Next-Generation Antivirus (NGAV) software uses advanced technologies, like AI, to take endpoint protection into a new era of effective cybersecurity defence. Since 1984, AV-Test Labs have identified 1,440,577,389 strains of malware. New strains often mean new evasive tactics that avoid detection and prevention by conventional security measures. To counteract these evasive tactics, this new approach uses advanced capabilities to handle the tsunami of known and emerging cyber threats and protect sensitive data. These new tactics are an evolution from the earlier static measures used by traditional antivirus software.
Antivirus software (AV) took off in the 1990s as the internet became ubiquitous. Back then, malware, such as viruses, worms, and trojans, were propagated using floppy disks, portable drives, and email. AV software was designed to recognize the “signatures” of malware, comparing these signatures to a database of known malware. The software would then take some form of action to remove the threat. As time has passed, cybercriminals have learned to create malware that avoids using known static signatures.
The evolving malware landscape has found success by using increasingly sophisticated evasive tactics. These Next-Gen malware strains have left traditional signature-based AV software behind. Next-Gen Antivirus software is the new era in antivirus detection and prevention. NGAV is based on intelligent technologies like machine learning and behavioral analysis to deal with complex, multi-stage, dynamic, and emerging threats. Using technologies that provide pattern recognition and can spot anomalous changes across networks, access points, and other systems, NGAV provides the framework to detect evasive malware. Intelligent technologies' adaptability is the main difference between this modern take on threat prevention and conventional AV software. This shift in how threats are detected is critical in making antivirus software effective and preventing sophisticated modern cyberattacks.
Malware developers have created an armory of evasive tactics to use when creating malware. Some examples of these evasive tactics include the following:
Malware designed to be polymorphic can change its signature every time it is installed on a new system. Dynamically modifying signatures makes detection by conventional signature-based AV software challenging. Metamorphic malware is even more dynamic, changing not only its signatures, but often the underlying code, while maintaining its core functionality.
Malware developers use a form of encryption to obfuscate the malware code making it difficult for conventional signature-based AV software to detect. Other forms of encryption are also used to encrypt the malware files, making them unreadable without a specific decryption key. Again, this method will prevent signature-based AV software from detecting the virus.
A particularly clever form of evasive malware is “fileless malware.” The malicious code of these software programs operates only within computer memory. Because fileless malware leaves no traces on the filesystem, it avoids detection by conventional AV software.
Modern malware is designed to evade detection, which has limited the use of conventional, static signature-based antivirus software.
This limitation has led to the development of Next-Gen Antivirus (NGAV) software. NGAV has the challenging remit of detecting dynamic malware that is explicitly designed to evade detection. This challenge has led to the design of sophisticated AI-powered solutions that take a systemic view of potential malware infection.
As hackers have evolved their tactics to improve the success rate of malware installs, security vendors have reacted by changing the methods used for detecting infections. Next-Gen Antivirus software, rather than focusing on signatures, uses visibility across an expanded organization system to look for unusual and anomalous activity on a network, interfaces, configurations, and access patterns. By recognizing patterns and anomalies outside of expected behaviors, the software can spot emerging threats and complex multi-stage malware infections.
The main features and benefits of Next-Generation antivirus solutions include the following:
Real-time threat
Conventional antivirus software relies on periodic scanning and regular signature updates to identify possible malware. This means that conventional AV software can quickly become out-of-date and miss an infection. One of the key benefits of NGAV is the ability to detect threats in real-time.
Multiple layers of detection
Conventional AV software mainly relies on detecting known signatures in malware packages. NGAV, on the other hand, uses multiple techniques, such as behavioral analysis and machine learning, to detect and prevent both known and emerging threats.
Behavioral analysis
The ability to detect unusual or anomalous behavior is a critical tool in the NGAV armory. The software creates a baseline pattern of behavior across a system and uses this to detect suspicious changes. This ability helps to detect previously unknown and emerging threats.
Machine learning
Machine learning (ML) models form the basis of AI. The ML algorithm is used to learn and adapt to new and emerging threats. The ability to learn over time allows the software to become increasingly effective and efficient at spotting emerging and zero-day threats.
Ransomware protection
Ransomware is a lucrative way to extract money from an organization. The financial incentives are driving increasingly sophisticated strains of malware that are challenging to detect. NGAV’s use of machine learning and behavioral analysis, in real-time, provides the essential capabilities needed to detect the most evasive strains of ransomware. Ransomware mitigation, the ability to successfully recover data targeted in a ransomware attack, also forms a critical role in remediation from ransomware. Advanced anti-exploit technology uses multiple layers of protection to handle complex attack pathways used by modern ransomware attacks. The ability to detect and block abnormal encryption attempts, is essential to capture emerging and zero day ransomware threats. Also, the ability to restore files from backup copies to their original state ensures comprehensive ransomware protection.
