCP — interpret and operationalize this model.

AWS Implementation

AWS emphasizes a clear distinction between responsibilities: it secures the physical infrastructure, networking, and hypervisors, while customers manage their workloads, operating systems, and configurations. AWS tools like CloudTrail, Config, and IAM help customers monitor and secure their environments but require proper configuration to avoid gaps.

Azure Approach

Azure’s shared responsibility model extends its control over services like identity through Azure AD while expecting customers to manage application-layer security, data protection, and access policies. Azure’s Security Center and Sentinel provide monitoring, but customers must align these tools with their own operational models for maximum effectiveness.

GCP Framework

GCP outlines its responsibilities for the infrastructure and platform, while customers remain accountable for data, workloads, and access control. GCP’s tools, such as Cloud Armor for WAF and IAM Recommender, help optimize customer permissions but require expertise to ensure compliance and security alignment.

Model Differences

While all providers follow the shared responsibility model, the responsibilities they retain and offer customers, as well as the tools available to manage customer responsibilities, vary. AWS provides granular tools for resource-level monitoring. Azure emphasizes integration across its ecosystem. GCP focuses on minimizing customer effort with AI-driven recommendations. 

These differences can complicate a multi-cloud strategy since organizations will need to account for where their workloads run to address the security gaps of those workloads.

Integration Considerations

In multi-cloud or hybrid setups, ensuring consistency across responsibility models is a major challenge. Misaligned configurations, fragmented logs, and varying security toolsets can lead to visibility gaps. Organizations need centralized platforms to unify security efforts, correlate data, and maintain control across providers.

Service Model Impact on Security Responsibilities

While understanding the division of security responsibilities between cloud providers and customers is foundational, the cloud service model an organization adopts — whether Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), or Software-as-a-Service (SaaS) — introduces yet more nuances. 

Why? That’s because, in addition to different rules and offerings across clouds, there are also slightly different rules for who manages what across service models. 

For businesses operating across multi-cloud or hybrid environments, these differences get complicated quickly. Is an entire environment compliant with company, industry, and international regulations? Across clouds and service models? All the moving parts can make it difficult to tell. 

Here’s what’s important to know across service types:

IaaS Security Boundaries

In an IaaS model, the provider secures the physical infrastructure, including servers, storage, networking, and the virtualization layer. Customers retain control — and responsibility — for everything running on top, such as operating systems, middleware, applications, data, and network configurations.

This extensive control gives customers flexibility, but without the necessary resources to remain vigilant, it also increases their exposure to risks like misconfigured security groups, unpatched operating systems, or overly permissive IAM policies. For example, leaving a storage bucket publicly accessible or failing to update an operating system could result in serious breaches that are entirely within the customer’s control.

PaaS Protection Requirements

With PaaS, providers extend their responsibilities to include securing the runtime, middleware, and underlying operating systems. While this reduces the customer’s operational burden, they still remain responsible for their applications, data, and configurations, including API security and access controls.

This shift simplifies infrastructure management but requires vigilance at the application and data layers. For example, customers deploying workloads on Kubernetes must ensure proper API security and enforce container-level isolation to protect against vulnerabilities. Neglecting these aspects leaves applications and data exposed, despite the provider’s robust runtime protections.

SaaS Security Considerations

In SaaS environments, the provider manages nearly all security aspects, including infrastructure, application functionality, and data processing. Customers, however, remain accountable for how they use the service, including configuring access controls, managing user permissions, and protecting sensitive data uploaded to the platform.

For example, failing to enforce multi-factor authentication (MFA) or improperly managing shared credentials can create entry points for attackers. In SaaS, the customer’s role is more focused on governance — ensuring secure usage practices and compliance with internal and external security policies — than on managing underlying infrastructure or app security controls.

Critical Security Gaps in Shared Responsibility

The Shared Responsibility Model defines security ownership, but in practice, it sometimes leads to blind spots that can leave organizations vulnerable. Misunderstandings of responsibilities, overlooked security areas, and the inherent complexity of cloud environments can create openings for savvy hackers to exploit. 

Teams who nail down their approach to different clouds, then different service models will then confirm their success by working through this checklist of gaps, making sure their cloud workloads can’t fall through.

Common Misunderstandings

A recurring challenge is the assumption that the cloud provider is responsible for more than they actually are. This often stems from ambiguous or incomplete communication about where provider responsibilities end. Some customers who don’t understand these complexities, like smaller businesses, might fail to configure basic security features, such as encryption or firewall rules.

Another layer of complexity arises in multi-cloud setups, where the shared responsibility boundaries differ slightly between providers. For example, AWS, Azure, and Google Cloud may offer similar logging features, but their capabilities and customer responsibilities vary, leading to gaps in implementation. This inconsistency might result in incomplete security coverage in one or more cloud environments.

Overlooked Responsibilities

Some security responsibilities are overlooked simply because they operate outside traditional paradigms. Ephemeral resources such as containers, serverless functions, and auto-scaling instances are prime examples. These transient workloads leave a minimal footprint, and without real-time monitoring or proper logging, critical evidence of attacker activity can be missed entirely.

