Rapidly evolving: this is one of the most overused descriptions for the cyber threat landscape nowadays. Still, it rings true and nobody can argue that threat actors have become notably aggressive and cunning with their attacks. One recent study shows that the evolving cyber threat landscape is causing widespread burnout.
To address the constantly changing nature of cyber threats and their impact, organizations should embrace a dynamic approach to threat monitoring. Threats quickly change, especially with the help of artificial intelligence. For organizations to keep up, it is important to learn how to adjust strategies and adopt new technologies that are more suitable for the kinds of problems posed by persistent cybercriminals.
Below is a guide to achieving a dynamic approach in tracking down and responding to threats. Instead of relying on threat signatures and fixed rules, it would help to take the following recommendations into account.
Consolidating security tools and teams
One of the hallmarks of a dynamic threat monitoring system is the unification of various security tools and teams. Some may think that this is a form of centralization, which would sound counterintuitive given that democratization is the go-to setup for many in the IT field nowadays. However, unifying security management is vital to ensure comprehensive security visibility and concerted actions.
Independent and self-directed teams or system parts are not too desirable in cybersecurity. Some may expect that autonomous parts can perform better against dynamic threats since their decisions are not dependent on other parts (or the higher-ups) so they can supposedly respond to security events more quickly. However, this only works in some situations, like when a threat has already been identified and there is a certainty that the actions that would be taken are appropriate.
In reality, the security information collected by different security tools or security teams still needs to be contextualized and properly analyzed to accurately determine and prioritize the threats encountered. Without contextualization, the resulting security alerts may end up as false positives or false negatives. Having too many of these weakens threat monitoring and the ability to respond promptly.
Ensuring real-time threat intelligence
Dynamic threat management does not solely rely on threat signatures, but this does not mean that threat intelligence is no longer necessary or that it is relegated to a minor priority. Threat intelligence is a crucial initial layer of threat monitoring, but it can only serve its purpose if it is up-to-date and delivered in real-time.
Threat intelligence should come from various reliable or authoritative sources. These include government institutions like CISA, cybersecurity frameworks like MITRE ATT&CK, and open-source providers of data such as the SANS Internet Storm Center, Microsoft, Pulsedive, and Phishtank.
In addition to obtaining real-time threat intelligence, it is also important for threat detection to be constantly and consistently in operation. Thanks to advanced artificial intelligence, it is now possible to automate threat monitoring 24/7. Together with data contextualization from security tools consolidation, security data is more efficiently collected and analyzed to detect potential threats or malicious activities more quickly.
Continuous monitoring ensures that there are no opportunities for cyber attacks to penetrate or find a window that allows sleeper malware to infect a system and activate at a later time. It ascertains that organizations get to promptly spot threats, isolate and mitigate attacks, and proceed with the launch of suitable countermeasures.
Eliminating the overreliance on cyber threat signatures starts with having the ability to detect threats without these signatures. This is where behavior-based analysis demonstrates its worth. It enables organizations to detect threats by evaluating behavior through complex algorithms.
Behavior-based analysis usually starts with a comprehensive analysis of a network to establish normal or safe behavior. Once this benchmarking is completed, AI can detect potentially harmful behavior without having access to the latest threat intelligence. It can detect zero-day exploits and other unknown attacks by examining patterns of behavior, making rapid threat detection and response possible.
Automated and flexible enforcement of security policies
Another important feature of dynamic threat management is the automation of incident response with flexible security policies. Organizations regularly encounter a wide range of attacks, so it is impractical to set rules to deal with each of them and manually respond to every incident. The response has to be automated but with flexible security policies.
For example, organizations can use an intrusion prevention system (IPS) that automatically detects and prevents attacks from penetrating the network. This detection and prevention regime can be based on threat signatures, URL filtering, malicious domain identification, and other criteria that can be configured easily depending on the kind of threats encountered. The security policies should be regularly updated to reflect the most recent threats. At the same time, they should be flexible enough to allow adjustments whenever necessary.
Proactive threat hunting
Proactive threat hunting refers to the active and methodical search for indicators of compromise, malicious activities, and other manifestations of cyber threats within a network or system. Unlike conventional cybersecurity, it actively and continuously pursues threats and employs data-driven analysis and hypothesis-backed investigations. It also supplements automation and machine learning with the expertise of a human security analyst.
This approach to threat hunting aligns with the goals of dynamic threat management. It yields the benefits of early detection, reduced dwell time, faster security event responses, and the ability to identify and prevent advanced threats. Additionally, it supports continuous improvement because of its iterative nature, which allows cybersecurity teams to build upon their experiences as they gain insights and explore their networks’ security weaknesses or blind spots.
Ongoing cybersecurity education
Lastly, it is important to provide sensible cybersecurity training and awareness to everyone who has access to the organization’s IT resources. Keeping security policies flexible and changing them in response to changing cyber threats is already a major challenge. Things can get even more complicated and challenging with people involved.
People are still the weakest link in the cybersecurity chain. Many still fall prey to social engineering attacks such as phishing and vishing. These deceptive attacks aimed at people have become even more dangerous with the rise of generative AI, which makes it possible to imitate people’s voices and automate the process of repetitively bombarding people with deceptive schemes.
To address evolving social engineering attacks, organizations need to provide continuous cybersecurity education, especially when it comes to threats that target people’s lack of knowledge and experience in dealing with sophisticated deception.
Change should be met with change, evolution with evolution. A stagnant cybersecurity strategy is a vulnerability. What used to work before may no longer work in the future. That’s why it is advisable to embrace dynamism in threat monitoring and management. Complacency has no place in modern cybersecurity. It is important to stay ahead of ever-evolving attacks by constantly improving cyber defenses, continuously monitoring and proactively hunting for threats, and making sure that everyone knows and understands the evolving nature of threats and the ways to address them.
Working as a cyber security solutions architect, Alisa focuses on application and network security. Before joining us she held a cyber security researcher positions within a variety of cyber security start-ups. She also experience in different industry domains like finance, healthcare and consumer products.