Cloud workload security is a critical issue for businesses of all sizes. Protecting your cloud-based applications and data is essential to ensuring the safety and security of your business. However, securing cloud applications can be difficult.
Christina Harker, PhD
Cloud application security can be challenging. This is due to the complex nature of cloud environments, and the many threats that are specific to cloud-based systems. In this article, we will discuss some of the challenges involved in protecting cloud workloads and outline some possible ways to address these challenges.
The best approach to cloud workload security is implementing a defense-in-depth strategy. This involves layering multiple security controls and measures throughout the infrastructure. Zero-trust means assuming every other node or entity in your architecture could be compromised at any time; organizations need to utilize each of these elements to maintain a strong security posture. Let's explore some of these security elements further.
Access control is a fundamental aspect of cloud infrastructure security that aims to regulate user access to resources and services. It is typically composed of two key components: authentication (AuthN) and authorization (AuthZ). Authentication is the process of verifying the identity of a user, device, or system attempting to access a given resource or environment. This can be accomplished through various means, such as usernames and passwords, multi-factor authentication (MFA), or even biometrics.
Once a user or system is authenticated, the next step is authorization, which determines the level of access and permissions granted to the authenticated entity. Authorization policies are often based on the principle of least privilege, ensuring that users and systems are granted only the minimum access necessary to perform their tasks. Access control can be tricky to get right; as cloud usage scales the complexity and granularity of policy controls will grow exponentially.
Encryption plays a vital role in safeguarding cloud workloads by protecting sensitive data from unauthorized access and tampering, both at-rest and in-transit. For data at rest, encryption ensures that stored data, such as files, databases, and backups, are protected while they reside on physical or virtual storage devices within cloud infrastructure.
For data in transit, encryption secures information as it travels between different components, services, or users within the cloud environment or between the cloud and on-premises systems. Secure communication protocols like Transport Layer Security (TLS) or Secure Sockets Layer (SSL) are widely adopted to encrypt data during transmission, preventing unauthorized interception or eavesdropping.
Implementing transit security is fairly trivial–most cloud providers offer access to free SSL certificates, and automatically encrypt most transit pathways by default. Encryption at rest can be harder to manage. Engineering teams are often presented with several options for data encryption. Should you choose provider keys? Customer-managed keys? Do you have specific compliance requirements? Provide-managed keys can offer simplicity, but may fail certain compliance audits as they are shared across customers.
Customer-managed keys are more secure, but they must be managed just like any other cloud resource, including access control policies that can be difficult to work with.
Intrusion Detection and Prevention Systems (IDPS) are a broad category of devices and software that actively monitors and analyzes network traffic to detect and prevent malicious activities targeting cloud workloads.
These systems employ a combination of signature-based, anomaly-based, and behavior-based detection methods to identify potential threats, such as unauthorized access, malware, or Distributed Denial of Service (DDoS) attacks.
Enterprise organizations can take different approaches to implementing IDPS. Most major cloud providers offer their own managed IDPS offerings, however they are somewhat opinionated, limited in features, and can add significant cost to overall cloud spend.
Another approach is to utilize vanilla computing nodes to host open source solutions like Snort or Suricata. This is typically more cost efficient but requires significant engineering and operational effort to design, deploy, and maintain. Finally, several vendors now offer all-in-one hosted cloud solutions. While these integrate well with the platforms, they tend to also be significantly more expensive.
Vulnerability management is a crucial aspect of cloud workload security that involves the systematic identification, assessment, and remediation of vulnerabilities across the entire software development lifecycle (SDLC). As applications are developed and deployed within the cloud environment, vulnerabilities may inadvertently be introduced at various stages, potentially exposing the infrastructure to security risks.
Software development-focused organizations will need to implement a variety of tools and processes to make sure that vulnerabilities are handled at every stage of the SDLC. Early in the development lifecycle, the focus is on monitoring software package management dependencies, docker image sources, and the overall software supply chain. In-house code needs to be consistently monitored for the introduction of vulnerabilities via static analysis.
Production workloads demand active scanning to identify and highlight anomalous or abnormal behavior that might be indicative of a compromise or introduced vulnerability. The issue for most organizations isn’t so much choosing the right tools, but having the resources and security acumen to install and configure all of them, as well as creating and maintaining good security processes around vulnerability management.
