The Widening Overlap Between Cloud Workloads and Cybersecurity

Written by David Balaban.

There’s no denying that the cloud has revolutionized the way businesses operate, offering on-demand scalability, greater agility, and reduced IT infrastructure costs. To the average organization, a shift from on-prem to cloud-based is truly a quantum leap in terms of benefits, but with the caveat that this can be a bumpy road full of hidden perils all along. The migration introduces a new security landscape whose elementary components called workloads are in the crosshairs and must be shielded against malicious actors.

A cloud workload denotes any task, process, or application that runs in a cloud computing environment. This could include anything from simple data storage to complex computational processes or data analytics pipelines. To run these workloads, organizations leverage cloud providers’ infrastructure and services, such as virtual machines, containers, or serverless computing entities.

What makes workloads potential targets?

Traditional cybersecurity concerns like data breaches, unauthorized access, and malware persist in the cloud territory. However, the very architecture of such an environment poses unique security challenges.

The main reason why cloud workloads can end up in malefactors’ spotlight is that they serve as conduits to accessing the wider applications they belong to. Plus, they often contain business secrets, financial records, intellectual property, customer data, and application code. Several more things that incentivize crooks to compromise workloads are as follows:

• Accessibility: Cloud services are designed to be accessible from anywhere within an internet connection, which makes them susceptible to attacks.
• Shared responsibility model: The onus is on both the provider and the customer to ensure security in the cloud. The roles are split as follows: the provider safeguards the underlying infrastructure, while the customer is responsible for shielding their workloads, data, and access controls. Lax conformity to this principle is a catalyst for vulnerabilities in user configurations.
• Distributed workloads: Cloud workloads can be dispersed across multiple servers and regions. This hallmark makes it more challenging to maintain visibility and control over their security.
• Economic incentives: Breaching cloud workloads can yield financial gains through data theft, ransomware raids, or cryptocurrency mining.
• Abundance of open source tools: While democratizing various aspects of cloud infrastructure deployment, third-party open source components such as code blocks pave the way for supply chain vulnerabilities and backdoor entry.
• Evolving attack landscape: As white hats close existing security gaps and come up with novel protection strategies, threat actors are constantly developing new methods to exploit vulnerabilities in cloud platforms and applications. This is a cat-and-mouse game that requires permanent efforts in terms of defenses.

The ripple effect from cloud workload exploitation

With cloud infrastructures gathering steam across enterprises today, the consequences of cyberattacks against the building blocks of such ecosystems can be devastating. The mainstream perspective is that the repercussions boil down to data breaches undermining the intactness of sensitive information stored in the cloud. However, the aftermath can stretch far beyond that.

Cloud workload abuse has serious economic undercurrents. Downtime caused by external interference such as DDoS disrupts business-critical services, leading to tangible monetary losses down the line. Remediation costs and reputational damages further compound the monetary impact of such onslaughts. Non-compliance with regulations like GDPR or HIPAA can result in legal consequences and hefty penalties.

Moreover, the loss of trust from customers due to a perceived failure to protect their data inevitably diminishes loyalty, which is a recipe for disaster when viewed through the lens of business continuity. Under the circumstances, cloud workload security comes to the fore as a fundamental way to maintain organizational well-being these days.

Protection best practices

Since any cloud environment is a synergy of closely related components, it takes a multifaceted, holistic approach to keep workloads safe. Virtual infrastructures, hardcoded secrets, as well as cloud management and DevOps consoles have been the “juiciest” targets for bad actors over the years.

Well-thought-out security mechanisms must extend across all these areas and work in concert with workload runtime protection. A fusion of the following battle-tested strategies can raise the bar for attackers high enough to foil exploitation in this arena:

• Access controls: Enforce the use multi-factor authentication, strong passwords, and role-based access controls throughout the cloud journey to limit unauthorized access. Deploying a turnkey identity and access management (IAM) solution can make these processes frictionless.
• Encryption: Encrypt data both at rest and in transit to make it meaningless for intruders who may potentially orchestrate a breach. An emerging technology called Confidential Computing can additionally protect data in use, which is arguably its most vulnerable state.
• Segmentation: Split your network into smaller portions with unique security controls to pull the plug on malefactors’ lateral movement.
• Security audits and patching: Proactive vulnerability scanning and timely patches of known security loopholes are instrumental in maintaining a secure cloud environment. This is also an important element of regulatory compliance.
• Security awareness training: Educate employees about secure cloud practices to minimize the risk of social engineering attacks and accidental data leaks.
• Intrusion detection and prevention systems (IDS/IPS): Implement automated ad hoc solutions to detect and respond to suspicious activity before it gets out of hand.
• Backup and disaster recovery: Prioritize your data and regularly back up the most valuable assets. Also, have an incident response plan in place to remediate the damage stemming from a breach and quickly restore normal operations.

It’s noteworthy that AI offers a potent set of capabilities to take the security of cloud workloads a step further. The technology excels in traversing vast amounts of information such as event logs and internet traffic patterns, identifying anomalies in real time. Properly trained machine learning models can make response and remediation decisions with little to no human involvement.

Endnote

Organizations can leverage the cloud’s benefits with confidence as long as they understand that security in this territory is an ongoing process rather than a product. Proactivity should be integrated into the very fabric of such digital infrastructures, from planning and design to implementing robust access controls and fostering a culture of security awareness. Regularly assess your security posture, adapt your strategies, and stay informed about the latest threats to ensure the continued protection of your cloud workloads.

About the Author

David Balaban is a cybersecurity analyst with two decades of track record in malware research and antivirus software evaluation. David runs Privacy-PC.com and MacSecurity.net projects that present expert opinions on contemporary information security matters, including social engineering, malware, penetration testing, threat intelligence, online privacy, and white hat hacking. David has a solid malware troubleshooting background, with a recent focus on ransomware countermeasures.