Fileless attacks and unknown threats
Unknown threats, like zero-days and fileless attacks, go under the radar of conventional AV software. The use of machine learning and behavioral analysis by Next-Gen AV provides the capabilities to detect and prevent fileless malware detonation.
Cloud-based management
Unlike conventional antivirus software, NGAV may be used as a cloud-based solution. Delivered as a SaaS, Next-Generation Antivirus software has essential attributes for organizations that may use hybrid environments and have many remote workers and devices. The cloud-based delivery model means that organizations can have fast, scalable deployment with minimal disruption. The solution can also be delivered by an MSP cost-effectively. However, it is worth noting that NGAV can also be used outside the cloud if a mechanism is provided to download and install updates without cloud connectivity.
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NGAV |
Traditional AV |
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Detection of broad spectrum of threats, including zero-days and evasive malware |
Uses intelligent technologies like machine learning and behavioral analysis to detect unknown threats and adapt to emerging threats. |
Static signature-based analysis that requires periodic updates, making the AV software quickly out-of-date and limited in its ability to detect new malware strains. |
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Performance impact |
Cloud-native architecture does not slow-down endpoints and there is no need for additional software or hardware. |
Periodic scans and updates take up computing resources and slow down machines. |
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Ease of management and scalability (time-to-value) |
A cloud-native architecture allows for fast implementation, scalability and centralized management. The SaaS deployment model means that an MSP can deploy and manage NGAV. |
Slow implementation can take months in large enterprises. Management is similarly onerous, with slow, phased upgrades. |
Next-Gen Antivirus software leapfrogs ahead of traditional AV software by its use of layered and advanced detection and prevention capabilities. Advanced technologies allow a proactive approach to mitigating cyberattacks. The technologies that detect and prevent cyberattacks include AI, neural networks, machine learning, behavioral analysis, and heuristic algorithms. Importantly, NGAV can map relationships between patterns of behavior to identify the tactics, techniques, and procedures (TTPs) used by attackers. This threat intelligence can be used for both detection and to help build a picture of an attack, allowing security teams to harden systems.
NGAV uses these technologies to identify threats designed to evade static signature-based detection. Modern cyber threats are complicated and challenging to predict. However, capabilities offered by machine learning and behavioral analysis allow the software to learn to spot emerging threat patterns. These advanced capabilities include the ability to prevent zero-day attacks, i.e., unidentified and unpatched exploits.
Next-Gen Antivirus software leapfrogs ahead of traditional AV software by its use of layered and advanced detection and prevention capabilities. Advanced technologies allow a proactive approach to mitigating cyberattacks:
NGAV: It uses layers of defense, including intelligent technologies, like machine learning and some behavioral analysis, to detect sophisticated, complex, and evasive malware threats. Malware threats detected also include emerging and unknown malware strains.
EDR: Endpoint detection and response software provides deep visibility and continuous monitoring across all endpoints in an organization. An EDR tool then uses advanced behavioral analysis to identify anomalous behaviors across these endpoints, generating alerts with actionable intelligence for system administrators, SOC teams, and security professionals.
XDR: Extended Detection and Response tools extend the reach and capabilities of traditional EDR tools to the cloud, email, networks, and servers. They connect across network, endpoint, and cloud data to identify threats. XDR can combine the telemetry from multiple other solutions, such as SIEM, UEBA, and EDR tools.
NGAV is a first point of defense, but because of the continuous evolution of evasive malware, some threats may slip through. EDR and XDR are synergistic with NGAV and are used to detect sophisticated threats that slip through the net. These extended protection tools generate threat intelligence, alerting teams to allow the correct procedures to be implemented to contain the attack. XDR tools provide comprehensive, cross-system intelligence to help identify the tactics, techniques, and procedures (TTPs) used by the attacker. Security teams can use this to harden the system against subsequent attacks.
One of the significant benefits of using a Next-Gen AV, as opposed to more traditional AV software, is that implementation happens in hours, not months. This is due to the cloud-based architecture of Next-Generation antivirus software. Deployment strategies to optimize the solution include integration with systems like EDR and XDR to ensure that all threats are captured and intelligence generated. This provides a 360-degree protection strategy reflecting the entire organization. User training also helps to educate users on the tell-tale signs of human-centered threats, like phishing. Because of the cloud-based architecture, ongoing management and maintenance can be centralized, and updates can be rolled out quickly. An NGAV solution is ideal for a managed service provider (MSP) deployment.
