Most organizations already have some level of cloud infrastructure services (IaaS, PaaS, FaaS, or serverless) and as more workloads migrate to, and are built on, the cloud, the top cloud security concern for any organization is a data breach. To underscore this point, breaches uncovered in March 2019 alone include the exposure of thousands of doctors’ notes by Meditab, 1.5 million customer records by Gearbest, 2.4 million client records from Dow Jones, and 809 million customer records by Verifications.io.
All of the above breaches were due to misconfigurations and mistakes made by the Cloud Service Provider (CSP) customer, not due to vulnerabilities or failures in the underlying CSP service. It drives the question — are current approaches to managing cloud security controls sufficient to prevent a breach? Put another way, what do organizations need to do to augment or boost their current cloud security approach to better manage breach risk at an acceptable level in the cloud?
Leveraging CSP security controls is essential, and, for some cloud implementations, is sufficient to manage public cloud workload risk. For most enterprises, however, these controls alone are not adequate to address the core aspects of cloud security: audit, visibility, protection, detection, and automation. As discussed in this report, aligning cloud complexity with organizational risk appetite is key to determining when and how to augment CSP security controls.
Breaches of data in the cloud are on the rise, not breaches of the underlying cloud provider’s infrastructure. This distinction between CSP and customer is vital since with cloud providers there is an explicit shared responsibility relationship. The cloud provider is responsible – and typically successful in – securing the underlying components of cloud services. The customer is responsible for securing how they use the cloud services, including properly configuring identity and access management (IAM), storage and compute settings, threat analysis and defense, and the security of the application and data processed and stored on the cloud.
If the underlying cloud infrastructure is secure, then responsibility for cloud breach must lie with the cloud customer. As Gartner states, “through 2022, at least 95 percent of cloud security failures will be the customer’s fault.”
The If cloud breaches are typically due to misconfigurations, then organizations must implement controls that quickly – and automatically – prevent or detect and remediate these errors. To this end, CSPs offer a plethora of security controls. For example, Amazon AWS provides more than 30 different cloud-security related services (e.g., GuardDuty, CloudTrail, CloudHSM, CloudWatch, etc.), including the recent beta release of AWS Secu- rity Hub. These controls are essential, playing a primary role in secure cloud configura- tions, though just turning them on does not guarantee secure cloud configurations.
Secure cloud configuration must be a dynamic and continuous process. At a base level, there is the configuration of the cloud infrastructure (e.g., blocking SSH ports, and IAM). Next, there is the configuration of the CSP security controls (e.g., enabling log monitoring and encryption). And, finally, SecOps teams must address changes to settings (e.g., detect- ing and acting on a threat actor turning off logging to cover their tracks).
So, what controls detect and prevent misconfigurations? To answer this question, we align CSP controls against core aspects of cloud security: Audit, Visibility, Protection, and Detection. These core aspects build on the NIST Cybersecurity Framework (NIST CSF). To augment the NIST CSF and better align it to cloud security, we include automation as a core aspect. Automation is so central to cloud operations that there are a series of con- trols necessary to monitor, track, and enforce automation functions
The Table 1 lists the CSP security controls available from the three major CSPs: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). These tools are necessary to manage and protect cloud workloads because, often, particularly for detective controls, these tools can provide visibility and control at a level not possible with external tools. For example, AWS GuardDuty leverages DNS logs, which aren’t made public to external security services. These detective tools enable users to derive insights from attack patterns and techniques so they can act more quickly. In the case of AWS, using services like Inspector for vulnerability scanning, or GuardDuty for network intrusion, or Macie for anomalous behavior detection improves the overall security response.
|Log Management||CloudTrail||Log Analytics||Stackdriver|
|Compliance||CloudHSM||Azure Trust Center and Key Vault||GCP Security|
|Service Catalog||Service Catalog||Managed Applications||Service Catalog|
|SIEM||CloudWatch||Azure Portal and Azure Monitor||Stackdriver Monitoring/Logging|
|Config Assessment||Trusted Advisor||Azure Advisor|
|MFA||Multi-Factor Auth||Azure MFA||Cloud Identity Aware Proxy|
|Web App FW||WAF||Application Gateway|
|IAM||AWS Identity & Access Management Cognito||Azure AD/IAM||Cloud Identity and Access Management|
|Key Management||KMS||Azure Key Vault||Cloud KMS|
|DLP||Macle||Azure OMS, Security Center||Cloud DLP|
|Anomaly Detection||GuardDuty||Stream Analytics||Cloud Dataflow|
|Vulnerability Scan||Inspector||Security Center||Scanner|
|Operational Insights||Systems Manager||Monitor||Stackdriver Monitoring|
|CI/CO||CodePipeline, OpsWorks CodeBuild CodeDeploy||Azure AutomationAzure Scheduler||GCP Deployment Manager|
|Provisioning templates||CloudFormation||Azure Resource Manager||Cloud Deployment Manager|
|Service Catalog||AWS Service Catalog||Azure Managed Applications||Google Cloud Platform Service Broker|
|Security Assessment||Inspector||Security Center Resource Security Hygiene||Cloud Security Command Center|
|Serverless Code||Lambda||Azure Functions||Cloud Functions|
|Account Management||Organizations||Azure Subscription and Service Management||GCP Resource MAnager|
Most organizations already have some level of cloud infrastructure services (IaaS, PaaS, FaaS, or serverless) and as more workloads migrate to, and are built on, the cloud, the top cloud security concern for any organization is a data breach. To underscore this point, breaches uncovered in March 201 Please subscribe to read the rest.
