Unleashing the Power of Threat Hunting in the Cloud

Threat Hunting in the Cloud differs from Legacy Threat Hunting (on-premise). Change my Mind.

This post, among many others in the “Cloud Threat Hunting” series, will take you into the Cloud Threat-Hutning and “little things” you should know. I have existed in the Cloud platforms since 2008 and have done many tasks, from general tasks and many security tasks, mostly for incident response and threat hunting.

In today’s digital landscape, where data and applications are increasingly migrating to the cloud (or exiting), organizations face evolving cybersecurity threats that require advanced detection and response strategies. As traditional security measures may fall short in cloud environments, proactive threat hunting has emerged as a crucial practice to identify and mitigate potential risks. In this blog post, we will delve into the concept of threat hunting in the cloud and outline effective strategies to strengthen your organization’s security posture.

Understanding Threat Hunting in the Cloud

Threat hunting is a proactive practice that focuses on actively searching for threats and identifying potential security incidents within an organization’s environment. Unlike traditional security measures that primarily rely on reactive defenses, threat hunting takes a proactive approach by actively seeking out signs of malicious activity, compromised assets, or vulnerabilities.

Defining Threat Hunting

Involves actively searching for threats within an organization’s environment, focusing on proactive detection rather than relying solely on reactive measures. In the cloud context, it involves uncovering malicious activities, compromised assets, or vulnerabilities that could expose critical data or systems.

Threat hunters use a combination of manual techniques, advanced analytics, and threat intelligence to identify indicators of compromise (IOCs), unusual behaviors, or suspicious patterns that could indicate the presence of malicious activity. They delve deep into the organization’s systems, logs, network traffic, and other data sources to uncover hidden threats, compromised assets, or vulnerabilities that could be exploited by attackers.

Key elements of threat hunting include:

Proactive Approach – Threat hunting is focused on actively searching for threats rather than waiting for alerts or incidents to occur. It involves assuming that the organization’s defenses may have already been breached and actively seeking out evidence of compromise.

Hypothesis-Driven Investigation – Threat hunters formulate hypotheses based on available threat intelligence, historical data, and knowledge of attack techniques. They then investigate the environment, looking for evidence that either confirms or disproves their hypotheses.

Advanced Techniques and Tools – Threat hunting leverages advanced techniques, including data analysis, anomaly detection, behavior profiling, and machine learning, to identify subtle signs of malicious activity that may evade traditional security controls.

Collaboration and Expertise – Threat hunting often involves cross-functional collaboration, bringing together security analysts, incident responders, network engineers, and other experts to share knowledge, insights, and skills. This collaborative approach enhances the effectiveness of threat hunting by leveraging diverse expertise.

Continuous Improvement – Threat hunting is an iterative process that evolves over time. As new threats emerge, attack techniques evolve, and the organization’s environment changes, threat hunters continuously refine their techniques, update their hypotheses, and incorporate new insights and knowledge into their hunting strategies.

By actively seeking out threats that may be lurking in the organization’s environment, threat hunting helps to detect and mitigate potential security incidents before they cause significant damage. It complements traditional security measures by providing an additional layer of defense, focusing on early detection, reducing dwell time (the time between a breach and its discovery), and minimizing the impact of cyberattacks.

Unique Challenges in Cloud Environments

Cloud environments present distinctive challenges for threat hunting due to their dynamic nature, shared responsibility models, and the complexity of distributed systems. Threat hunters must adapt their strategies to accommodate these challenges while harnessing the benefits offered by the cloud.

Threat hunting in the cloud involves actively searching for potential threats and security incidents that may have evaded traditional security measures. It requires a proactive and adaptive approach, leveraging advanced techniques, collaboration, and specialized knowledge to identify and mitigate risks. However, threat hunting in the cloud presents unique challenges, such as the shared responsibility model, cloud-specific attack vectors, complexity and scale of cloud environments, evolving infrastructure, visibility limitations, and compliance considerations.

To overcome these challenges, organizations must adopt effective strategies that leverage threat intelligence, utilize advanced technologies like machine learning, collaborate across teams, and continuously monitor and refine their hunting techniques. By doing so, organizations can proactively detect and respond to threats, bolstering their security posture in the dynamic and ever-evolving cloud landscape.

Complexity and Scale

Cloud environments are highly complex, with numerous interconnected systems, services, and workloads distributed across multiple regions. The scale of these environments can make it challenging to monitor and analyze vast amounts of data and logs generated by various cloud services. Threat hunters must adapt their techniques and tools to effectively navigate and analyze this complex ecosystem.

