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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.
There are a wide variety of threats that organizations must face in today’s rapidly evolving cybersecurity landscape. Some of the most common types of threats include:
Advanced Persistent Threats or APTs are a type of cyber threat where an unauthorized user gains access to a network and stays undetected for a long time. This type of threat is often used to steal data over a prolonged period or to cause continuous damage to the targeted organization. APTs are typically orchestrated by groups that have significant resources and are highly skilled in exploiting vulnerabilities in systems.
APTs are particularly dangerous because they employ a wide range of tactics to gain entry, remain hidden, and extract valuable information. They often involve complex malware and sophisticated evasion techniques that can bypass traditional security measures and remain undetected for extended periods.
Zero-day exploits refer to a cyber threat where a hacker exploits a software vulnerability before the vulnerability becomes generally known. There are no specific defenses in place because the software’s creators are unaware of the vulnerability until the attack occurs.
These attacks are particularly dangerous because they take advantage of the time gap between the discovery of a vulnerability and the release of a patch to fix it. This gives hackers an opportunity to exploit the vulnerability and potentially gain access to sensitive data or critical systems.
The Internet of Things (IoT) – a network of interconnected devices – presents a new frontier for cyber threats. These devices, ranging from smart home appliances to industrial control systems, are often not designed with security in mind, making them easy targets for cybercriminals.
IoT vulnerabilities can result in the compromise of personal data, disruption of services, and even physical harm. The increasing reliance on IoT devices in both personal and business contexts makes addressing these vulnerabilities a critical issue.
Fileless malware is a type of cyber threat that operates in the computer’s memory rather than on the hard drive. This makes it extremely difficult to detect and remove, as traditional antivirus software typically scans the hard drive for malicious files.
This type of malware is particularly dangerous because it can easily bypass traditional security measures. It can also persist on a system even after a reboot, making it a significant threat to organizations.
Phishing and social engineering attacks have evolved significantly in recent years. Cybercriminals are now using more sophisticated tactics, such as spear phishing and whaling, to trick individuals into revealing sensitive information or performing actions that compromise security.
These attacks often involve carefully crafted emails or messages that appear to come from trusted sources. They can lead to significant financial loss, data breaches, and damage to an organization’s reputation.
Deepfakes, or artificially created, realistic images or videos, represent a new form of cyber threat. They can be used to manipulate information, spread disinformation, and cause harm to individuals or organizations.
Deepfakes have the potential to undermine trust in digital content, manipulate public opinion, and even influence political outcomes. They pose a serious challenge to organizations and individuals alike, as they can be difficult to detect and counter.
Artificial Intelligence (AI) is not only being used to boost security but also to enhance cyber threats. AI-powered attacks can analyze vast amounts of data, learn from previous attacks, and automate tasks, making them more efficient and harder to detect.
AI-powered attacks can adapt to changes in security measures, identify vulnerabilities faster, and execute attacks at a scale and speed that humans cannot match. This makes them a grave threat to organizations and underscores the need for proactive security measures.
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 (UBA) 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, access valuable assets, or 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:
The first step in threat detection and prevention is to conduct a thorough risk assessment. This process involves identifying potential risks, vulnerabilities, and threats that could impact the organization’s information systems. This includes identifying potential attack vectors, assessing the likelihood of a breach, and evaluating the potential impact on the organization.
After identifying the risks, it’s essential to analyze and prioritize them based on their potential impact and likelihood of occurrence. This will help organizations focus their resources on addressing the most significant threats and vulnerabilities first. Prioritizing risks can be done using various methods, such as quantitative risk assessments, qualitative analysis, or a combination of both.
A security framework is a set of guidelines and best practices designed to help organizations establish and maintain a robust security posture. There are several well-known frameworks available, such as the NIST Cybersecurity Framework, ISO/IEC 27001, and the CIS Critical Security Controls. Organizations should choose a framework that aligns with their specific needs, industry regulations, and compliance requirements.
While security frameworks provide a solid foundation for building a secure environment, it’s essential to customize them based on the organization’s unique needs and risk profile. This may involve adapting the framework’s guidelines to suit the organization’s size, industry, and specific threats or vulnerabilities. Customizing the framework will help ensure it is effective in addressing the organization’s unique security challenges.
Developing an incident response plan is crucial for effective threat detection and prevention. An incident response plan outlines the steps an organization should take in the event of a security incident, including who should be notified, what actions should be taken, and how the incident will be investigated and resolved. Developing an incident response plan in advance will help organizations respond quickly and effectively to security incidents, minimizing the potential impact on their systems and data.
Developing an incident response plan is not a one-time task. Organizations should regularly test and update their incident response plan to ensure it remains effective in addressing new and emerging threats. Regularly testing the incident response plan through tabletop exercises or simulated incidents will help organizations identify areas where the plan may need to be updated or revised.
Providing security awareness training to employees is an essential component of threat detection and prevention best practices. Security awareness training educates employees on cybersecurity best practices, such as how to identify and report potential security incidents, how to create strong passwords, and how to avoid phishing scams. Providing regular training will ensure employees are aware of the latest threats and best practices for protecting the organization’s systems and data.
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
Simple Deployment
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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