This comprehensive guide covers everything related to securing cloud native infrastructures. We‘ll understand key concepts, evolution, best practices, vulnerabilities and mitigation strategies.
Overview
With this 2800+ word guide, you will learn:
- What is cloud native security: Definition, goals, benefits
- How it evolved: Brief history, key technology drivers
- Core components: Perimeterless models, microsegmentation, DevSecOps etc.
- Best practices: Supply chain security, access management etc.
- Common threats: Misconfigurations, software vulnerabilities etc.
- Managing risks: Policy automation, runtime security, access controls
So if you are looking to secure containerized applications across hybrid/multi-cloud environments, you are in the right place.
What is Cloud Native Security?
Cloud native security refers to the processes, tools and techniques used to protect applications, data, infrastructure and workflows hosted in distributed, ephemeral cloud environments.
It focuses on securing the full lifecycle of cloud native workloads by addressing unique risks introduced by orchestration platforms like Kubernetes or serverless runtimes leveraging functions-as-a-service architectures.
As per research firm Gartner,
More than 85% of global organizations will be running containerized applications in production by 2025.
But this also means 85% of organizations can expect to suffer a container or Kubernetes related security breach if they do not implement adequate safeguards proactively.
Some key goals and principles of cloud native security include:
- Embedding security across the workflow from code to production
- Isolating and authenticating individual workloads in perimeterless environments
- Automating policy enforcement and compliance checks
- Detecting threats and anomalies in ephemeral architectures
- Facilitating secure and rapid iterations through DevSecOps
Compared to traditional cloud security models designed for monolithic applications, cloud native security is tailored for rapid iteration, decentralized governance and automation across ephemeral workloads.
It provides multiple layers of defense including:
- Hardening deployed workloads
- Detecting suspicious user activity
- Protecting volatile secrets and keys
- Preventing attacks on third party dependencies
Thereby addressing key threats like compromised containers, misconfigured platforms, and insider attacks.
The Evolution of Cloud Native Security
The need for cloud native security became evident as organizations began encountering security gaps while transitioning monoliths to containerized microservices in late 2010s.
Several key developments have shaped evolution of modern security controls:
2015 – 2016
- Docker cements itself as de facto OCI compliant container format with widespread support across clouds
- Kubernetes emerges as leading container orchestrator promising greater portability
- Concept of "Infrastructure as code" gains wider acceptance enabling automation
2017-2018
- High profile breaches highlight gaps in default Kubernetes security models
- CNCF launches efforts to define policy standards for cluster governance and access controls
- DevSecOps practices start focusing on image scanning and embedding security in CI/CD pipelines
2019-2020
- Growth of service meshes like Istio allow microservices security within production environments
- Falco established as defacto Kubernetes threat detection engine using behavioral monitoring
- Techniques like Binary Authorization, SPIFFE and Cilium Network Security mature to address identified gaps
2021 and beyond
- Ransomware groups increasingly target container orchestrators to maximize damage
- Supply chain attacks emerge allowing malware injection into legitimate container images
- Security tools adapt to ephemeral serverless architectures built on functions as a service
In essence, Cloud Native Security has rapidly evolved protection, detection and response capabilities to match the scale, distribution and dynamism of modern infrastructures.
But this space continues to be an arms race against increasingly sophisticated attackers.
Core Components of a Cloud Native Security Model
Let us breakdown key elements that make up a robust cloud native security framework:
Perimeterless and identity-based security
Traditional notions of network perimeters dissolve with cloud native apps distributed across regions, clouds and edges. To restrict access, security controls are directly tied to individual workload identity like virtual machine attributes or pod labels.
Multi-factor authentication, ephemeral certificates and mechanisms like the SPIFFE standard further strengthen identity assurance across decoupled microservices.
Microsegmentation
Workloads are isolated from each other and restricted from accessing underlying infrastructure through microsegmentation tools like network policies. This limits lateral movement in case of intrusions.
For example, a compromised container cannot access storage volumes associated with other workloads.
Encryption
Protecting data at transit and rest is critical given increased mobility. This is achieved through industry standard transport layer encryption between microservices and dedicating key management to secure secrets.
Continuous compliance monitoring
The ephemeral nature of cloud native resources means compliance posture against regulatory standards has to be continuously monitored instead of periodic audits.
Tools can automatically validate controls like encryption, access restrictions etc. are correctly implemented across namespace, clusters etc. Non compliant workloads can be immediately quarantined before issues compound.
DevSecOps principles
By embedding security practices across the workflow including image scanning, fuzz testing before rollout and policy compliance checks post deployment, vulnerabilities can be eliminated early preventing downstream costs.
This “shift left” culture allows threats to be localized and addressed where introduced instead of materializing subtly before detection.
Automated policy enforcement
With infrastructure as code and policy as code, security baselines can be enforced by default instead of “bolting on” later.
Tools like Kyverno and Open Policy Agent (OPA) allow guards to be implemented ensuring all deployed resources comply with organization standards and industry benchmarks.
Logging and monitoring
Centralized logging sinkholed from various components in the stack and then correlated using analytics tools provide single pane of glass visibility.
Modern SIEM solutions focused on cloud native threats help accelerate detection and response.
Together these provide a layered defense-in-depth approach tailored for cloud native environments – integrating with CI/CD pipelines on one end and bridging production platforms at the other end – closing gaps and facilitating secure innovation at velocity.
Best Practices for Cloud Native Security
Let us look at top recommendations from leading analysts to minimize risks:
Secure your software supply chain
Attackers often inject malicious code by compromising legitimate third party container images downloaded from public registries.
So maintaining central control over all images, libraries and dependencies used across environments by establishing private registries is strongly advised. Automated scanning of images for known vulnerabilities using Binary Authorization servers before rollout also eliminates bad builds before they enter pipelines.
