4 Threat Hunting Techniques to Prevent Bad Actors in 2024

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4 Threat Hunting Techniques to Prevent Bad Actors in 2024

4 Threat Hunting Techniques to Prevent Bad Actors in 2024
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Today’s cybersecurity threats are highly sophisticated; bad actors are using technology like no-code malware and AI-generated phishing campaigns to breach company networks with alarming frequency. With traditional detection methods failing to adequately protect networks, data and users, security teams must take a more proactive approach to identifying threats.
Threat hunting involves preemptively searching for threat indicators and potential vulnerabilities on the network that other tools missed. This guide discusses threat hunting techniques and solutions to mitigate 2024’s biggest cybersecurity risks.
Most organizations have already invested heavily in automated threat detection solutions like endpoint protection and firewalls but still struggle to identify and remove cyber threats, especially when they’re already on the network.
Proactive cyber threat hunting is valuable for:
Advanced threats are difficult to detect because they adapt their methods specifically to avoid automated detection tools. They may use new technology — like AI — to generate better, more human-sounding phishing emails. Other advanced threats target Internet of Things (IoT) devices, operational technology (OT) systems, Smart City implementations and other automated or remote devices that are harder to protect.
Threat hunting proactively seeks out the causes of advanced threats, such as unpatched vulnerabilities or poor security hygiene, and the signs that one is already occurring—such as unusual account behavior on the network—helping with advanced threat prevention and mitigation.
Many automated threat detection tools are signature-based, which means they identify potential threats by comparing them to a database of known patterns, such as specific registry changes or the way certain types of malware are executed. The obvious limitation of signature-based detection is that it can’t identify novel or never-before-seen attack methods.
Threat hunting uses advanced techniques and technologies to spot suspicious activity that could indicate an attack attempt or in-progress breach, even if none of that activity matches known threat patterns.
Another limitation of many automated security tools is that they focus almost entirely on prevention but struggle to detect attackers already on the network. Threat hunting proactively analyzes monitoring data from tools like security information and event management (SIEM) to spot anomalous behavior, such as unusually large data transfers or a spike in failed authentication attempts. This approach allows teams to reduce the duration of successful cyberattacks and the damage they cause.
Modern business networks contain hundreds of applications and devices that must receive regular updates to patch any security vulnerabilities that attackers could exploit. Unpatched vulnerabilities cause approximately 60% of all data breaches, but many organizations lack a strategy for identifying and mitigating them. Threat hunting involves proactively seeking out and patching vulnerabilities in enterprise software, device firmware, cloud applications and third-party integrations to prevent breaches and perform forensic analysis post-breach.
Data privacy regulations and cybersecurity insurance policies require companies to implement certain security tools and procedures. These requirements vary across industries and use cases but often include things like proactive patch management, strict data access controls and comprehensive security monitoring.
Threat hunting helps identify vulnerabilities and other potential compliance issues so teams can correct them before they’re exposed in a breach or audit. The tools and strategies used by threat hunters also improve overall data privacy and security, simplifying compliance and risk management.
Threat hunters use many different strategies to identify cyber threats. Four of the most popular threat hunting techniques include:
Human security analysts manually query monitoring data to search for potential threats. With human searching, threat hunters use tools like SIEM to aggregate monitoring data and then run queries for specific information. It can be challenging to formulate the right queries that aren’t too broad or too strict, and wading through all the results to find relevant information is tedious and time-consuming.
Automated tools sort monitoring data into clusters based on specific characteristics to aid in analysis. Data that shares particular characteristics are clustered together so that human and machine searchers can easily identify outliers that could indicate a vulnerability or compromise.
Threat hunters define a search parameter—such as a specific type of security event occurring at a certain time—and automated tools find the monitoring data that meets that criteria and group it together. Grouping helps threat hunters track an attacker’s movement on the network, determine what tools and techniques they’re using, and ensure that eradication attempts have succeeded.
Analysts look for statistical outliers among a set of aggregated data. These data outliers sometimes indicate an attempted or successful breach. Manually stacking very large data sets is tedious and prone to human error, so analysts typically use automated programs to process, sort and analyze data for outliers.
To assist with Security teams use a variety of threat hunting tools and solutions to collect and analyze data, identify vulnerabilities and anomalous activity and remove threats from the network.
Threat hunting encompasses a wide scope of techniques, methodologies, and tools used to proactively identify vulnerabilities and malicious actors on the network. Implementing threat hunting techniques and solutions can help you prevent breaches, limit the duration of (and damage caused by) successful attacks and simplify compliance and risk management.
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4 Threat Hunting Techniques to Prevent Bad Actors in 2024

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