Logging and monitoring have long been essential components of server infrastructure. They are critically important in the context of cloud workload security. Logs and metrics provide visibility into the activities, performance, and overall health of cloud and application infrastructure. Logs, in particular, can provide an up-to-date stream of “events” from inside an application or server, giving engineers a detailed understanding of what happens inside a live workload environment.
Every major cloud platform provides basic logging and monitoring facilities. Basic resource and bandwidth usage can be monitored, and logs can be streamed from a variety of sources into centralized aggregation. However, needs will often grow beyond these simplistic use cases.
Utilizing logs for security analysis means fielding a resilient and reasonably performant logging infrastructure, including the capacity for long term storage and large-scale analytics. Effective security usually means having a search interface, similar to tools like Elasticsearch, as well as the ability to automatically alert relevant personnel when a potential incident is identified. Third-party log aggregation tools are often complex and prohibitively expensive.
Effective cloud workload security means focusing on multiple elements, not all of them technical. While having the right tools in place at every layer of the application stack is critical, it’s also important to have the right culture and processes in place. Implementing the technical details is much easier when an organization focuses on effective, holistic security and engineering practices.
Achieving full visibility means understanding what's going on inside and around workload environments. Not just monitoring resources and network traffic either; DevOps and infrastructure engineers need to collaborate with development teams early in the SDLC to help implement instrumentation interfaces inside the core application logic.
It’s much easier to design code to emit useful information from day one than it is to try and glue that functionality on once primary development is complete. Monitoring needs to be a holistic exercise: Software supply chain, resource usage, logs and events, even cost anomalies. Seeing a massive spike in network egress costs could be an indicator of a compromised node.
Engineers at smaller startups may be more comfortable with understanding and mitigating cloud infrastructure security risks. However, engineering staff from enterprise organizations that may be just starting their journey into the cloud and agile development may have a skills gap.
It should be a top priority to plan and implement staff training programs on modern attack vectors and security techniques, as well as cloud infrastructure. Training also has the added benefit of boosted morale and engagement.
Cloud workload security seems to imply focusing on the environment where the application itself runs. In the modern threat landscape, that simply isn’t enough. Defense in depth aims to minimize the risk of a security breach by ensuring that even if one layer of defense is compromised, the remaining layers continue to provide robust protection.
In the cloud, where network boundaries are fuzzy, and resources are often publicly reachable by default, adjacent resources and platforms need to be secured and monitored as if they were part of the production workload environment. Attackers could just as easily elevate access using a neglected IAM role in some corner of an AWS account, rather than take the seemingly obvious route of attacking the infrastructure head on.
Manual work is great but it just doesn't scale. Asking a human to perform a task will always be "best-effort". Automation and orchestration means security policies are applied on every deploy, monitoring agents are always built into VMs, and container images are always scanned for vulnerabilities.
Implementing some aspects of automation into an agile, cloud-focused environment often means investing in DevOps-focused initiatives. Using a CI/CD pipeline as a central pillar, a variety of testing and policy enforcement can be seamlessly integrated and automated along with daily development and deployment work.
When it comes time to seek compliance or certification, security tooling should make it easy for engineers to provide auditors with data/proof. KPI-focused work grinds to a halt if engineers are scrambling to write bespoke scripts and queries to surface security data.
Audits often occur with strict deadlines looming; providing the requested data promptly is crucial for meeting those timeframes. Being able to quickly retrieve data enables a smoother and more efficient audit process. Having a repeatable process for extracting relevant data also ensures it’s accurate and to standards. A bash script that was hastily written to scrape Git logs may not provide the most consistent or useful data.
Effective cloud workload security demands a multi-faceted approach and defense in depth. There are significant challenges for any organizations in effectively securing their workloads, especially if they lack experience with cloud environments. There are principles to follow that can make it easier, but organizations should be pragmatic and understand exactly what they're facing.
Cloud Security Challenges Organizations Need To Overcome
Migrating on-premise infrastructure to the cloud is a top priority for many organizations today. The cloud offers a number of benefits, including scalability, flexibility and cost savings. However, many organizations are unprepared for the security challenges that come with cloud adoption. In this blog post, we will discuss some of the cloud security challenges that organizations need to overcome.