Dynamic Nature

Cloud environments are highly dynamic, with workloads being created, modified, and decommissioned on-demand. The dynamic nature of the cloud introduces a challenge for threat hunters, as they need to continuously adapt their hunting strategies to account for the ever-changing infrastructure. Traditional static approaches to threat hunting may not be effective in cloud environments, requiring a more agile and dynamic mindset.

Lack of Visibility

Traditional security measures that rely on perimeter defenses and network-based monitoring may not provide sufficient visibility into cloud environments. The distributed nature of cloud infrastructures, along with the use of serverless architectures, containers, and microservices, can result in a lack of centralized visibility. Threat hunters need to leverage cloud-native security tools, logging services, and data analysis techniques to gain comprehensive visibility into the cloud environment and identify potential threats.

Shared Responsibility Model

Cloud service providers operate under a shared responsibility model, where the provider is responsible for securing the underlying cloud infrastructure. At the same time, the organization is responsible for securing its data, applications, and configurations. Threat hunting requires collaboration and coordination between the organization and the cloud service provider to ensure comprehensive coverage.

Cloud-Specific Threats & Attack Vectors

Cloud environments introduce new threats and attack vectors that differ from traditional on-premises environments. These may include misconfigurations, insecure APIs, unauthorized access to cloud resources, data leakage from cloud storage, and exploitation of shared resources. Threat hunters must be knowledgeable about these cloud-specific threats and stay updated on the latest attack techniques targeting cloud environments.

Compliance and Legal Considerations

Organizations operating in regulated industries may face additional challenges related to compliance and legal requirements when performing threat hunting in the cloud. Compliance frameworks such as GDPR, HIPAA, or PCI-DSS have specific requirements for data protection and privacy. Threat hunters must ensure that their activities comply with these regulations and work closely with legal and compliance teams to address any concerns.

Strategies for Cloud-based Threat Hunting

Cloud-based threat hunting is a proactive cybersecurity practice aimed at detecting and mitigating potential threats in cloud environments. As organizations increasingly rely on cloud services, it is crucial to implement effective strategies for threat hunting to maintain a strong security posture. These strategies encompass a range of approaches, including leveraging threat intelligence, utilizing advanced technologies, fostering collaboration, and continuously monitoring and refining techniques. By adopting these strategies, organizations can proactively identify and respond to threats specific to cloud environments. This article explores these strategies in detail, providing insights into how organizations can enhance their cloud-based threat hunting capabilities and protect their critical assets in the cloud.

Leverage Threat Intelligence

Integrating threat intelligence into cloud-based threat hunting is essential for staying informed about the latest threats, attack vectors, and indicators of compromise (IOCs) specific to cloud environments. Subscribe to threat intelligence feeds and utilize threat intelligence platforms to gather relevant information. This knowledge empowers your team to proactively search for potential threats and identify patterns that might indicate an ongoing or impending attack.

Utilize Machine Learning and AI

Leveraging machine learning (ML) and artificial intelligence (AI) technologies can significantly enhance your cloud-based threat hunting capabilities. ML algorithms can analyze massive amounts of data, identify anomalies, and detect patterns of suspicious behavior in real-time. AI-powered systems can automatically correlate and prioritize security events, enabling threat hunters to focus on investigating the most critical threats. By leveraging these technologies, organizations can augment their human-driven threat hunting efforts, improve detection accuracy, and reduce response times.

Collaborate Across Teams

Encourage collaboration and knowledge sharing between threat hunters, cloud engineers, DevOps teams, and security operations center (SOC) analysts. Foster a shared understanding of the cloud environment, its configurations, and the associated security controls. Regular meetings, cross-training sessions, and joint exercises can help build strong relationships and facilitate effective communication. This collaboration enables teams to collectively respond to emerging threats, share insights, and identify potential areas of vulnerability or improvement within the cloud environment.

Employ Cloud-Native Security Tools

Leverage cloud-native security tools and services to enhance threat-hunting capabilities. Cloud service providers offer a wide range of security services that can provide valuable insights and visibility into your cloud environment. Utilize tools such as cloud-specific log management and analysis services, cloud-native intrusion detection and prevention systems, and cloud SIEM solutions. These tools are designed to work seamlessly within the cloud environment and can provide valuable data and alerts for threat-hunting purposes.