Enforce least privilege access
Standing privileges allowing workloads excessive permissions should be avoided. Instead access should be granted temporarily only when required through Just in Time (JIT) elevation mechanisms monitored by Privileged Access Management (PAM) solutions.
Immutable infrastructure constructs prevent changes or additions post deployment closing common misconfiguration avenues.
File system access should ideally be read only with layered writable volumes only if essential.
Detect insider threats early
Given the extent of access developers and DevOps engineers possess in cloud native environments, monitoring user activity for anomalies indicative of insider threats helps counter credential theft and malicious actions.
Analyzing SSH sessions, endpoint activity combined with object access logs from various platform components provides holistic coverage.
Focus on cloud native visibility
Threat detection models designed for monoliths struggle to interpret interdependencies in microservices architectures. So analytics tuned to understand APIs between workloads, serverless functions, stateful changes etc. are necessary for identifying sophisticated attacks.
Purpose built SIEM solutions that incorporate runtime sources beyond just network flows are imperative for cloud native visibility.
Common Threats and Vulnerabilities in Cloud Native
Despite additional controls in place, cloud native environments continue to be plagued by security incidents.
Below we discuss observe issues:
Misconfigurations exposing systems
Kubernetes complexity coupled with pressure to maintain configuration parity across multiple clusters multiplies risks of missteps. Small oversights leave grave impacts:
- Accidentally exposing dashboards to Internet leading to cryptojacking outbreaks
- Errors granting IAM roles overly permissive access to cloud resources
- Insecure default settings for network policies granting unnecessary comm channels between microservices
- Committing secrets to source code repositories later scrapped by attackers
Such incidents contributed to over 200 million records being compromised through misconfigured cloud databases and storage instances as per data from Tenable Research.
Software supply chain compromise
The ubiquity of container images in CI/CD pipelines has turned dependencies into prime targets:
- Typosquatting attempts where tampered images are uploaded to registries with names close to popular packages
- Dependency confusion issues allowing substituted malicious versions to be pulled instead
- Compromise of base OS images like Alpine enabling arbitrary code execution across downstream deployments
- Insertion of malware into pipelines through tainted third party scripts and plugins
Cloud native environments intrinsically exacerbate such risks through heavier reliance on integrating third party code and frameworks.
Research shows attacks on open source supply chains now make up 68% of codebase exploits with JavaScript ecosystems facing some of the worst threats.
Insufficient identity and access controls
Overprovisioning permissions across users and service accounts coupled with inability to track identity lifecycle enables attackers to easily move laterally. Typically errors include:
- Excessive roles assigned to administrators all cluster scope instead of locking down control to specific namespaces
- Long lived tokens and certificates persisting past expiry through lack of rotation policies
- Confused deputies issues where loosely monitored third party integrations are exploited to escalate privileges
- Lack of segmentation controls allowing workloads to directly interact with each other and underlying infrastructure
Such gaps explain findings from IBM that 60% of Kubernetes cluster incidents originated from identity or access management breaches.
Malware infections within runtimes
The complexity of container platforms causes both misconfigurations as well as opportunities to achieve persistence:
- Orchestrator exploits providing control over clusters not patched to latest versions
- Privileged containers either overly entitled or spawned with sensitive mounts
- Cryptominers spun up through batch workloads and serverless runtimes
- Backdoored cloud functions allowing attackers to persist within serverless hosting
Frequent scanning paired with anomaly detection is key to countering such threats.
Overall simplified abstractions and seamless integrations defining cloud native platforms have also introduced new topologies of risk.
Mitigating Cloud Native Security Risks
So how can organizations overcome these challenges? Here are proven strategies:
Automate policy enforcement
Embedding compliance checks and security best practices into CI/CD pipeline prevents drift. Policy engines continuously validate configurations across namespaces, clusters and environments.
This allows issues to be flagged early – before they enter production.
Enable application self protection
Since attackers often target application logic on nodes, hardening workloads through runtime security enables self-defense.
Web application firewalls provide intrusion prevention, rate limiting and request validation easily integrated with microservices via API gateways and service meshes.
Isolate and compartmentalize
Creating trust boundaries through microsegmentation limits the attack surface. Network policies restrict lateral cross talk between workloads.
Authenticating infrastructure dependencies removes standing access risks.
Compromises can be localized through distributing controls.
Govern through DevSecOps
Security automation at code commit and policy automation post deployment closes gaps. Dynamic scanners continuously validate images and dependencies used across pipelines removing bad builds before they progress downstream.
CI servers enforce coding best practices while defending infrastructure as code prevents drift.
Centralize monitoring and alerts
Collating and correlating detection signals across microservices, functions, containers, orchestrators and virtual network layers enable analytically driven investigation powered by machine learning.
Streaming logs to concentrated SIEM systems focused on behavioral baseline monitoring provides unified visibility.
So in summary, a resilient defense framework secures across code flows, infrastructure configurations and user activity – all tailored for ephemeral systems predicated on seamless extensibility and rapid iteration.
Conclusion
The dominance of containerized microservices and serverless functions means cloud native security provides the most relevant protection model for modern infrastructures.
Legacy network-centric controls have proven inadequate for massively decentralized and ephemeral architectures spread across edge, multi cloud and on-premises footprints.
Securing the entire application lifecycle requires rethinking processes, controls, platforms and culture driven by key goals:
- Protecting credentials and secrets
- Embedding security into rapid iteration
- Automating policy and compliance
- Monitoring across distributed enclaves
Once in place, robust cloud native security unlocks more benefits through safer deployment of new applications at velocity.
So as attacks now routinely ransom Kubernetes clusters and compromise software pipelines, adopting systems designed ground up with trust zero principles has become an urgent imperative.
