Threat detection is an organization’s ability to monitor events in its IT environment and detect real security incidents. Threat prevention is the ability to block specific threats before they penetrate the environment or before they do damage. Detection and prevention go hand in hand—in order to prevent threats, you must be able to detect them in real time.
Security organizations use sophisticated tools to detect and prevent threats. In the traditional security operations center (SOC), the main system used to collect threat data and detect threats was the security information and event management (SIEM) system. Increasingly, organizations are transitioning to eXtended Detection and Response (XDR), which can improve detection of evasive threats, automate investigation, and enable direct response to threats.
On the prevention side, a range of advanced threat protection technologies that leverage artificial intelligence (AI) are helping detect threats, even if they do not match a known malware or attack signature. These include NGAV, user behavior rules, and ransomware protection.
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Effective threat detection depends on the maturity of your cybersecurity operation and the tools at your disposal. The more your environment grows, the greater the need for automated solutions that can help with advanced threat detection.
Sophisticated cybercriminals targeting your organization are likely to be evasive and difficult to identify. For instance, you can never be certain if a hacker group or state-sponsored attacker has become interested in your organization. This has been the reason for many high-profile breaches.
Security operations centers (SOCs) and security teams can detect and respond to cyber threats before they become active and affect the organization. Even so, you should still have an incident response plan in place for when an incident occurs. This allows your team to isolate, respond to, and bounce back from cybersecurity incidents.
To arrange a timely and appropriate response, SOC teams must understand the particular cyber threat. Using frameworks such as MITRE ATT&CK can assist security teams with their understanding of adversaries and how they work, making threat response and detection faster.
SOC analysts can also gain a significant advantage from using advanced tools including behavioral analytics (UEBA) and threat hunting capabilities, which can help with proactive threat detection.
Traditionally, threat detection was based on technologies like security information and event management (SIEM), network traffic analysis (NTA), and endpoint detection and response (EDR).
SIEM systems collect security-data from across the enterprise and generate reports and security alerts, but they are limited in their ability to perform in-depth analysis of these events, and combine them into a meaningful attack story. Traditional SIEMs are also not able to directly respond to threats.
NTA, EDR and similar solutions are highly effective at detecting threats in specific silos within the IT environment, and enable teams to rapidly respond to them. However, they are separate solutions, requiring complex integration, and cannot detect evasive threats that move between silos.
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eXtended Detection and Response (XDR) is a new security paradigm that combines the strengths of traditional solutions. Like SIEM, it collects data from multiple security silos. Like NTA and EDR, it enables in-depth investigation and direct response to threats discovered in the environment. XDR collects in-depth data from networks, endpoints, cloud systems, email systems, and other resources.
XDR uses artificial intelligence (AI) and threat intelligence to identify threats and construct a full attack story, which security teams can easily visualize, and quickly act upon. It integrates with IT systems and security tools, enabling security teams to identify an incident, investigate it, and rapidly respond from the same interface.
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Here are some useful tools for detecting and preventing security threats.
NGAV solutions can help prevent both known and unknown attacks. To do that, NGAV solutions monitor the environment and respond to certain attack tactics, techniques and procedures (TTPs).
NGAV technology is an evolution of traditional antivirus software. While traditional antivirus technology primarily relied on known file-based malicious software (malware) signatures and heuristics, NGAV technology offers a system-centric and cloud-based approach.
NGAV technology employs predictive analytics powered by artificial intelligence (AI) and machine learning (ML) in combination with threat intelligence. These capabilities enable NGAV solutions to detect and prevent fileless non-malware attacks as well as malware.
NGAV solutions can identify TTPs and malicious behavior from unknown sources, as well as collect and analyze endpoint data to identify root causes. Additionally, NGAV solutions can respond to emerging and new threats that previously went undetected.
UBA solutions can track, collect and assess user activity and data using monitoring systems. UBA solutions can analyze historical data logs, such as authentication and network logs stored in log management and security information and event management (SIEM) systems. This information helps UBA solutions identify patterns of traffic associated with normal behavior as opposed to potentially malicious user behavior.
It is important to note that UBA solutions cannot respond to threats. Rather, these solutions are designed to provide security teams with actionable insights. However, some solutions can be configured to automatically adjust the difficulty of authentication for users that exhibit anomalous behavior.
Deception technology is designed to protect against threat actors that have managed to infiltrate a network. The goal is to prevent these actors from causing significant damage. To achieve this, deception solutions generate traps or decoys that mimic legitimate assets and deploy these traps across the infrastructure.
A deception decoy can run inside a real or virtual operating system environment. Typically, these decoys are designed to trick threat actors into believing they found a way to escalate their privileges and steal credentials. Once the trap is triggered, notification alerts are pushed to a centralized deception server. Then, the server records the affected decoy as well as the attack vectors used by the threat actor.
Advanced ransomware protection solutions can identify ransomware as it begins operating, and automatically respond, preventing it from encrypting your organization’s files.
Ransomware can be highly evasive, so protection systems use advanced analytics to detect abnormal processes that are likely to be ransomware and block them. For example, solutions can detect memory strings from known ransomware solutions, detect rapid encryption of files, and prevent exfiltration using decoys that appear to be valuable data.
Ransomware protection solutions can do more than just detect and immediately block a malicious process. They can execute built-in or customized playbooks to eradicate a ransomware threat from infected machines.
Vulnerability scanners automatically and proactively attempt to identify application, security and network vulnerabilities. Scanning is typically performed by in-house IT staff or third-party security service providers. Threat actors also use vulnerability scanners when trying to identify points of entry into a network.
A vulnerability scanning process typically includes the following:
Cynet 360 is the world’s first Autonomous Breach Protection platform that natively integrates the endpoint, network and user attack prevention & detection of XDR with the automated investigation and remediation capabilities of SOAR, backed by a 24/7 world-class MDR service. End to end, fully automated breach protection is now within reach of any organization, regardless of security team size and skill level.
XDR Layer: End-to-End Prevention & Detection
SOAR Layer: Response Automation
MDR Layer: Expert Monitoring and Oversight
Cynet 360 can be deployed across thousands of endpoints in less than two hours. It can be immediately used to uncover advanced threats and then perform automatic or manual remediation, disrupt malicious activity and minimize damage caused by attacks.
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