NGAV is a fundamental tool for protecting any business against the threat of ransomware. Solutions like GravityZone by Bitdefender stop ransomware by blocking attacks and intercepting attempts to encrypt sensitive data. This dual action is an essential feature of extended anti-ransomware that unifies NGAV with EDR and XDR. Modern ransomware developers use complex TTPs (tactics, techniques, and procedures) to evade detection and circumvent security protection. Solutions that detect ransomware must be able to identify emerging patterns and map unusual activity to potential ransomware attacks.
Macmillan cancer support in the UK uses Bitdefender GravityZone for integrated endpoint protection, detection, response, and risk analytics across more than 3,350 endpoints, including Microsoft Windows and Apple macOS workstations, and Microsoft Windows, VMware ESXi, and VMware vSphere physical and virtual servers, as well as VMware Horizon virtual desktops. Bitdefender also protects Microsoft Azure running in Macmillan's hybrid cloud. As a result, the organization now spends 70% less time on incident response, with an 85% reduction in security consultant costs. There has also been a decrease in security-related trouble inquiries by 80%.
When evaluating NGAV solutions, an organization should keep certain elements in mind:
Layered technologies, including AI: Look for solutions that offer layers of protection, also known as defense-in-depth. Behavioral analysis is also essential in an NGAV solution, as it provides the capability to identify unusual behavior on endpoints.
False positives: Check out the solution statistics on false positives. NGAV uses powerful pattern recognition technologies, which could give rise to false positives. Ask the vendor how false positives can be dealt with in the solution to minimize their impact on employee productivity.
Handling of fileless attacks: Fileless malware is especially challenging as it is based on scripts often used legitimately by IT teams. Make sure the NGAV solution has simple configuration to identify malicious scripts.
Ransomware protection: A Next-Generation AV solution should be able to prevent the two-pronged attack tactics of a ransomware infection: stopping the malware from executing, stealing data, and encrypting critical files.
Anomaly Detection: While malicious and unusual behavior is often simple to detect, behavior that is common, but unauthorized is often more difficult to discern. Anomaly detection allows for the identification of just that type of behavior. By creating a baseline of what is normal and alerting when deviations from that baseline are observed, anomaly detection can bring attention to activity that would otherwise go ignored by traditional defenses. A common example is a login of a user account from an unusual location – nothing malignant on its own but could be signs of a credentials theft that can lead to a damaging security breach.
Easy to deploy and maintain: NGAV solutions are cloud-based, but they must have an easy-to-configure dashboard to allow for management across the extended enterprise.
Unification of extended protection measures: NGAV is part of a more comprehensive package of measures that should include Endpoint detection and response (EDR). For advanced security further unification with XDR consolidated protection beyond endpoints.
Cyberattacks are constantly pushing the boundaries of security, and in doing so, they create malware that circumvents all but the most comprehensive and advanced security solutions.
To ensure that even the most evasive and emerging threat is identified and stopped, Bitdefender GravityZone provides a unified platform that uses the combined capabilities of NGAV, EDR, and XDR for enhanced security. Bitdefender recognizes that there is no such thing as a "one-size-fits-all" solution in cybersecurity. A unified approach that uses multiple layers of defense, empowered by machine learning models, alongside non-AI technologies, addresses the challenges of modern cyberattacks. By using a unified antimalware platform, Bitdefender maintains top results in real-world protection tests.
Traditional antivirus solutions only work with known threats, as AV scans look for known malware package signatures. Also, traditional AV software requires periodic updates to keep its signature databases current. This limitation means that AV software takes a retrospective approach to malware detection and prevention. While traditional antivirus may still have some benefits, it should always be extended with more modern antimalware approaches that use AI and behavioral analysis.
Endpoint detection and response (EDR) software is synergistic with NGAV solutions by extending detection and protection capabilities. EDR also ensures that there is deep visibility and continuous monitoring across all endpoints. An EDR tool adds another layer of protection to capture the most persistent and evasive forms of malware, including preventing zero-day exploits. Once identified, an EDR tool generates alerts offering actionable intelligence for security teams to work with. EDR and NGAV solutions can be integrated into a unified platform.
Yes, NGAV solutions use advanced technologies like AI, machine learning, and behavioral analysis to detect unknown exploits. AI-powered technologies use massive data sources to identify patterns, learning how to spot early warning of emerging threats. Zero-days often encompass new patterns of behavior and novel processes. Applying machine learning and other AI technologies, like deep learning, helps identify zero-days.