NDR vs SIEM: The Key Differences

As cybersecurity toolkits advance in scope and compute power, it’s easy to miss how newer tools – like Network Detection and Response (NDR) – overlap with tried-and-trusted solutions such as Security Information and Event Management (SIEM). This article will uncover the differences between NDR and SIEM, while clarifying the best use cases and deployments for both.
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What is NDR?

Network Detection and Response is focused primarily on uncovering the granular day-to-day activities within an organization’s networks. Rather than placing a gateway at the edge of an organization’s networks – which grants visibility solely into North-South traffic – NDR places sensors on internal networks, logging all internal, or East-West, connections. In this way, NDR starts where the firewall leaves off.

An NDR’s sensors copy each packet – alongside its metadata – and send the copies to the solution’s central analysis engine. This is often achieved by network TAPs, or span ports, which are high-performance hardware-based sensors; other deployment environments can require software-based and virtual sensors.

Collectively, all of this data is assembled into an NDR’s continuous monitoring and response stack:

Network Behavioral Baseline Establishment

When first deployed, an NDR’s immediate role is to establish the normal, everyday behavior of its connected networks. This is achieved by feeding collected logs into an unsupervised learning algorithm, which assembles this stream of data into a model of average communication patterns, volume, and timing. By profiling all of this, an NDR can apply its first layer of network-level threat detection.

Detection of Deviations from Baseline

When a device’s network behavior begins to deviate from the normal model, the NDR can notice it and flag it as potentially suspicious. This behavior could include a sudden influx of login attempts, attempted connections to restricted ports, or the unexpected exfiltration of data from an employee that doesn’t usually access that database.

Depending on the erratic behavior in question, the NDR can then engage in either an automated response, or compare the network activity against known Indicators of Compromise (IoCs).

Signature-based Analysis

The majority of cyberattacks follow a specific approach: this attack profile results in set patterns of activities, or IoCs. To verify the risk behind network aberrations, an NDR can compare a network’s real-time activity against its database of IoCs, allowing it to rapidly and automatically detect exactly which attack is occurring – and help pinpoint a potential attacker.

Automated Response

Finally, if the NDR does verifiably discover a potential network intrusion, it can respond at the network level. This response could include quarantining compromised devices, blocking malicious traffic, or isolating affected network segments. This prevents an attacker’s lateral movement, and could shut down an attack before its full deployment.

What is SIEM?

While NDRs collect and analyze packets from an organization’s networks, SIEM spreads an even wider net: it aims to gain full organization-wide visibility. Logs are small files that a device generates whenever it conducts an activity: they’re collected for SIEM analysis via a software agent that gets installed on each source device.

From there, the SIEM reassembles the log files into a cohesive view of each device’s actions:

Log Collection, Filtering, and Parsing

The agent monitors for new logs continuously, gathering them in real-time or at scheduled intervals, depending on system configuration. Before they’re sent to the SIEM platform, the agent filters out noise (irrelevant data), parses key fields (such as timestamps, IP addresses, or event types), and extracts the most meaningful components.

Log Normalization

Each device or application generates logs in its own syntax— this can range from human-readable text to dense JSON or XML structures. To make it all legible to the SIEM’s analysis engine, the system identifies the source for each log and applies a parser tailored to that specific format. Parsers break down log entries into individual data fields, such as timestamp, source IP, destination port, event type, or user ID. This standardized schema can then be compared and analyzed across systems.

Analysis and Alerting

The SIEM begins by scanning for predefined patterns and indicators of compromise (IOCs), such as multiple failed login attempts, unusual data transfers, or access from blacklisted IP addresses. These patterns are usually encoded in detection rules or use cases that map to specific threats, like brute-force attacks or lateral movement.

Correlation is a key part of this analysis process. SIEMs link together seemingly unrelated events across different systems – like a suspicious login followed by a configuration change and a large file download. When a collection of suspicious alerts is discovered, the SIEM sends an alert to the organization’s security team, who then verify and remediate the underlying security risk.

NDR vs SIEM: Two Different Use Cases

Since NDR and SIEM have slightly different focal points, their ideal use cases vary drastically. Consider the following:

Lateral Movement Detection

NDR is particularly effective at detecting lateral movement because, unlike traditional security tools that rely heavily on logs and endpoint data, NDR targets the real-time behavior of devices and users over an internal network- making it specifically trained to spot the subtle signs of an attacker snooping around post-compromise.

Single Pane of Glass

SIEMs provide teams with a single pane of glass, centralizing and consolidating security data from the full breadth of an organization’s assets into one interface. Instead of analysts jumping between multiple tools, each covering a specific isolated domain, a SIEM aggregates everything into one platform.

SIEMs support this one-stop functionality by offering customizable dashboards, real-time alerts, incident timelines, and reporting features within an accessible UI. As a result, teams can consolidate a great deal of their workflows into one, and drastically streamline day-to-day operations.

Combine NDR Precision and SIEM Visibility with Stellar Cyber’s Open XDR Platform

While SIEM and NDR are both individually powerful tools, their combined might allows for security teams to map the full attack chain – from initial device compromise to lateral movement and malware deployment – and deliver immediate remediation. Stellar Cyber’s Extended Detection and Response (XDR) provides this. Stellar Cyber acts as a Next-Gen SIEM, channeling all device and network intel into a central analysis engine. Rather than simply generating alerts, however, Stellar Cyber adds another layer of threat identification, which clusters alerts according to the specific incident they relate to. This way, false positives are dropped, and genuine alerts are mapped to an attacker’s specific points of entry and ensuing interactions. Finally, these incidents are delivered to the entirety of your security team according to Stellar’s customizable dashboard. Skip manual intervention entirely and deploy automated playbooks, or give analysts cutting-edge incident visibility. Explore Stellar Cyber with a demo, and start building your NDR and SIEM capabilities.

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