Combating AI-Driven Cyber Threats: The Imperative of Integrated Defense
In the ever-evolving realm of cybersecurity, adversaries continually refine their tactics, leveraging advancements in artificial intelligence (AI) to orchestrate more sophisticated and elusive attacks. The emergence of offensive AI has revolutionized cyber threats, enabling malicious actors to deploy attacks that are not only more complex but also more challenging to detect and mitigate.
The Rise of AI-Orchestrated Cyber Attacks
Recent developments have highlighted the integration of AI throughout various stages of cyber attacks. For instance, in November 2025, a significant AI-driven cyber espionage campaign was reported, where AI autonomously managed tasks from initial access to data exfiltration. This operation underscored the potential of AI to execute complex attacks with minimal human intervention, thereby increasing the speed and scale of cyber threats.
Another alarming trend involves the use of steganography, where malware is concealed within seemingly innocuous image files. These images, often disguised as legitimate software update prompts or CAPTCHAs, deceive users into inadvertently deploying malicious payloads such as remote access trojans (RATs) and information stealers. Such techniques effectively bypass traditional signature-based detection systems, rendering them less effective.
Furthermore, adversaries have been exploiting vulnerabilities in antivirus (AV) exclusion rules. Through a combination of social engineering, man-in-the-middle attacks, and SIM swapping, attackers have convinced victims to disable security measures, allowing malware to propagate undetected across enterprise networks. This method highlights the limitations of relying solely on endpoint detection and response (EDR) systems, as they can be circumvented by sophisticated attack vectors.
The Need for a Combined Defensive Approach
The evolving threat landscape necessitates a multifaceted defense strategy that integrates both EDR and network detection and response (NDR) systems. While EDR focuses on monitoring and responding to threats within individual endpoints, NDR provides a broader perspective by continuously analyzing network traffic to identify anomalies and potential threats traversing the organization.
In the context of AI-driven attacks, the synergy between EDR and NDR becomes crucial. EDR systems may struggle to keep pace with the speed and scale of AI-fueled attacks, potentially missing subtle indicators of compromise. NDR complements EDR by detecting behavioral anomalies and deviations from typical network patterns, offering an additional layer of defense. This collaborative approach enhances the organization’s ability to detect and respond to threats more effectively.
Addressing the Expanding Attack Surface
The modern attack surface is increasingly complex, with threat actors targeting multiple domains, including identity, endpoints, cloud services, and on-premises infrastructure. This multifaceted approach allows attackers to maximize their reach and impact while evading detection.
For example, the group known as Blockade Spider has been active since April 2024, employing a combination of techniques to execute ransomware attacks. By exploiting unmanaged systems to gain initial access, they move laterally across networks, seeking valuable data to encrypt and hold for ransom. The full extent of their operations was uncovered through the combined use of NDR and EDR, which provided comprehensive visibility into both virtual systems and managed endpoints.
Similarly, the Volt Typhoon attack observed in 2023 involved state-sponsored actors utilizing living off the land (LoTL) techniques to evade endpoint detection. By compromising unmanaged network edge devices, such as routers and IoT hardware, the attackers were able to mask their activities. NDR played a pivotal role in detecting variations in network traffic volume, revealing the malicious activity that had bypassed EDR systems.
The Impact of Remote Work on Cybersecurity
The shift towards remote work has introduced new vulnerabilities, particularly concerning Virtual Private Networks (VPNs). Compromised endpoints connected via VPNs can serve as entry points for malware, facilitating its spread across enterprise networks. If an EDR system fails to detect malware on a remote machine, the infection can propagate once the device connects to the corporate network. Additionally, compromised VPNs can obscure lateral network movements, making it challenging to identify malicious activities.
For instance, recent breaches of Salesforce supply chains were executed by leveraging AI to harvest OAuth credentials, granting unauthorized access to customer accounts. NDR can identify weak entry and transit points, highlighting areas that require immediate attention, while EDR can provide evidence of compromised accounts being used as pivot points for further attacks.
The Imperative of Continuous Monitoring and Collaboration
The examples above underscore the importance of continuous monitoring and the collaborative use of EDR and NDR systems. By working in tandem, these systems enable defenders to detect innovative adversary techniques and respond swiftly to emerging threats. As adversaries continue to enhance their capabilities through AI, adopting a combined defensive approach becomes essential for reducing risk and bolstering an organization’s ability to respond effectively.
Corelight’s Open NDR Platform exemplifies this integrated approach, enabling Security Operations Centers (SOCs) to detect novel attack types, including those leveraging AI techniques. Its multi-layered detection strategy encompasses behavioral and anomaly detections, identifying a range of unique and unusual network activities. As adversaries develop new methods to evade EDR systems, deploying NDR can significantly strengthen an enterprise’s defensive posture.
Conclusion
The advent of AI-driven cyber attacks necessitates a paradigm shift in cybersecurity strategies. Relying solely on traditional defenses is no longer sufficient. Organizations must adopt a combined defensive approach that integrates EDR and NDR systems, ensuring comprehensive visibility and rapid response capabilities. By embracing this collaborative strategy, organizations can effectively combat the sophisticated and evolving threats posed by AI-enhanced adversaries.
