The proactive process of scanning through networks for evidence of hostile activity is known as threat hunting. Traditional cybersecurity solutions like firewalls and antivirus software are less aggressive than this. To safeguard their networks from threats, most businesses rely on perimeter security techniques. However, these precautions are no longer sufficient. As recent high-profile breaches have demonstrated, cybercriminals are growing smarter and finding new ways to access even the most well-defended networks.
Threat hunting is a technique for staying one step ahead of the bad guys. You can discover and halt assaults before they do damage by looking for signals of malicious behavior ahead of time. Cyber threat hunting entails proactively investigating an organization’s surroundings for unknown vulnerabilities and undetected attacks. This process can also be facilitated by third-party vendors who are specialists in the field of cybersecurity. These security specialists collect and analyze data from numerous sources inside and outside the organization to generate and test theories about potential risks based on cyber threat information, known attack approaches, and other information.
The following kinds of threat hunting can be identified.
Structured threat hunting
Threat hunting is structured and based on indicators of attack as well as the attacker’s strategies, techniques, and procedures. When these attack techniques are detected on the network are used to coordinate threat searches. Threat hunters can use these predefined technique blueprints to detect threat actors during the early stages of an attack before they cause harm to the environment.
Unstructured threat hunting
This kind of threat hunting begins with a trigger or indicator of compromise. Before and after the trigger, the hunter scans the network for harmful patterns. Threat hunters can look at historical data to the extent that data retention limits allow. This form of threat hunting can uncover new risks as well as threats that have previously penetrated the environment but are now inert.
Situational threat hunting
Threat hunting that is situational or entity-driven focuses on high-risk/high-value items like sensitive data or vital computing resources. Its key advantage is that it aids in the concentration and prioritization of threat hunting activity, hence increasing its effectiveness. Attackers frequently go after high-value or high-risk assets or privileged users like IT administrators, domain controllers, and development managers. Threat hunting aids in the identification of high-priority targets and the conduct of targeted searches for threats.
Threat hunting is driven by intelligence
Intelligence-driven hunting is a popular threat hunting method in organized hunts. Threat information reporting is central to this type of threat hunting, which frequently involves active exploitation. Security professionals will formulate their hypothesis and prepare their investigation once they are notified of this action. Instead of looking for indications, intelligence-driven hunts scan for specific behaviors of malicious actors and their tools.
Threat hunting best practices
Hunters must be aware of all aspects of their surroundings to detect anomalies. Architecture, communication channels, and user rights are all included. A threat hunter’s job is to find high-value data that might be the target of an attack. Hunters should be aware of corporate processes as well as staff and consumer behavior.
Access to system data, usually in log format, is a key part of transparency. Logs should be collected centrally so that modern security tools may easily analyze and collect them. Network filters, firewalls, and intrusion prevention and detection systems are all ehttps://dzone.com/xamples of tools that can provide useful information.
Threat hunters must comprehend the latest attack methodologies, tools, and processes to locate attackers who have gotten past security systems. It is not sufficient to rely on common knowledge or obsolete threat information. Modern threat hunting must go beyond the obvious, such as uncovering zero-day exploits or assaults that traverse security silos, such as account penetration combined with code injection or network attacks.
To summarize
Effective threat hunting requires human creativity and insight to succeed. Automated analytics skills from third-party specialists can however save threat hunters many hours of fruitless manual labor. Even while untrained machine learning algorithms are slower than humans at pattern detection, they can analyze far more data. Analyzing log files from multiple network appliances for possible threat patterns is more effective through automation. Threat hunters that are successful mix human inventiveness with automated analysis.