Developing a proactive security strategy can potentially save an organization millions of dollars per year. According to IBM, the average cost of a data breach in 2023 added up to a staggering $4.45 million, up 15% over the last three years. This is especially true for cloud-native environments, which face unique security challenges due to their dynamic nature. Instead of waiting to respond to cybersecurity incidents after they happen, it's much better to embrace a proactive approach, and prevent them in the first place.
Security engineering is one way to build security into the software development lifecycle (SDLC). This approach requires that teams “shift security left,” meaning they address security early in the development stages, and continue to remain proactive through continuous monitoring. This article will explore five key ways to do this: defining clear security goals, planning for potential threats, actively looking for hidden threats, writing code with security in mind, and using log and event data from system monitoring to identify vulnerabilities. These methods are particularly useful in the cloud, where the traditional ways of keeping systems safe need to be rethought.
1. Define Security and Compliance Goals
Defining security and compliance goals is a critical first step in developing a proactive cybersecurity strategy. These goals help protect an organization's important digital information and ensure that the company meets certain standards and regulations.
The process of setting these goals requires a deep understanding of the company's specific attack surface. This includes knowing what risks the company faces and what compliance regulations it needs to follow. It's important to find the right balance between being secure and keeping the business running smoothly.
To make these goals a reality, it's necessary to involve everyone in the company, not just the IT department. This includes regular cybersecurity awareness training, given that 95% of all data breaches are caused by employee negligence. Additional proactive security measures include updating company policies to keep up with new threats, and choosing technology that helps meet these security goals. By taking these steps, the company can turn its security and compliance goals from ideas into actions that make the company safer.
2. Create a Threat Model and Mitigation Plan
Creating a threat model and mitigation plan is an important step in strengthening an organization's security posture. This process starts with identifying and assessing potential threats and weaknesses that could be exploited by attackers. It's essentially about looking at your system through the eyes of someone who might want to break into it, which helps in understanding how best to protect it.
Once these potential threats are identified, the next step is to develop a plan to reduce these risks. This plan might include a variety of strategies, such as proactive software updates and patch management, using advanced technology such as artificial intelligence for threat detection and response, and other actions designed to strengthen security.
The main advantage of taking this proactive stance is that it helps organizations use their resources more effectively. Instead of spreading their efforts thinly over many areas, they can focus on the most significant risks. This not only improves the organization's overall security but also prepares it better for preventing and responding to security breaches. By planning ahead and addressing threats before they become attacks, organizations can significantly reduce the risk of data loss, reputational damage, and other issues.
3. Embrace Proactive Threat Hunting
Embracing proactive threat hunting is about taking an active role in finding cyber threats that haven't been caught by the usual security measures an organization has in place. It's a critical step in discovering threats that are lurking unnoticed, including advanced persistent threats. The idea is to go beyond waiting for alerts and to start looking for signs of potential threats before they turn into serious problems. This approach is especially important in environments where data and applications are hosted in the cloud, as these can present unique security challenges.
To do this effectively, organizations can use a security data lake to analyze large amounts of application telemetry data, spotting signs of unusual activity that could indicate a security threat. This approach can be combined with artificial intelligence and machine learning, which can help identify patterns and anomalies that human analysts might miss. These technologies can sift through data much faster than humans can, making it possible to detect threats in real time.
The benefit of proactive threat hunting is a stronger and more secure environment. By finding and addressing threats early, organizations can prevent them from growing into bigger issues that could cause significant damage. This approach not only helps protect sensitive information but also strengthens the organization's overall defense against cyber attacks, making it more difficult for attackers to succeed.
4. Instill Secure Coding Best Practices
Adopting secure coding practices is a vital step in shifting security left, embedding it early in the development process. These practices involve following certain guidelines and standards, like those suggested by trusted organizations such as the NIST Secure Software Development Framework, to make sure that the software is built securely from the beginning.
Some examples of secure coding best practices include:
- Input Validation: Making sure that all data entering the system is checked and validated. For instance, if a program expects a date, it should reject any input that isn't a date. This prevents attackers from sending harmful data into the system.
- Regular Updates: Keeping all software up to date to protect against known vulnerabilities. Developers should apply patches and updates to both their own code and any third-party dependencies they use.
- Encryption of Sensitive Data: Encrypting data like passwords and personal information so that even if data is intercepted, it cannot be easily read by unauthorized parties.
- Error Handling: Writing code to handle errors gracefully without giving away too much information. For example, if something goes wrong, the system should not display detailed error messages that could help an attacker learn about its inner workings.
To ensure these and other best practices are consistently followed, developers can use tools designed to analyze code for potential security issues. These tools can automatically identify parts of the code that may be vulnerable to attacks, allowing developers to fix these issues before the software is released.
By making secure coding a priority, organizations can significantly lower the chances of their software being compromised. This leads to a stronger security posture, helping protect both the organization and its customers from the consequences of data breaches and other security incidents.
5. Leverage Log and Event Data for Continuous Security Monitoring
Keeping a close eye on the continuous stream of data generated by an organization's technology infrastructure is a key part of maintaining strong security. This process, known as continuous monitoring, involves watching and analyzing the logs and event data produced by systems and applications. These logs are records of what's happening within the system, such as user activities, errors, and system alerts. By examining this information, organizations can spot unusual or suspicious behavior that might indicate a security threat.
Cybersecurity log analytics and event data analysis allows organizations to gain a deeper understanding of how their systems operate and where potential security issues might lie. Tools like ChaosSearch are designed for this purpose, and can help teams create a security data lake to sift through vast amounts of data quickly. This empowers security analysts and DevOps teams to identify patterns and anomalies. For example, if an unauthorized user tries to access a restricted area of the network, this activity can be flagged for further investigation.
The real strength of this approach lies in its ability to provide accurate information about potential threats. When a security issue is detected, the detailed information collected through continuous monitoring enables a faster and more effective response. This might involve stopping an ongoing attack, preventing access to sensitive areas, or fixing a security weakness before it can be exploited. By leveraging log and event data, organizations can not only detect threats as they happen but also improve their ability to respond to incidents, reducing the potential impact on their operations and their customers.
Embracing Proactive Security Engineering to Build More Secure Software
Maintaining a proactive security posture is essential for cloud-native teams to effectively protect their applications against evolving threats. Integrating the outlined techniques into a proactive security strategy can significantly enhance an organization's ability to preemptively address potential risks, and build more secure, resilient software. It’s critical to set clear security goals, embrace threat modeling and mitigation, take advantage of proactive threat hunting, enact secure coding practices, and leverage log data for ongoing security analysis. Together, these techniques form a robust foundation for a proactive cybersecurity strategy, ensuring a resilient and secure cloud-native environment.
