Threat hunting differs from traditional intrusion prevention technologies in that it detects hidden malicious activity and helps security teams defend against human-led attackers more effectively. It typically does this through taking a proactive approach by reviewing system logs and investigating anomalies that either support or contradict a hypothesis.
Hypotheses for an organization’s security environment can be developed based on situational factors or entity behavior that are specific to that environment. Hunters use stack counting and other data analysis techniques to detect patterns or anomalies within data.
What is Cyber Threat Hunting?
Cyber threat hunting is an efficient method for discovering threats in your network that cannot be detected through traditional detection technologies. The process involves examining log data, network activity logs, endpoints and threat intelligence to spot potential anomalies or signs of malicious activity within a network. Qualified hunters employ creative strategies and tools in order to detect suspicious behavior that doesn’t conform with common patterns or signatures associated with known threats.
Cyber threat hunts aim to identify and respond to potential hidden threats before they infiltrate an organization’s systems, networks or data. Furthermore, they assist with mitigating existing threats by eliminating or lessening their impact on business activities; this may involve responding to detected activities, installing patches/updates/network configuration changes/adjusting user privileges as necessary etc.
Understanding how a system operates normally is key to any successful hunt, including how users and devices normally interact. Teams regularly collect data from IT/OT/IoT and security systems for analysis against existing information – this may involve looking for things such as suspicious account activity, unusual DNS requests, login pattern deviations from normal patterns, port access deviations from norms deviations file tampering lateral movement etc.
As soon as a threat hunt begins, analysts will create a hypothesis and search for evidence of that hypothesis within collected data. Statistical analysis and intelligence analytics software may be employed in order to visualize relational data to reveal connections or correlations that would otherwise be difficult or impossible to discover with spreadsheets or manual searches alone.
Next step should be testing the hypothesis by comparing it against Indicators of Compromise (IOCs). This can be accomplished using various sources – IoCs from past breaches, IOCs from threat hunters or even something as basic as logging abnormalities, privileged account activity, network traffic patterns, registry changes or file tampering as indicators.
As part of a threat hunt, the final phase entails taking action on any confirmed malicious activity. This may involve taking measures such as deleting malware files, restoring altered or deleted files to their original state, deploying security patches and more. As your team works to address these activities, they’ll gain insight into the tactics, techniques and procedures employed by threat actors so they can improve detection capabilities going forward.
Detection
Threat hunting allows organizations to take an effective, proactive approach to cybersecurity by quickly detecting any malicious activity before an attack even begins. This process enlists both human and automated security analysts for detection, as well as advanced technology tools and techniques, so as to detect threats which would otherwise go undetected.
As cyber threats evolve, defenders must remain alert for possible signs of an attack to detect and thwart it – which makes threat hunters an integral part of any organization’s cybersecurity plan.
Historically, detecting breaches or intrusions involved searching for specific indicators of compromise (IOCs) like infected files, network traffic anomalies and port access abnormalities. Unfortunately, this approach was limited as attackers could use techniques to avoid traditional IOC methods and stay hidden.
Actively hunting threats is the best way to detect them. By continuously monitoring computing environments, threat hunters are able to detect malicious activities before they cause any damage and respond immediately. They do this by analyzing threat intelligence, log data, user and entity behavior analytics (UEBA), user analytics data as well as suspicious patterns or anomalies in user and entity behavior analytics (UEBA) reports or user and entity behavioral analytics (UEBA) results to detect suspicious patterns or anomalies that arise within them.
Though this method takes longer, it provides less reliance on luck and provides greater network visibility. Furthermore, threat hunters’ reports can feed directly into automated technologies to increase their effectiveness over time without needing human intervention.
Communication is of utmost importance during any hunt process. Threat hunters share their investigations’ results with all stakeholders and teams involved to ensure everyone fully comprehends the extent of an issue; furthermore, this transparency allows threat hunters to ensure any automated technologies can detect similar malicious activity in future and therefore decrease incidents.
Threat hunters must maintain a comprehensive knowledge of computer systems and networks in order to create scripts and programs to automate tasks, parse logs, analyze data sets, and carry out investigations more easily. Furthermore, technical writing skills are invaluable when communicating complex cybersecurity information to stakeholders who may not have your depth of understanding about your cybersecurity environment.
Prevention
Prevention technologies such as endpoint security and network defenses can drastically decrease the number of false positive alerts your cybersecurity team needs to deal with each day or hour, making it simpler and faster to identify and prioritize threat hunting opportunities.
Analysts can use various search techniques to query data sets in order to detect threat artifacts, including stack counting – a technique which utilizes frequency analysis of particular values within large datasets to detect outliers – in order to detect anomalous values that vary widely across data points. Stack counting can also help in uncovering anomalies where values vary significantly between individual points.
Pattern recognition can also help identify threat artifacts through pattern analysis of large data sets. This technique can identify suspicious activity that would otherwise go undetected with static rules alone, such as repeated attacks against an asset or vulnerability discovery. Furthermore, pattern recognition allows organizations to quickly detect “who,” “what,” and “when?” issues that deviate from expected geographical or seasonality patterns – providing insights that might otherwise remain hidden behind static rules alone.
Threat hunters must quickly respond once they identify an anomaly or potential pattern to contain its spread, such as disabling users, blocking IP addresses, updating passwords, installing security patches or altering network settings – among many other methods – so as to stop current attacks as well as learn from it to prevent future ones. Doing this helps security teams thwart current attacks while learning from past ones preventing further incidents in the future.
Assembling a security operations center (SOC) makes threat hunting much simpler; acting as your single point of contact for all cyber security matters. Utilizing an integrated threat detection and response platform will further aid your hunting capabilities by consolidating multiple log sources, adding threat intelligence telemetry data, and providing contextual analysis of security events. It should be noted, however, that such platforms require human expertise for their effective usage and management.
Resolution
With security teams having to respond to hundreds of alerts every day, it can be challenging for them to dedicate sufficient time or resources for proactive detection of malicious activity – leaving your organization open to attacks. Threat hunting provides an investigative approach and enhances existing security solutions by uncovering new threats that have bypassed detection tools.
As an effective cyber security technique, threat hunting combines human investigators’ skills with cutting-edge technologies and threat intelligence in order to detect hidden threats in your environment that would otherwise remain undetected. Threat hunters use intuition and creativity in detecting malicious activity within your network that cannot be detected automatically by automated tools; as an added benefit they may use what information is gained during this process to enhance automatic detections over time.
Cyber threat hunters use the collected data to inform security teams of any findings, so that they may respond and mitigate threats accordingly. They also utilize this information to mitigate current vulnerabilities, analyze trends, and predict possible attacks in the future.
Structured and unstructured threat hunting approaches differ substantially in their methodology and focus. Structured hunts use frameworks like MITRE ATT&CK to help detect malicious attackers before any damage can be done; while unstructured hunts typically begin with an indicator of compromise (IoC), and then search for patterns throughout a network both pre and post detection.
Once a hunt has concluded, the threat hunter uses its results to test their hypothesis against industry frameworks and models. This may include reviewing Indicators of Compromise (IoCs), such as privileged user activity, spoofed HTTP responses, registry changes or port access anomalies. Furthermore, keeping up-to-date on new attack techniques and mitigations in cybersecurity industry is vital as attackers have proven adept at switching strategies frequently; so keeping current with latest attack techniques and mitigations available.
While threat hunting may create new security incidents, an experienced hunter will be able to reduce false positives by understanding how suspect behavior was identified and applying that knowledge into automated detection systems. Doing this will prevent other threats from evading detection and improve your security technology’s efficiency.
