Building Resilience Against Recurrence with Cloud Remediation

Originally published by Tamnoon.

Written by Michael St.Onge, Principal Security Architect, Tamnoon.

In the fast-evolving cloud security landscape, successful remediation isn’t just about fixing issues when they arise – it’s equally about preventing the recurrence of these issues.

Prevention is the final, critical stage of the cloud security remediation process. After a specific threat or vulnerability has been addressed, prevention focuses on reducing the likelihood of that issue happening again. The goal is to implement systematic safeguards, processes, and controls to stop the same problems from recurring.

What Prevention Is: Reducing Recurrence Systematically

Prevention is the strategic deployment of policies and practices aimed at reducing the likelihood of security issues recurring in the cloud environment. In this context, prevention is not a set of static rules but a dynamic, evolving process that adapts to the ever-changing threat landscape.

To achieve effective prevention, organizations focus on establishing policies that ensure DevOps teams do not inadvertently replicate errors or misconfigurations. This involves a collaborative effort where security works with DevOps to build and enforce policies aligned with organizational goals.

Policies: Bridging the Gap Between Security and DevOps

The relationship between security and DevOps can sometimes be fraught due to differing priorities and approaches. DevOps teams often prioritize speed, innovation, and continuous delivery, while security teams are focused on risk mitigation, compliance, and safeguarding sensitive data. Without the right processes and policies in place, these goals can be at odds, potentially leading to tension and delays in the development lifecycle.

Consider a scenario where a DevOps team is under pressure to release a critical feature within a tight deadline. In pursuit of speed, they may bypass certain security protocols, such as rigorous testing or compliance checks. While this enables rapid deployment, it introduces security vulnerabilities.

Without clear policies and communication, such actions can lead to a compromise between speed and security, creating tension between the two teams.

The challenge is exacerbated by common pitfalls in how security teams approach policy development and enforcement. Such approaches tend to rely entirely on manual work (which doesn’t scale effectively) or on automated, machine learning-driven approaches (which – without proper context – can negatively impact production).

Where Current Approaches Fall Short

Manual Policy Creation is Time-Consuming

Traditionally, security teams attempt to prevent recurrence of an issue by manually creating new policies and processes. For example, after remediating incorrect IAM permissions, they may develop a policy dictating proper permission granting.

However, manual policy creation is extremely time-intensive and risks being too narrow or inflexible to prevent variants of similar issues. In a rapidly scaling infrastructure, manually updating access control policies for each resource can result in delays and inconsistencies. This lag in policy adaptation may expose the organization to vulnerabilities.

Consider a scenario where a manual policy dictates specific firewall rules for a set of applications. As the organization expands, new applications are added, but the manual policy update process lags behind. The result is an inconsistent application of security policies, leaving some resources exposed due to outdated rules.

Automation Risks Over-Enforcement Without Context

On the other end of the spectrum, some organizations use automated prevention methods based on artificial intelligence. While this increases speed, these systems often lack nuanced context about the environment and business needs. As a result, they risk over-enforcing restrictions or recommending overly broad changes that negatively impact operations.

Imagine an automated system identifying a pattern of user access that triggers a security alert. Without considering that these access patterns are part of a routine system upgrade, the automation restricts user access, causing operational disruptions. This highlights the need for human oversight to understand and contextualize security alerts.

Keys to Prevention

The most successful prevention strategies blend automation with manual oversight – with a focus on promoting consistency, automation, and adaptable processes.

Consistency

Consistent application of security best practices is essential for prevention. This requires close collaboration between security teams and developers to ensure policies are followed. Security must take care not to simply dictate to DevOps teams. Instead, fostering mutual understanding and trust is key so developers buy into the importance of prevention.

Automation

Automation streamlines policy enforcement, reducing manual effort and ensuring rapid responses to emerging threats. However, this automation is carefully calibrated to avoid over-enforcement, with human oversight providing the necessary context.

Process

A well-defined and documented process is essential for successful prevention. Organizations establish a clear process for creating, updating, and enforcing policies, including regular reviews and adjustments to adapt to evolving security challenges.

Real-World Example: Configuring AWS Config Rules

To illustrate the prevention stage, let’s consider a real-world example involving AWS Config rules – and how an organization might implement a process to prevent the creation of new unencrypted EBS volumes.

• Introduction: Unencrypted EBS volumes pose a security risk. Prevention involves systematically ensuring that new volumes are encrypted by default.
• Policies in Place: Policies are established to dictate that all new EBS volumes must be encrypted. DevOps trusts these policies as they align with security best practices.
• Consistency: The policy is consistently applied across the cloud environment, leaving no room for deviations or misconfigurations.
• Automation: AWS Config rules are configured to automatically detect and alert on any new unencrypted EBS volumes, triggering a swift response.
• Process: The prevention process includes regular reviews of encryption policies, updates based on emerging threats, and collaboration between security and DevOps teams.

The bottom line: Towards a better prevention approach

Preventing recurrence of cloud security issues is essential for reducing organizational risk. Manual policy creation is too slow while automation alone risks blind over-enforcement. The most effective prevention blends consistency, automation, and adaptable processes – amplifying the strengths of both human oversight and software safeguards. With robust prevention in place, organizations can systematically strengthen their cloud security postures over time.

For practitioners

For security teams, an optimized prevention process provides improved workflow efficiency, response agility, and clarity of responsibilities. By reducing time spent on manual policy creation and clarifying handling procedures, practitioners can focus their efforts on higher-value security initiatives. They can also respond faster to emerging threats thanks to predefined protocols. Streamlined prevention ultimately helps practitioners improve productivity and job satisfaction.

For management

For leadership, effective prevention delivers tangible improvements in overall security posture through proactive risk reduction. Metrics around policy violations, audit findings, and incident response times will steadily improve. Automated enforcement of compliance requirements also reduces organizational exposure. Leadership gains confidence that both existing and emerging threats will be systematically addressed before impacting the business. With robust prevention practices in place, organizations send a strong message that security is an integral part of their culture.