Another commonly overlooked area is identity management. Service accounts and machine identities often proliferate unchecked, leading to excessive permissions or dormant accounts that become easy targets for attackers. The technical challenge lies in mapping and securing these identities, especially in environments with thousands of interdependencies.

Integration Challenges

Many organizations rely on multiple tools and platforms for cloud security, each addressing a specific layer like identity management, network traffic analysis, or compliance monitoring. However, these tools can operate in silos, making it difficult to achieve a unified view of an incident or threat.

For example, a cloud-native web application might generate logs from its firewall, API gateway, and application server. Without integration, connecting these disparate data sources into a coherent narrative demands significant manual effort, which can delay incident response and increase the likelihood of oversight.

Visibility Issues

It’s already a technical hurdle to maintain good visibility in distributed and dynamic cloud environments. In multi-cloud environments, the problem only worsens. 

For instance, one provider might offer detailed logs of network flows, while another might lack granularity, which makes it difficult to correlate data across environments. Attackers exploit these blind spots and move laterally between systems that lack end-to-end oversight. 

Compliance Confusion

The division of responsibilities complicates compliance requirements, especially when regulations call for evidence of specific security controls. CSPs may offer encryption for data at rest, but customers are typically responsible for key management and audit log reviews. Misunderstanding these nuances can lead to non-compliance and fines, even when a provider meets its obligations.

The confusion becomes more acute in hybrid and multi-cloud environments, where different regions might fall under varying regulatory jurisdictions. Tracking compliance across multiple frameworks — like GDPR in Europe and CCPA in California — requires consistent visibility and governance.

The Shared Responsibility Model is not inherently flawed, but it assumes organizations have the tools, expertise, and processes to fully manage their share of the responsibility. The reality is that visibility gaps, siloed tools, and overlooked areas introduce risks that require a strategic, technically robust approach to overcome.

Implementing Effective Shared Security

In a world of multiple rules and a panoply of gaps to leap, organizations need a step-by-step guide to implementing their own security in the context of the Shared Responsibility Model. And it’s important to note: a well-executed security strategy not only mitigates risks but also aligns security practices with the speed and scalability of modern cloud infrastructures. The Cloud Security Alliance says, effective use of the model “helps you design controls and identify areas to save time and resources.” But how? With so many considerations, it’s easier said than done. 

Let’s work through a checklist to help account for security in the context of truly understanding the Shared Responsibility Model and knowing where so many teams hit speed bumps: 

1. Develop a Strategy that includes Clouds, Service Models, and Organizational Compliance Requirements

The foundation of effective shared security lies in the creation of a clear, actionable strategy tailored to the organization’s cloud architecture and service models. This strategy must account for variations in responsibilities between IaaS, PaaS, and SaaS, as well as the unique requirements of multi-cloud and hybrid environments.

Key considerations include:

• Identifying the organization’s security ownership for each service model and aligning them with internal capabilities.
• Prioritizing high-impact areas like identity management, data protection, and API security — all common attack vectors in cloud environments.
• Ensuring the strategy is dynamic, adaptable to evolving workloads, and integrated with broader risk management objectives.

2. Select Tools that Address Security Gaps

Comprehensive tools? Native cloud solutions? The effectiveness of shared security heavily depends on selecting the right tools. While working on a cloud-by-cloud basis can be a good foundation, and a long-term solution for organizations with a single-cloud presence, ultimately, most organizations want to look to tools that integrate seamlessly across cloud providers and offer centralized visibility, automation, and real-time insights for all their workloads. 

Modern shared security tools should include:

• Identity and Access Management (IAM) tools for monitoring permissions and detecting privilege escalation.
• CSP-native tools like AWS CloudTrail or Azure Monitor, supplemented with third-party platforms for cross-cloud log aggregation.
• Cloud-native platforms that offer CSPM and runtime protection, ensuring misconfigurations are detected, and workloads are monitored continuously.

Tool selection should align with the organization’s maturity level, ensuring scalability for growing workloads while addressing immediate gaps. Comprehensive CNAPPs can combine these capabilities, which comes with the advantage of overarching visibility as well as consistent policy enforcement no matter where workloads are running.

3. Define Team Responsibilities

Ambiguity about team roles and responsibilities in the cloud often leads to missed vulnerabilities or inefficient processes.

Key actions include:

• Assigning ownership for key areas, such as API security, IAM configurations, and compliance reporting.
• Establishing collaboration frameworks between security, DevOps, and cloud teams to ensure security is embedded across the development lifecycle.
• Training teams on the nuances of cloud security, particularly the specific responsibilities associated with different CSPs and service models.

4. Automate Processes

Manually managing security in cloud environments is untenable due to the scale, speed, and complexity of operations. Automation is essential for monitoring, detecting, and remediating security risks in real time.

Useful automation opportunities include:

• Automatically detecting and removing excessive permissions.
• Identifying issues like exposed storage buckets or overly permissive security group rules and resolving them without human intervention.
• Using tools that automatically isolate compromised resources or revoke unauthorized access during an attack.