Implement Cloud-specific Hunting Techniques

Adapt threat-hunting techniques to the cloud environment. Consider techniques such as:

  • Centralized Log Management – The first step in cloud threat hunting is setting up a centralized log management system. This can be accomplished using cloud-native solutions like AWS CloudTrail, Google Cloud’s Operations Suite, and Azure Monitor. Other solutions like Elastic Stack (ELK) or Splunk can also be used.
  • Integrate Security Tools – There are numerous security tools that can help to identify threats in the cloud. AWS offers AWS GuardDuty and AWS Security Hub, Azure provides Azure Security Center, and Google Cloud has Google Cloud Security Command Center. Use these tools and integrate them with your log management system to get the most complete view of your environment.
  • Baselines – Set up baseline configurations to understand what is a normal activity in your environment. This is crucial in detecting anomalies that could be indicative of a threat. This can be done using cloud-native solutions like AWS Config, Azure Policy, or Google Cloud’s Asset Inventory.
  • Implement Anomaly Detection – Machine learning techniques can be useful to spot unusual behavior, such as unexpected network traffic or abnormal user behavior. Many cloud-native solutions like AWS Macie or Azure Advanced Threat Protection have anomaly detection built-in.
  • Use Cloud-Specific Threat Intelligence – Cloud service providers often provide threat intelligence feeds that are specific to their platform. This can be integrated into your threat hunting activities to identify threats specific to your cloud platform.
  • Perform Regular Hunting – Threat hunting is not a one-time activity. Regularly form new hypotheses based on the latest threat intelligence, and hunt for threats in your environment. This should be a continuous process of improvement.
  • Automate – Once you’ve found a process that works, automate it. Many cloud services offer automation and orchestration capabilities to help respond to threats quickly and effectively. For example, AWS offers AWS Step Functions, while Azure has Azure Logic Apps.
  • Incident Response – Plan your incident response processes and procedures ahead of time so you can react swiftly when a threat is detected. This includes defining how to quarantine affected systems, how to preserve evidence for forensic analysis, and how to communicate during and after an incident.

Continuously Monitor and Refine

Threat hunting is an iterative process that requires continuous monitoring and refinement. Regularly assess your hunting techniques, update playbooks, and incorporate lessons learned from previous investigations. Stay up-to-date with the evolving threat landscape and emerging attack techniques specific to cloud environments. Leverage data from previous threat hunts to identify patterns, indicators, and potential areas of improvement. This iterative approach ensures that your threat-hunting activities remain effective and adaptable to changing threats and cloud environments.

Bear in mind, Cloud-based threat hunting is crucial for organizations to proactively identify and mitigate potential security threats in their cloud environments. By leveraging threat intelligence, machine learning, collaboration, cloud-native security tools, and specialized hunting techniques, organizations can enhance their detection capabilities and strengthen their overall security posture in the cloud. Continuous monitoring, refinement, and staying abreast of cloud-specific threats and attack techniques are essential for maintaining an effective cloud-based threat-hunting program. By implementing these strategies, organizations can stay one step ahead of potential threats and protect their critical assets and data in the dynamic and evolving cloud landscape.

The Approach

What can be a general approach to threat-hunting?

A general approach to threat hunting typically involves a systematic and iterative process that combines proactive techniques, data analysis, and collaboration. While the specifics may vary depending on the organization and the environment, the following steps outline a typical general approach to threat hunting:

Define Objectives and Scope: Clearly define the objectives of your threat hunting activities. Determine the scope of your hunt, such as specific systems, networks, or data that you want to investigate. This helps to focus your efforts and ensure you have a clear understanding of what you are trying to achieve.

Collect and Analyze Data: Gather relevant data from various sources, such as logs, network traffic, endpoint telemetry, and threat intelligence feeds. Centralize and aggregate this data to enable comprehensive analysis. Utilize specialized tools and techniques, such as data visualization, correlation, and statistical analysis, to identify anomalies, patterns, or indicators of compromise.

Formulate Hypotheses: Based on the analysis of the collected data, develop hypotheses or educated guesses about potential threats or malicious activities. These hypotheses should be specific and testable, aiming to uncover suspicious behaviors or potential indicators of compromise. Consider leveraging threat intelligence and knowledge of current attack techniques to formulate targeted hypotheses.

Investigate and Validate: Actively investigate the hypotheses through manual analysis and advanced techniques. Conduct deep dives into the identified anomalies or indicators of compromise to gather additional evidence and validate their significance. This may involve examining network flows, system logs, user behavior, configurations, and other relevant data sources. Collaborate with cross-functional teams and experts to gain different perspectives and insights.

