HawkAI – Elevating Cybersecurity with Precision Detection Rules
It is an undeniable reality that cyber threats are continually evolving, and organizations need to stay ahead to protect their assets. The SOC has, overtime, served as the frontline defence, continuously monitoring networks, systems, and user activities to identify potential threats and respond to them effectively. However, as cyber adversaries develop more sophisticated tactics, organizations will agree that they face mounting challenges in detecting subtle anomalies and even preventing security breaches in real time. Traditional methods of monitoring, though valuable, often struggle to keep pace with the sheer volume and complexity of modern threats and it is here that artificial intelligence (AI) has become a game-changer.
By integrating AI into SOC operations, organizations can augment human analysts with advanced capabilities to detect, analyse, and respond to threats more efficiently. AI enables automated analysis of vast datasets, identifies patterns that might elude manual review, and delivers quick-action insights faster than ever before. The ability of AI to adapt to new attack methods and evolve with emerging risks makes it an essential tool in modern cybersecurity.
HawkEye AI or HawkAI, which is DTS Solution’s SOC AI initiative, exemplifies the transformative potential of AI in threat detection and monitoring. Leveraging data-driven insights, HawkAI empowers businesses to identify and neutralize potential cyber threats before they escalate into significant issues.
Threat Detection with HawkAI
The core mission of HawkEye AI is to enhance SOC operations by addressing three key pain points in cybersecurity through the following –
Precise Threat Detection – It identifies anomalies in real-time to alert analysts about potential incidents with the ultimate goal of reducing false positives.
Predictive Insights – HawkEye AI predicts likely attack vectors and allows organizations to fortify their defences proactively.
Adaptive Learning – The platform evolves in tandem with emerging threats and adjusts its models and thresholds to remain relevant and effective.
HawkEye AI excels in handling a variety of detection challenges that traditional systems struggle to address. Its core features include –
- Dynamic Outlier Thresholds – Unlike static thresholds, HawkEye AI implements dynamic baselines suited to specific environments. The system defines what is “normal” behaviour by analysing login frequencies, file access patterns, and network traffic. Alerts are generated when activities exceed these baselines. Over time, the platform refines its thresholds through feedback from investigations, ensuring that false positives decrease while genuine threats are caught with precision.
- User Behaviour Analysis – Modern cybersecurity requires understanding the nuanced behaviour of users. HawkEye AI builds profiles on these based on several factors some of which are –
- Login times and locations.
- Frequency of system access.
- Types of files and applications accessed.
Deviations from these norms are flagged for review, enabling SOC teams to identify insider threats, compromised accounts, or unauthorized activities.
3. Detection Use Cases for Real-World Threats – HawkEye AI addresses different of real-world challenges with defined detection use cases –
- Geo-Anomaly Detection – HawkAI identifies logins from regions outside a user’s typical geography by analysing login locations. For instance, if a user who normally logs in from Dubai suddenly accesses the system from Europe, HawkEye flags this as suspicious, prompting immediate investigation.
- RDP Login Monitoring – Remote Desktop Protocol (RDP) remains a popular target for attackers. HawkEye tracks logins by analysing usernames, IP addresses, and logon methods. Anomalies, such as logins from untrusted IPs or unusual hours, are flagged, helping SOC teams mitigate brute force attacks or lateral movement attempts.
- Traffic to Anomalous Services – The platform examines outbound network connections to detect unusual communications. For example, if a device within the network connects to an unknown external service or uses a non-standard port, HawkAI identifies the activity as potentially malicious, such as data exfiltration or command-and-control communications.
4. Advanced Azure and DNS Monitoring – HawkEye AI also specializes in addressing challenges unique to cloud environments and DNS-level threats in the following areas –
- Azure Active Directory Monitoring – The platform scrutinizes administrative and user activities within Azure AD. Anomalies are detected when operations deviate from a user’s role or typical behaviour. For instance, if a user suddenly escalates privileges or modifies critical configurations, the system flags this for further investigation.
- DNS-Based Threat Detection – HawkEye incorporates sophisticated mechanisms to detect Domain Generation Algorithm (DGA) activity. DGAs, commonly used by malware, generate seemingly random domain names to evade detection. HawkEye uses deep learning to identify patterns that indicate malicious intent, enhancing protection against advanced persistent threats.
5. Reducing False Positives for Efficient Operations
One of the standout advantages of HawkEye AI is its ability to minimize false positives. Traditional systems often overwhelm analysts with non-critical alerts, leading to fatigue and oversight. HawkAI’s iterative approach ensures that –
- Thresholds are optimized based on real-world feedback.
- Alerts are prioritized by severity, enabling analysts to focus on high-risk incidents.
- Continuous learning keeps the system aligned with evolving threats.
This focus on operational efficiency ensures that SOC teams can respond effectively to genuine threats without being bogged down by noise.
Built on Industry Standard - MITRE ATT&CK Framework
HawkEye AI aligns its detection rules with the widely recognized MITRE ATT&CK framework. By mapping tactics and techniques such as Credential Access, Initial Access, and Lateral Movement, the platform ensures comprehensive threat coverage. This alignment helps organizations adopt standardized responses and improves incident management workflows.
In Conclusion
Unlike generic solutions, HawkEye AI is tailored to the unique needs of modern SOCs. With features such as behaviour profiling, anomaly detection, and real-time alerts, it provides a robust defence against both common and sophisticated threats. By integrating AI and machine learning, the platform delivers actionable insights that empower organizations to secure their digital ecosystems effectively.
Cybersecurity is not just about responding to threats—it’s about staying ahead of them. With HawkEye AI, your organization can build a proactive defence system that minimizes risks and maximizes efficiency. Explore HawkEye AI today and connect with DTS Solution at [email protected].