5. Validate Continuously

Shared security is not a static framework — it requires ongoing validation to ensure controls remain effective as environments change. This involves regularly testing configurations, monitoring for anomalies, and validating compliance requirements.

Key practices include:

• Conducting regular security assessments to identify gaps introduced by new deployments or updates.
• Using threat simulation tools to validate incident detection and response workflows.
• Implementing continuous compliance monitoring to track alignment with regulatory frameworks like SOC 2 or GDPR.

Effective shared security isn’t just about avoiding risks; it’s about building a scalable, resilient foundation that supports security no matter where workloads live, and regardless of how much they scale over time. 

Enhancing Cloud Security with Upwind

The Shared Responsibility Model seems simple on the surface and clearly benefits organizations by enabling effortless scalability and facilitating innovation. Keep the benefits, while managing challenges with comprehensive visibility across multi-cloud and hybrid environments, automated security controls, continuous monitoring, and runtime protection for ephemeral workloads. 

Coupled with integrated compliance features, the platform simplifies evidence collection and reporting for frameworks like SOC 2 and GDPR, Upwind helps customers meet regulatory requirements while maintaining a strong security posture. Get your Upwind demo here. 

Frequently Asked Questions

How does DevOps impact the shared responsibility model?

In a DevOps culture, security becomes a shared responsibility across teams. With CSPs functioning similarly, workflows can blur the lines for all, as security is shared across more groups, with more opportunities for misalignment and miscommunication.

Further, continuous deployment pipelines and ephemeral resources like containers require customers to manage security configurations, monitor runtime environments, and validate policies more frequently. These dynamic workflows increase the pace of potential misconfigurations, such as overly permissive IAM roles or exposed APIs, which can be exploited if not continuously monitored and remediated. 

This integration of development and operations expands the customer’s role in securing cloud environments while still relying on providers for infrastructure-level security. 

It also demands stronger collaboration between security and DevOps teams to ensure that automated pipelines include built-in checks for compliance, configuration standards, and vulnerability management so security is embedded within the development lifecycle.

Overall, the shift to multi-cloud environments, often driven by DevOps, increases the complexity of maintaining consistent security practices across providers. That reality has spurred the need for centralized tools that not only account for each CSP’s shared responsibility model but also bring together monitoring, enforcement, and incident response across cloud platforms. 

What security aspects are always customer responsibilities?

Customers are always responsible for securing:

• Their data. They must classify, encrypt, and control access to data.
• Their applications, including the managing of access controls, configuring security policies, and monitoring workloads for vulnerabilities or anomalies. However, in SaaS, customers typically don’t manage the underlying application, but remain responsible for how they use the service, like managing user permissions and configuring access controls.

While data security and application-level controls are generally always the customer’s responsibility, the extent depends on the service model.

How do compliance requirements affect shared responsibilities?

Compliance requirements like SOC 2 or GDPR extend shared responsibilities by making customers accountable for implementing and documenting controls over their data, workloads, and configurations. 

While CSPs handle infrastructure compliance, customers must align their cloud usage with regulatory standards, such as encrypting sensitive data, managing access controls, and maintaining audit logs, and they’ll need to prove it, though they don’t directly control the cloud servers they use. Therefore, compliance also requires collaboration with CSPs to ensure visibility into shared environments and evidence collection for audits.

What tools help manage shared security responsibilities?

Cloud-native tools are effective, and include solutions like AWS CloudTrail, Azure Security Center, and GCP Operations Suite for visibility. They are limited to the clouds they serve, which means they’ll leave security gaps and create extra management tasks for most teams, who work across multiple cloud environments simultaneously.

Comprehensive tools like third-party platforms offer CSPM (Cloud Security Posture Management), workload protection, and runtime monitoring to detect and remediate issues across multi-cloud environments. Those capabilities can be combined (as in a CNAPP) or deployed individually, depending on use case. They’ll bring together multiple clouds under one dashboard, for a more logical workflow and a more complete view of resources.

How does containerization change the shared responsibility model?

Containerization significantly alters the Shared Responsibility Model by adding new layers of complexity and responsibility for customers, while CSPs maintain their foundational duties around infrastructure security. 

Here’s how: 

• Ephemeral Resources: Containers are short-lived and dynamically scaled, so security measures must adapt to their transient nature. Customers must make sure that security controls, such as image scanning and runtime monitoring, are automated and continuous so they keep up with these fast-changing environments.
• Securing Images: Customers are responsible for the integrity and security of container images, so they’ll need to adapt their workflows to ensure they’re using trusted registries, scanning images for vulnerabilities before deployment, and updating images to address security flaws.
• Orchestration management: With tools like Kubernetes, the customer must configure and secure the orchestration layer, like role-based access controls (RBAC), network policies, etc. 
• Monitoring runtime activities: Runtime protection is critical since misconfigured containers, excessive permissions, or exploited vulnerabilities can lead to breaches. Customers must detect and respond to anomalies, and enforce policies on their containers.
• Managing APIs: Containers often rely on APIs for communication, which increases the attack surface. Customers need to handle authentication mechanisms, rate limiting, etc.
• Shared Tools: If they use third-party tools to unify their clouds, customers will need to integrate them with their new platform.