NEWS: Logpoint Acquires Muninn
As we can read in the headlines every day, we are witnessing an escalation of sophisticated cyberattacks, which is in parts propelled by the power of automation. The responsibility of safeguarding against these threats falls on the shoulders of security teams, who often grapple with the challenge of maintaining comprehensive visibility across their entire operational environment.
The complexity arises from a multitude of security operations challenges that Security Operations Center (SOC) teams confront, including:
Expanding Attack Surface Monitoring: The digital transformation wave and the shift towards remote work have led organizations to broaden their IT infrastructure. This expansion includes migrating workloads to public clouds, developing cloud-native applications, and deploying IoT/OT devices. Regrettably, many organizations lack the appropriate monitoring tools or the requisite security expertise to effectively secure this ever-expanding attack surface.
Managing the Surge in Security Alerts: Each security tool in an organization's arsenal can generate hundreds of alerts daily. When combined, these security operations tools can easily churn out thousands of alerts per day, creating an overwhelming volume for teams to manage.
In response to these challenges, Gartner has proposed the concept of the SOC Visibility Triad. This triad comprises three key components: Security Information and Event Management (SIEM), User and Entity Behavior Analytics(UEBA), and a combination of Endpoint Detection and Response (EDR) and Network Detection and Response (NDR).
The primary objective of the SOC Visibility Triad, as defined by Gartner, is to significantly diminish the likelihood of an attacker successfully bypassing an organization's entire cybersecurity defense. Each component of the triad contributes unique and complementary capabilities, fortifying the overall security architecture. As a result, this integrated approach can identify a broader range of threats than any of the individual solutions could detect independently.
Security Operations Centers (SOC) frequently position SIEM products as the cornerstone of their enterprise protection strategies, and there are compelling reasons for their widespread adoption.
SIEM solutions excel in generating compliance reports and can be instrumental in early threat detection, provided the threats breach a predefined set of rules within the SIEM system. Some SIEM vendors are venturing into the realm of artificial intelligence, incorporating automatic rule generation, anomaly detection, and advanced statistical analysis.
Despite their prevalence, SIEM products are not without their limitations. They rely on log data, which inherently restricts their visibility, potentially leaving organizations exposed to lateral (east-west) movement attacks. Furthermore, the installation, configuration, management, and scaling of SIEM products can be complex and costly.
NDR solutions leverage network traffic analysis to scrutinize network communications in real-time. This analysis includes several layers, aiming to identify threats, unusual behaviors, and potentially risky activities. NDR systems offer in-depth insights into security events, providing security operations teams with forensic-level evidence to comprehend and report the full extent of security incidents. This is achieved by examining every network transaction and reconstructing all conversations through comprehensive stream reassembly. NDR tools can generate broad and very detailed data packages such as PCAP data, network log and metadata.
Utilizing these detailed data, NDR’s are designed to provide network visibility and detection across your entire network (East-West, North-South) and apply sophisticated machine learning algorithms to pinpoint anomalous behaviors and security events. This enables contextualized alerts and can even trigger automated responses. Learn more about how NDR works and what it is here.
SIEM systems work by aggregating and analyzing log data from various sources within an organization's IT infrastructure, including host systems and applications. The SIEM system collects this data and normalizes it into a standard format for easier analysis. It then applies correlation rules and advanced analytics to identify patterns or anomalies that could indicate a potential security threat. When a threat is detected, the SIEM system generates an alert for the security team to investigate further. Additionally, SIEM systems can assist with compliance reporting by providing a centralized view of an organization's security events and incidents.
Originating as compliance management tools over a decade ago, SIEM products have evolved significantly. The growing need for enhanced security measures has steered SIEM solutions towards integration within security operations centers in recent years. These SIEM systems are capable of generating detailed reports on incidents and events, encompassing malware attacks and other malevolent activities. If the analysis identifies activities that breach predefined rulesets, the SIEM system can trigger alerts to notify the security team.
Historically, SIEM solutions have been known to demand considerable effort for configuration and usage, and they depend on logs that also need configuration and lack self-adaptability. While there are preconfigured SIEM products on the market, they tend to be costlier and more susceptible to triggering false alerts. Given that these systems primarily consolidate logs and are prone to give context-free alerts, determining the most effective response can pose a challenge for SIEM users. Once a network is growing, integrating new data feeds into SIEM solutions and monitoring existing feeds can be a complex task.
Advanced NDR security platforms such like Muninn AI Detect and AI Prevent are able to handle a vast amount of network data in real-time and through machine learning quickly decode dozens of protocols to identify attack behaviors with enough context and evidence for SOC teams to take confident action.
NDR solutions are highly effective in hunting threats, thanks to their use of machine learning. They employ this technology to generate predictive behavior profiles, which enable them to identify previously undetected security threats. Furthermore, NDR solutions are particularly adept at detecting subtle, persistent threats, often referred to as "low-and-slow" tactics, techniques, and procedures. These are stealthy strategies used by cybercriminals who aim to remain unnoticed within a network for extended periods, slowly gathering information or gradually inflicting damage. By recognizing these patterns, NDR products provide a crucial layer of defense, significantly enhancing an organization's overall cybersecurity strategy. See the top 5 use cases for NDR here.
For those already using a SIEM solution, integrating a Network Detection and Response (NDR) system can dynamically enhance your cybersecurity strategy. Not only can it potentially decrease your overall security expenditure, but it can also significantly broaden your visibility into network activities. Furthermore, NDR can enrich the context of alerts and expedite your response time to legitimate threats, thereby hardening your organization's resilience.
For a more detailed deep dive into Network Detection and Response download our technical white paper.
If you are interested in exploring SIEM vendors and reading SIEM reviews, here are a few resources to check out:
G2 - Best Security Information and Event Management (SIEM) Software.
Capterra - SIEM Software.
Are you interest in learning more about Muninn's NDR solution? Book a meeting with one of our cybersecurity specialist and get the answers to your questions.
