Businesses are now going paperless and digital, storing their valuable data in the cloud. However, whereas cloud storage allows everyone in the company to access the data at any time, it also brings certain cybersecurity challenges.
While cloud environments are scalable, flexible, and efficient, traditional security approaches often fall short, creating a need for advanced cybersecurity measures designed specifically for the cloud. One important technique in this regard is cloud threat hunting – a systematic and continuous search of malicious activity on the cloud and its subsequent elimination.
Cyber attackers are becoming increasingly sophisticated, employing advanced techniques including AI, zero-day exploits, and advanced persistent threats (APTs). Insider threats caused by employees with access to sensitive data also pose a challenge. Cloud threat hunting can help identify anomalies early on and reduce the dwell time of any malware. Here’s how you can do cloud threat hunting:
1. Developing a Strategy
To implement an effective cloud threat hunting strategy, you must have a well-structured approach that includes creating a robust threat-hunting framework and establishing meaningful metrics to measure success.
Two strategies are commonly used here: hypothesis-driven methodology and data-driven methodology. In the former, you start with a specific hypothesis about potential threats or vulnerabilities, while in the latter, you start with large volumes of data and use advanced analytics to identify anomalies and potential threats.
In hypothesis-driven methodology, you need a limited set of data relevant to the hypothesis, while in the latter, you need large amounts of raw data.
During the planning phase, you must also set up your KPIs. One KPI can be detection time, or the average time taken to detect a threat after it has entered the environment. Another KPI can be response time, or the average time taken to respond to and mitigate a threat after it is detected.
2. Leveraging Tools and Technologies
You can use tools provided by cloud service providers or third-party tools. For example, AWS equips your storage with AWS GuardDuty which continuously monitors for unwanted and unauthorized activity to protect accounts. It uses anomaly detection, machine learning, and integrated threat intelligence to pinpoint hazards. Similarly, Google Cloud has a Security Command Center (SCC) for cloud threat-hunting purposes.
Third-party tools include RED and SIEM. EDR, or Endpoint Detection and Response tools, monitor endpoint activities and provide detailed visibility into potential threats. On the other hand, Security Information and Event Management or SIEM tools aggregate and analyze log data from various sources to provide real-time event monitoring, threat detection, and incident response.
3. Conducting Threat Hunts
Regular threat hunts are essential for maintaining a strong security posture in cloud environments. This process involves developing hypotheses based on threat intelligence and historical data, performing active hunts for indicators of compromise (IOCs), and analyzing and correlating data.
When conducting hunts, you look for IOCs which are evidence of a potential security breach. They include unusual traffic or suspicious files. Similarly, you look for anomalous behavior such as unexpected data transfers, particularly to malicious domains, irregular login times, or unusual patterns of resource usage.
Endnote
As cloud solutions become more common in the digital scape, the number of cyber attacks also grows. Cloud threat hunting is a cloud cybersecurity approach in which you systemically and continuously scan your storage for any threat. You can use either a hypothesis-based or a data-driven methodology, and leverage either native or specialist third-party tools. Through constant cloud threat hunting, you can ensure safety for your cloud storage.