Refine and Iterate: Continuously refine your hypotheses, hunting techniques, and detection capabilities based on the insights gained from investigations. Incorporate feedback and lessons learned into future hunts. Update playbooks, detection rules, or automated systems to improve the effectiveness and efficiency of your threat hunting efforts.

Document Findings and Take Action: Thoroughly document your findings, including the identified threats, compromised assets, or vulnerabilities. Clearly articulate the impact, severity, and potential risk associated with each finding. Communicate your findings to relevant stakeholders, such as incident response teams, system administrators, or management, to enable appropriate actions and remediation.

Learn and Share Knowledge: Regularly share knowledge and insights gained from threat-hunting activities within the organization. Foster collaboration and information sharing among security teams, IT operations, and other relevant stakeholders. Encourage continuous learning and development of hunting techniques and skills through training, conferences, and industry collaboration.

By following this general approach to threat hunting, organizations can systematically uncover potential threats, identify vulnerabilities, and proactively respond to security incidents before they escalate. It emphasizes the importance of data analysis, collaboration, and continuous improvement in building a robust threat-hunting capability.

Effective Strategies for Cloud Threat Hunting

To proactively minimize the security gaps, create friction with the adversary, or even find a passive attacker in cloud environments, you must adopt effective strategies for cloud threat hunting. This article will delve into the importance of cloud threat hunting and provide insights into key strategies that can help organizations stay ahead of potential threats. Below is highlights for Cloud threat hunting:

  • Understanding Cloud Threat Hunting
  • Cloud-Specific Threat Landscape
  • Cloud-Specific Threat Landscape
  • Best Practices and Recommendations
  • Training and Skill Development

Now let’s dig into additional strategies:

Threat Intelligence

Threat intelligence plays a crucial role in cloud-based threat hunting by providing valuable information about the latest threats, attack techniques, and indicators of compromise (IOCs) specific to cloud environments. Here’s a deeper look into how organizations can effectively leverage threat intelligence:

Threat Intelligence Feeds

Subscribe to reputable threat intelligence feeds that provide up-to-date information on emerging threats and attack campaigns targeting cloud environments. These feeds aggregate data from various sources, including security researchers, industry experts, and global security communities. Regularly ingest and analyze threat intelligence feeds to stay informed about the evolving threat landscape.

Threat Intelligence Platforms

Utilize threat intelligence platforms that aggregate and analyze threat data from multiple sources. These platforms often offer advanced analytics, visualization tools, and automation capabilities to process and correlate large volumes of threat data. By leveraging such platforms, organizations can gain insights into threat actors, their tactics, techniques, and procedures (TTPs), and the specific indicators of compromise relevant to cloud environments.

Customized Threat Intelligence

Tailor threat intelligence to your organization’s specific cloud environment. Understand the unique characteristics and vulnerabilities of your cloud infrastructure, applications, and services. Customize threat intelligence feeds or platforms to focus on threats that are most relevant to your cloud deployment, taking into account the cloud service provider used, specific cloud services utilized, and industry-specific threats.

IOC Enrichment

Enrich threat intelligence with additional contextual information to enhance detection capabilities. Augment IOCs with metadata, such as IP geolocation data, domain reputation scores, or threat actor profiles. This enrichment helps in prioritizing alerts, understanding the potential impact of threats, and identifying correlation opportunities across different events and logs.

Threat Hunting Playbooks

Develop threat hunting playbooks that incorporate threat intelligence. These playbooks should outline step-by-step procedures, techniques, and tools to investigate specific threats or scenarios. Leverage threat intelligence to identify patterns or IOCs that are indicative of potential threats, and incorporate these indicators into the playbooks to guide proactive hunting efforts.

Collaborative Threat Intelligence Sharing

Engage in collaborative threat intelligence sharing with trusted industry peers, information sharing and analysis centers (ISACs), or threat intelligence communities. Participate in forums, conferences, and industry-specific working groups to exchange information on cloud-related threats and share insights on effective threat hunting strategies. Collaborative sharing enhances collective defense and widens the visibility of emerging threats.

Indicators of Behavior (IOBs)

Move beyond traditional IOCs and incorporate indicators of behavior (IOBs) derived from threat intelligence. IOBs focus on identifying patterns and behaviors associated with specific threat actors or attack campaigns. By understanding the tactics, techniques, and behaviors of threat actors targeting cloud environments, organizations can better detect and respond to sophisticated attacks that may not rely on known IOCs.

