Proactive Security Controls
Finnis Springer
Proactive controls are security controls that are designed to prevent the creation of noncompliant resources. These controls can reduce the number of security events handled by responsive and detective controls. These controls make sure that deployed resources are compliant before they are deployed; therefore, there is no detection event that requires response or remediation.
For example, you might have a detective control in place that notifies you if an Amazon Simple Storage Service (Amazon S3) bucket becomes publicly accessible. You might also have a responsive control that remediates it. Although you already have these two controls in place, you can add another layer of protection by adding a proactive control. Through AWS CloudFormation, the proactive control can prevent the creation of update of any S3 bucket that has public access enabled. Threat actors could still bypass this control and deploy or modify resources outside of CloudFormation. In this case, the detective and responsive controls would remediate the security event.
Proactive controls complement preventative controls. Proactive controls reduce your organization's security risk and enforce the deployment of compliant resources. These controls evaluate resource compliance before the resource is created or updated. Proactive controls are generally implemented by using CloudFormation hooks. If the resource fails the proactive control validation, you can choose to either fail the resource deployment or present a warning message. The following are some tips and best practices for building proactive controls:
When building new proactive controls, start in observe mode. This means that you send a warning message instead of failing the resource deployment. This helps you understand the impact of the proactive control.
AWS CloudFormation helps you set up AWS resources, provision them quickly and consistently, and manage them throughout their lifecycle across AWS accounts and Regions. CloudFormation hooks proactively evaluate the configuration of your CloudFormation resources before they are deployed. If noncompliant resources are found, it returns a failure status. Based on the hook failure mode, CloudFormation can fail the operation or present a warning that allows the user to continue with the deployment. You can use available hooks, or you can develop your own.
AWS Control Tower helps you set up and govern an AWS multi-account environment, following prescriptive best practices. AWS Control Tower offers preconfigured proactive controls that you can enable in your landing zone. If your landing zone is setup using AWS Control Tower, you can use these optional proactive controls as a starting point for your organization. You can build additional, custom proactive controls in CloudFormation as needed.
Proactive controls reduce the risk of human error that leads to the deployment of noncompliant resources. They also reduce human effort later in the development cycle because they make developers consider resource security prior to deployment. This applies the shift left practice to building secure resources because it forces compliance earlier in the development lifecycle.
Because proactive controls prevent the deployment of noncompliant resources, they reduce the amount of time you spend triaging and fixing security issues. They also the number of security findings, which detective controls would identify later in the development cycle.
While there may be some upfront costs associated with implementing proactive cybersecurity measures, the cost of a cybersecurity breach can be much greater. In addition, proactive measures can actually save time in the long run by preventing security incidents and minimizing the time and resources required to respond to a breach.
Many small and medium-sized companies make the mistake of believing that they're too small to be targeted by cybercrime when in fact, they are just as vulnerable as larger organizations. Any organization can be a target for cybercriminals, regardless of its size or industry. Small businesses may even be seen as easier targets because they may have fewer security measures in place.
Another common misconception is that proactive cybersecurity is only necessary for highly regulated industries such as finance, healthcare, or government. While these industries do have specific regulations and compliance requirements around cybersecurity, all businesses are at risk of cyber threats and need to be proactive in protecting their data and systems.
Some people believe that once they have implemented security measures, they no longer need to worry about cybersecurity. However, cybersecurity is an ongoing process, and threats are constantly evolving. It is important to regularly review and update security measures to stay ahead of potential threats.
These breaches are cautionary tales that demonstrate the importance of taking a proactive approach to cybersecurity. They illustrate the devastating consequences that can result from a failure to adequately protect sensitive information and address vulnerabilities in a timely manner.
While no organization can guarantee complete protection against cyber threats, a proactive approach to cybersecurity can help reduce the likelihood of a breach and mitigate the impact if one does occur.
AI and ML are already being used to automate security tasks such as threat detection, incident response, and vulnerability scanning. As the technology continues to evolve, AI and ML will likely play an even greater role in proactive cybersecurity.
One area where AI and ML are already being used is in the development of predictive analytics. Predictive analytics uses machine learning algorithms to analyze large amounts of data and identify patterns that can indicate potential security threats. By using predictive analytics, organizations can identify potential threats before they occur and take proactive measures to mitigate the risk.
Another area where AI and ML are likely to play a big role in shaping the future of proactive cybersecurity is in the development of autonomous security systems. These systems use AI and ML algorithms to continuously monitor and respond to potential security threats without human intervention. Autonomous security systems are able to learn from past incidents and adapt to new threats, making them more effective at preventing cyber attacks.
Finally, AI and ML are also being used to develop more advanced cybersecurity tools and technologies. For example, AI and ML algorithms can be used to identify new and emerging threats, analyze malware behavior, and detect phishing attacks. These tools can help organizations stay one step ahead of cybercriminals and better protect their systems and data.
Companies often confuse meeting compliance mandates with good security. This couldn't be further from the truth. Merely meeting operational compliance requirements doesn't guarantee protection against a breach. Compliance standards typically outline only the most necessary measures and controls. This might establish a baseline level of security, but it isn't likely to stop a breach.
An organization that experiences a breach despite meeting requirements might still face considerable penalties. It's important not to rely on compliance as security but rather take a proactive and holistic approach. You need to meet compliance requirements, but it's crucial to also strengthen defenses and mitigate risks.
Compliance standards matter. These regulations play a crucial role in establishing a baseline for cybersecurity programs, but organizations shouldn't mistake them for comprehensive protection against all threats. These standards often provide high-level requirements defining minimum security controls for specific security categorizations. Even renowned frameworks like NIST acknowledge that compliance controls are "the set of minimum security controls."
Viewing compliance as the pathway to security leaves you at a distinct disadvantage when attackers come knocking. Declaring that you comply with a given framework or requirement sounds great, but that's just the start of the journey.
Compliance standards often lack customization. It's critical to address your organization's unique risk profile and environments. Each business possesses its own distinctive attack surface, data requirements and regulatory obligations, making a one-size-fits-all compliance approach insufficient. Factors such as software variations and cloud infrastructure adoption can significantly alter the risk landscape.
For instance, encrypting the whole disk is an effective control for physical drive theft but is irrelevant in a cloud environment. Controls like this simply check the compliance box, doing little to bolster security. Adding controls such as encrypting individual files is more useful because it meets compliance and combats attackers attempting to steal data remotely.
The dynamic cybersecurity landscape is constantly facing emerging threats. While essential for establishing a baseline of security measures, compliance regulations struggle to keep up with rapidly evolving attack vectors and emerging technologies. As a result, organizations find themselves vulnerable to these changing threats.
A security-focused approach is crucial in establishing a robust and effective security program. Prioritizing security over compliance allows organizations to address actual threats and vulnerabilities, ensuring a comprehensive and holistic approach to safeguarding their data. Taking a compliance-first approach puts the cart before the horse and doesn't address the evolving landscape of cybersecurity threats.
By proactively identifying and mitigating potential risks, organizations establish a solid foundation of security measures that naturally align with compliance requirements. This approach enhances the overall security posture and leads to compliance, as the necessary controls and protocols are already in place to meet regulatory standards.
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