In recent years, the number and sophistication of zero-day vulnerabilities have surged, posing a critical threat to organizations of all sizes. A zero-day vulnerability is a security flaw in software that is unknown to the vendor and remains unpatched at the time of discovery. Attackers exploit these flaws before any defensive measures can be implemented, making zero-days a potent weapon for cybercriminals.
A recent example is, for instance, CVE-2024-0519 in Google Chrome: this high-severity vulnerability was actively exploited in the wild and involved an out-of-bounds memory access issue in the V8 JavaScript engine. It allowed remote attackers to access sensitive information or trigger a crash by exploiting heap corruption.
Also, the zero-day vulnerability at Rackspace caused massive trouble. This incident was a zero-day remote code execution vulnerability in ScienceLogic’s monitoring application that led to the compromise of Rackspace’s internal systems. The breach exposed sensitive internal information, highlighting the risks associated with third-party software.
Traditional security solutions such as Security Information and Event Management (SIEM), Intrusion Detection Systems (IDS), and Endpoint Detection and Response (EDR) often struggle against zero-day attacks. These tools usually rely on predefined rules, known signatures, or behavioral patterns to detect threats. However, zero-day attacks are inherently new, unknown, and unpredictable, so these reactive security measures are not enough.
The limitations of traditional security tools stem from their dependency on historical data and static detection mechanisms. For instance:
Their reactive approach often results in delayed detection—if it happens at all—leaving organizations exposed until after the damage is done. Moreover, advanced attackers increasingly use obfuscation, polymorphism, and file-less malware, which can bypass traditional security measures entirely.
Given the limitations of traditional solutions, a proactive approach to security is essential. This is where Network Detection and Response (NDR) comes into play. Unlike conventional tools, NDR leverages machine learning and anomaly detection to identify irregular behaviors and suspicious activities, even without predefined rules.
By continuously analyzing network traffic and metadata, NDR can detect zero-day exploits early by identifying deviations from normal patterns. This approach significantly reduces the risk of severe impacts by providing early warnings and enabling faster incident response.
For example, an NDR solution can detect a Command and Control (C2) channel set up by an intruder using a zero-day exploit by leveraging these key capabilities: first, the solution continuously monitors all network traffic, including metadata such as source and destination IPs, connection times and traffic volumes. If an intruder establishes a C2 channel, even if using encrypted channels, NDR can detect suspicious patterns such as unusual outbound traffic, unexpected spikes, or communication with rare or new external IPs. If a zero-day exploit is used to infiltrate the network, subsequent C2 communications will often show anomalous behavior such as beaconing, irregular-sized transfers, or specific timing (e.g. “phone home” signals).
With the help of AI-driven algorithms, the NDR can analyze traffic patterns and detect even minor deviations from basic network behavior. When setting up a C2 channel, the tool can recognize atypical command sequences, traffic flows, or unusual communication protocols. Many C2 channels use techniques such as domain generation algorithms (DGA) or DNS tunneling to obfuscate communication.
An effective NDR solution with machine learning can detect such obfuscation by recognizing non-standard DNS queries or random domain patterns that differ from normal traffic. By correlating multiple indicators—such as unusual traffic after a system change (e.g. an unpatched zero-day exploit)—NDR can identify a potential C2 setup.
For example, if a device suddenly communicates with external hosts after executing a zero-day payload, this unusual activity would trigger alerts for further investigation. If an attacker uses a zero-day exploit to penetrate a system and establishes a C2 channel via a hidden technique such as DNS tunneling, the NDR solution can detect irregular DNS queries with patterns that deviate from typical query behavior (e.g., very long subdomain names, fast query intervals).
NDR also monitors connections to new or rare external IP addresses that the company has not previously interacted with and analyses anomalies in traffic that indicate attempts at data exfiltration or commands to compromised systems.
Zero-day vulnerabilities represent one of the most challenging security threats today. Traditional solutions, designed for known threats, cannot keep up with the evolving tactics of cybercriminals. Adopting advanced solutions like NDR is essential for modern organizations seeking to stay ahead of these threats and protect their critical assets.
Discover how advanced Network Detection and Response (NDR) can provide proactive defense against sophisticated cyberattacks. Download our comprehensive APT Whitepaper now to learn how Exeon’s AI-powered NDR solution can help you detect and mitigate emerging threats.
To see how NDR acts in your corporate network, and precisely how it detects and responds to advanced threats, watch our recorded threat detection video.