Indicators of Behavior (IOBs) are a valuable addition to threat hunting in cloud environments. Unlike traditional Indicators of Compromise (IOCs), which focus on specific artifacts or signatures associated with known threats, IOBs provide insights into the behaviors and techniques used by threat actors. Here’s a deeper exploration of IOBs and their significance in cloud-based threat hunting:

Behavior-Centric Approach: IOBs shift the focus from static IOCs to dynamic behavioral patterns exhibited by threat actors. Instead of relying solely on known signatures or artifacts, IOBs analyze the tactics, techniques, and procedures (TTPs) employed by attackers. This approach enables threat hunters to identify abnormal or suspicious behaviors that may indicate a potential compromise, even when traditional IOCs are not available.

Cloud-Specific IOBs: Cloud environments introduce unique attack vectors and behaviors that may not be captured by traditional IOCs. IOBs specific to cloud environments help in detecting cloud-specific threats and malicious activities. These behaviors may include unauthorized API calls, abnormal resource provisioning or deletion patterns, unusual network traffic, or suspicious access to sensitive data stored in cloud storage services.

Contextual Understanding: IOBs provide contextual understanding by considering the broader activities and behaviors surrounding a potential threat. They help threat hunters understand the intentions, motivations, and strategies employed by threat actors. By analyzing these behaviors, threat hunters can identify indicators that may not be evident through individual events or isolated incidents.

Anomaly Detection: IOBs facilitate anomaly detection by identifying deviations from normal patterns of behavior. By establishing baselines of expected behaviors within a cloud environment, threat hunters can pinpoint activities that deviate from the established norms. This enables the early detection of suspicious activities, lateral movement, privilege escalation attempts, or attempts to exploit misconfigurations within the cloud infrastructure.

Correlation and Link Analysis: IOBs enable the correlation and link analysis of related activities or events. By analyzing the behaviors exhibited across different logs, events, or systems, threat hunters can identify patterns that may indicate a coordinated attack, advanced persistent threats (APTs), or insider threats. Correlating IOBs with other sources of threat intelligence, such as threat actor profiles or campaign analysis, enhances the understanding of the overall threat landscape.

Proactive Threat Hunting: IOBs empower threat hunters to take a proactive stance in threat detection. Instead of relying solely on reactive incident response, IOBs help identify potential threats at an earlier stage, reducing dwell time and minimizing the impact of an attack. Proactive threat hunting based on IOBs allows organizations to stay ahead of emerging threats and adopt preemptive security measures.

Continuous Learning and Updating: IOBs are not static; they evolve along with the threat landscape. Threat hunters should continuously update and refine their IOBs based on new threat intelligence, emerging attack techniques, and lessons learned from previous incidents. Regularly sharing and collaborating with industry peers and threat intelligence communities ensures that IOBs stay relevant and effective.

Utilize Machine Learning and AI – Leverage the power of machine learning and artificial intelligence (AI) to augment your threat-hunting capabilities. These technologies can analyze massive amounts of data, identify anomalies, and detect suspicious activities in real time, providing valuable insights to threat hunters.

Collaborate Across Teams – Encourage collaboration between threat hunters, cloud engineers, DevOps teams, and security operations center (SOC) analysts. Foster a shared understanding of the cloud environment, promote knowledge sharing, and enable cross-functional teams to respond swiftly to emerging threats.

Continuously Monitor and Refine – Threat hunting is an iterative process that requires continuous monitoring and refinement. Regularly assess your hunting techniques, update playbooks, and incorporate lessons learned from previous investigations to optimize your organization’s threat detection capabilities.


Threat hunting in cloud environments requires organizations to leverage effective strategies and tools. Key elements include leveraging threat intelligence to stay updated on emerging threats, utilizing machine learning and behavioral analytics for enhanced detection, adopting a hypothesis-driven approach, and promoting collaboration among teams. Effective threat hunting involves deep dive analysis, automation of detection and response, continuous monitoring and improvement, and sharing knowledge and insights. Leveraging indicators of behavior (IOBs) helps shift the focus from static indicators to dynamic behavioral patterns exhibited by threat actors, facilitating anomaly detection, correlation, and proactive threat hunting. By implementing these strategies, organizations can strengthen their cloud-based threat hunting capabilities and proactively detect and respond to potential threats in their cloud environments.

Practical Hunting from the field

Hunting KQL on GitHub

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