CSP security controls address audit, visibility, protection, detection, and automation requirements to a point. There is an inverse relationship between the effectiveness of these controls and the complexity of the cloud environment. To illustrate, AWS CloudTrail does an excellent job as an audit control, recording events (e.g., API calls, AWS SDKs, command line tools, AWS Management console, and other AWS services). Of course, CloudTrail is only useful when turned on and – not surprisingly – an attacker’s first move is often disabling CloudTrail. Blocking this threat requires detective controls to identify when CloudTrail is turned off, preventive controls to prevent services from starting with- out CloudTrail enabled, and reactive controls to restart CloudTrail in the event of miscon- figuration or malicious action.
To accomplish these tasks natively on AWS requires the following steps (and similar steps in multi-cloud scenarios across multiple cloud providers using their specific approaches):
Yes, this is only four steps, but consider that logging is just one of the hundreds of require- ments for ongoing cloud security and the complexity of managing this at scale across multiple clouds. To provide some perspective, this requirement equates to the Center for Internet Security (CIS) requirement 6.2 “Activate audit logging.” There are seven CIS audit logging requirements to be set, validated, and re-checked regularly in AWS.
Seven requirements are still not an excessive demand on a SecOps team but add in a GCP workload, and the number doubles. Deploy workloads across all three clouds and the requirements more than triple. And, this is just the underlying configuration, not the additional AWS Lambdas, Azure functions, and GCP cloud functions necessary to detect log setting changes and the resulting reset actions. Considering that this is only one of nearly 200 CIS recommendations, implementing these recommendations, particularly across a multi-cloud environment, becomes a considerable task.
Automation of cloud services is a double-edged sword. On the one hand, automation drives better security by automating security controls with dramatic, tangible benefits. Automating security can reduce the incidence of a breach and, according to the 2018 Ponemon report, businesses that have security automation reduce the cost of a breach by 35%. The flip side of the automation sword is the misconfiguration of controls where automating cloud provisioning can act as a force multiplier. In other words, things can go very well or very poorly, very quickly, due to automation. For example, provisioning of serverless computing (e.g., AWS Lambda) without proper automation of dynamic and static code testing could result in vulnerable code launching into production quickly and quietly.
Sure, it is possible to write 100’s of scripts using cloud-native tools to enforce CIS bench- marks and detect and respond to changes to manage cloud risk. However, not only is this a brittle and unsustainable strategy, as complexity increases, relying entirely on CSP tool- sets becomes unmanageable for the following reasons:
Going back to Gartner’s projection about cloud security failures being due to human error, as the complexity of the environment increases, so too does the opportunity for error. As shown in figure 1, the relationship between CSP security controls, cloud complexity, and risk is not a simple straight-line equation. As complexity increases, so too does risk, but your organization may be at very high risk even in a basic cloud environment.
At point A, organizations deploying cloud workloads without implementing CSP security controls are assuming a level of risk way above the corporate risk appetite. One open SSH port or one weak AWS Console password is all it takes to give adversaries a natural entry point.
Point B is the sweet spot for CSP security controls. For an organization with minimal public cloud complexity (i.e., number of workloads, clouds, zones, etc.) proper and diligent implementation of CSP security controls is necessary and sufficient to bring cloud risk below the corporate risk appetite level and on-par with on-premises IT workload risk. The CSPs will argue that their intrinsic security posture makes it possible for lower risk in the cloud than on-premises for organizations at this level of cloud complexity.
As complexity increases (point C), the CSP controls remain essential but rapidly become insufficient to maintain risk. The challenges of managing controls across diverse cloud environments with different approaches, capabilities, UIs, and architectures make it impractical and unsustainable to rely on CSP controls alone. Even those organizations that are single-cloud today can quickly become multi-cloud due to business requirements, developer preference, or M&A activity. The goal of enterprise security should be to adopt a cloud security approach that enables and supports rapid business shifts and is forward-looking. This security approach accelerates corporate innovation and profitability.
If your organization is further to the right on the chart, the ideal way to normalize cloud risk is augmenting CSP security controls with a unifying security control layer. This unify- ing security control layer facilitates the right balance of audit, visibility, protection, detec- tion, and automation as a basis for managing risk in the cloud. For example, audit is only as effective as visibility since one can only record what one sees. Similarly, organizations must balance protection and detection controls. Both are essential to blocking a breach. However, heavy-handed protective controls can drive up IT friction by putting limits on developers. For example, instituting rules that prevent all SSH and RDP ports (blocking test and development access) versus a more nuanced rule set that prevents RDP/SSH in a specific context, for example in production only.
DivvyCloud provides a unification layer to work in concert with the underlying CSP secu- rity controls. By leveraging a resource model they delivers universal monitoring and controls across clouds including AWS, Azure, GCP, Alibaba Cloud, and Kubernetes. Divvy- Cloud monitors and remediates cloud and container misconfigurations and policy viola- tions. Allowing customers to achieve continuous security and compliance and realize the benefits of cloud and containers.
DivvyCloud sits inside the virtual private cloud, providing the visibility, governance, and trust necessary to address cloud security.
As shown in Figure 2, adding a solution like DivvyCloud facilitates keeping cloud risk below the enterprise risk appetite. By balancing and augmenting the audit, visibility, protection, detection, and automation aspects of CSP controls, DivvyCloud improves cloud security by:
Breaches of cloud data are on the rise, and the primary cause is a misconfiguration of cloud workloads (including serverless workloads) and the CSP user interfaces to manage the workloads. The good news is CSPs provide a wide range of comprehensive security tools to help manage the audit, visibility, protection, detection, and automation of these workloads. The not so good news is achieving the right balance of cloud security is increasingly difficult as the complexity rises. For simple cloud implementations – with proper setting of security controls – CSP tools are sufficient to manage enterprise risk in the cloud. For more complex deployments, CloudOps or SecOps teams require a unifying security control layer to balance and boost the audit, visibility, protection, detection, and automation aspects of CSP controls to manage enterprise risk in the cloud.