Threat Hunting 101: A Critical Element of Cyber Security Strategy

Threat Hunting

Threat hunting is a proactive approach to identifying and mitigating cyber threats that may have evaded traditional security controls. It involves a combination of human analysis, machine learning, and automation to detect and respond to threats in real-time. In this article, we will explore the what, why, how, types, methods, and importance of TH in cyber security.

What is Threat Hunting?

TH is a proactive and iterative process of identifying, classifying, and prioritizing potential cyber threats that may have evaded traditional security controls. It involves a combination of human analysis, machine learning, and automation to detect and respond to threats in real-time. TH is not a one-time event, but rather an ongoing process that requires continuous monitoring and improvement.

Why is Threat Hunting Important?

TH is important because traditional security controls are often inadequate in detecting and responding to advanced cyber threats. According to the Cost of a Data Breach report, a data breach costs a company an average of USD 4 million. The longer the time between system failure and response deployed, the more it can cost an organization. Threat hunting helps to reduce the time from intrusion to discovery, reducing the amount of damage done by attackers.

How to Conduct Threat Hunting?

Conducting TH involves a combination of human analysis, machine learning, and automation. Here are the 10 essential steps to effective TH:

1. Hypothesis: Develop a hypothesis about a potential threat based on threat intelligence, known attack techniques, and other information.
2. Data Collection: Collect and process data from various sources, including network traffic, system logs, and endpoint data.
3. Data Analysis: Analyze the collected data using machine learning and automation to identify potential threats.
4. Trigger: Identify a trigger that points to a specific system or area of the network for further investigation.
5. Investigation: Conduct an in-depth investigation of the potential threat using technology such as Endpoint Detection and Response (EDR).
6. Resolution: Communicate relevant malicious activity intelligence to operations and security teams to respond to the incident and mitigate threats.
7. Continuous Monitoring: Continuously monitor the network and systems for signs of malicious activity.
8. Threat Intelligence: Gather and analyze threat intelligence from various sources to improve TH capabilities.
9. Automation: Automate threat hunting processes using machine learning and automation to improve efficiency and effectiveness.
10. Improvement: Continuously improve TH capabilities through training, testing, and evaluation.

Types of Threat Hunting

There are several types of TH, including:

• Proactive: Proactive TH involves identifying potential threats before they occur.
• Reactive: Reactive TH involves responding to threats that have already occurred.
• Intelligence-Driven: Intelligence-driven TH involves using threat intelligence to identify potential threats.

Methods of TH

There are several methods of TH, including:

• Network Traffic Analysis: Network traffic analysis involves analyzing network traffic to identify potential threats.
• Endpoint Analysis: Endpoint analysis involves analyzing endpoint data to identify potential threats.
• System Log Analysis: System log analysis involves analyzing system logs to identify potential threats.

Importance of Threat Hunting

Threat hunting is important because it helps to:

• Reduce the Time from Intrusion to Discovery: TH helps to reduce the time from intrusion to discovery, reducing the amount of damage done by attackers.
• Improve Incident Response: TH helps to improve incident response by providing relevant malicious activity intelligence to operations and security teams.
• Enhance Cyber Security Posture: TH helps to enhance cyber security posture by identifying and mitigating potential threats.

TH Methods and Importance

TH Method	Importance
Network Traffic Analysis	Reduces the time from intrusion to discovery
Endpoint Analysis	Improves incident response
System Log Analysis	Enhances cyber security posture
Intelligence-Driven Threat Hunting	Identifies and mitigates potential threats

Examples of Threat Hunting

Here are two examples of TH:

Example 1: Hunting for Lateral Movement

A threat hunter at a financial institution notices that a user’s account has been compromised, and the attacker has gained access to the network. The threat hunter hypothesizes that the attacker may be attempting to move laterally across the network to gain access to sensitive data.

Hunting Process:

1. The threat hunter collects network traffic data from the compromised user’s account and surrounding systems.
2. Using machine learning algorithms, the threat hunter analyzes the data to identify unusual patterns of communication between systems.
3. The threat hunter identifies a suspicious connection between the compromised user’s account and a database server.
4. Further investigation reveals that the attacker has used a legitimate tool to dump credentials from the database server.
5. The threat hunter communicates the findings to the incident response team, which responds by isolating the affected systems and resetting passwords.

Example 2: Hunting for Insider Threats

A threat hunter at a technology company suspects that an insider may be exfiltrating sensitive data. The threat hunter notices that a employee has been accessing sensitive data repositories more frequently than usual.

Hunting Process:

1. The threat hunter collects endpoint data from the employee’s workstation, including process execution history and file access logs.
2. Using behavioral analytics, the threat hunter analyzes the data to identify unusual patterns of behavior.
3. The threat hunter identifies a suspicious pattern of file access and encryption activity on the employee’s workstation.
4. Further investigation reveals that the employee has been using a personal cloud storage service to exfiltrate sensitive data.
5. The threat hunter communicates the findings to the incident response team, which responds by revoking the employee’s access to sensitive data and launching a full investigation.

In both examples, the threat hunter uses a combination of human analysis, machine learning, and automation to identify and respond to potential threats. By proactively hunting for threats, the organization can reduce the time from intrusion to discovery and minimize the impact of a potential breach.

Conclusion

In conclusion, threat hunting is a proactive and iterative process of identifying, classifying, and prioritizing potential cyber threats that may have evaded traditional security controls. It involves a combination of human analysis, machine learning, and automation to detect and respond to threats in real-time. By understanding the what, why, how, types, methods, and importance of threat hunting, organizations can better protect themselves from cyber threats.

Join us on Facebook, WhatsApp , Telegram , LinkedIn  and Cert-In for latest cyber security news.

Home