In recent years, the number and complexity of zero-day vulnerabilities has increased, 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 taken, making zero-days a powerful weapon for cybercriminals.
A recent example is, for example, CVE-2024-0519 in Google Chrome: This high-severity vulnerability was heavily exploited in the wild and involved an out-of-bounds memory access problem in the V8 JavaScript engine. This allowed remote attackers to gain access to sensitive information or cause a crash by exploiting heap corruption.
Additionally, a zero-day vulnerability at Rackspace caused massive problems. The incident was a zero-day remote code execution vulnerability in ScienceLogic’s monitoring software that compromised Rackspace’s internal systems. The breach exposed sensitive internal information, highlighting the risks associated with third-party software.
Why traditional solutions fail
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 typically rely on predefined rules, known signatures or behavior patterns to detect threats. However, zero-day attacks are inherently new, unknown, and unpredictable, so these reactive security measures are not sufficient.
The limitations of traditional security tools stem from their reliance on historical data and static detection mechanisms. For example:
- SIEM systems: Aggregate and analyze log data based on predefined criteria. If an attack does not match a known signature, it goes unnoticed. Generating a large number of false alarms in the SIEM also weakens the SOC team’s effectiveness against “real” attacks.
- IDS Tools: Monitor network traffic for suspicious activity using established patterns and missing zero-day exploits that use new evasion techniques.
- EDR Solutions: Rely on signatures and behavioral analysis that are ineffective against zero-day vulnerabilities using new attack vectors.
Their reactive approach often results in delayed detection – if it occurs at all – leaving organizations exposed until the damage is done. Moreover, advanced attackers are increasingly using obfuscation, polymorphism, and fileless malware that can completely bypass traditional security measures.
You need proactive security: Enter Network Detection and Response (NDR)
Given the limitations of traditional solutions, a proactive approach to security is required. Here is where Network Discovery and Response (NDR) comes into play. Unlike conventional tools, NDR uses machine learning and anomaly detection to identify irregular behavior and suspicious activity even without predefined rules.
By constantly analyzing network traffic and metadata, NDR can detect zero-day exploits at an early stage by detecting deviations from normal patterns. This approach significantly reduces the risk of major shocks by providing early warnings and enabling faster incident response.
Key features of an effective NDR solution
- Real-time threat detection: Continuous monitoring of network traffic metadata allows NDR to detect suspicious activity without relying on static signatures.
- Advanced Machine Learning: Heuristic analysis and AI-driven algorithms identify new attack vectors, minimizing the chance of missed detections.
- Detailed information: NDR provides deep visibility into network activity, enabling security teams to respond quickly and accurately to emerging threats.
For example, an NDR solution can detect a command and control (C2) channel created by an attacker using a zero-day exploit using the following key capabilities: First, the solution continuously monitors all network traffic, including metadata such as source and destination. IP, connection time and traffic volume. When an attacker establishes a C2 channel, even when using encrypted channels, NDR can detect suspicious patterns such as unusual outgoing traffic, unexpected spikes, or communication with rare or new external IP addresses. When a zero-day exploit is used to penetrate the network, subsequent C2 communications will often exhibit anomalous behavior such as beacons, irregularly sized or timed transmissions (such as “phone home” signals).
Using AI-driven algorithms, NDR can analyze traffic patterns and detect even minor deviations from the underlying network behavior. When configuring a C2 channel, the tool may recognize unusual 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 machine-learning NDR solution can detect such confusion by recognizing non-standard DNS queries or random domain patterns that differ from normal traffic. By correlating several metrics, such as unusual traffic after a system change (such as an unpatched zero-day exploit), NDR can identify a potential C2 installation.
For example, if a device suddenly communicates with external hosts after executing a zero-day payload, this unusual activity will trigger alerts for further investigation. If an attacker uses a zero-day exploit to infiltrate the system and establish a C2 channel using a covert technique such as DNS tunneling, the NDR solution may detect irregular DNS queries with patterns that deviate from typical query behavior (such as very long subdomain names , fast intervals requested).
NDR also monitors connections to new or rare external IP addresses that the company has not previously interacted with, and analyzes traffic anomalies that indicate attempts to steal data or commands to compromised systems.
Protect your organization from zero-day threats!
Zero-day vulnerabilities represent one of the most complex 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 today’s organizations as they strive to stay ahead of these threats and protect their critical assets.
Learn how Advanced Network Detection and Response (NDR) can provide proactive protection against sophisticated cyber attacks. Download our full APT document now to learn how Exeon’s AI-powered NDR solution can help you detect and mitigate emerging threats.
To see how NDR works in your corporate network and exactly how it detects and responds to advanced threats, watch our recorded threat detection video.
