The cyber threat landscape is rapidly evolving, characterized by increasingly sophisticated attacks targeting a widening attack surface. In response, organizations have strengthened their security postures with multiple layers of defense, resulting in an average of 10 to more than 70 cybersecurity solutions deployed across their environments.
The consequence of this tool sprawl is a sea of alerts that is humanly impossible to triage, resulting in sub-optimal security outcomes.
To address this and thanks to breakthroughs in Large Language Model (LLM) development, AI SOC analysts are being deployed alongside human analysts in the security operations center (SOC). These AI-augmented SOCs are resulting in significantly more accurate and rapid detections and responses, resulting in improved cybersecurity resilience.
Alert Investigation Explained
Alert investigation is the process of investigating security alerts triggered by security solutions. Typically, alerts are investigated by security analysts within the SOC. Team sizes vary from one analyst to dozens, depending on the size of the organization.
These alerts emanate from endpoint, network, or email security solutions, among dozens of other solutions. By quickly responding to the alerts, organizations can prevent security breaches or minimize damages before they turn into major security incidents. The Mean Time To Detect (MTTD) and Mean Time To Respond (MTTR) are essential metrics that guide the SOC.
Different Types of Alert Investigations
There are several types of alert investigations focussed on different areas of the IT architecture and users:
- Network Alerts: Anomalous activity detected by network security solutions for eg: network intrusion.
- Endpoint Alerts: Anomalous activity detected by an endpoint security solution, for eg: malware being executed.
- Cloud Alerts: This can be triggered by a range of solutions across any one of the cloud services layers.
- Email Alerts: Anomalous activity detected on emails, for eg: Phishing
- User-behavior Alerts: Anomalous user behavior for eg: logging in from an unusual location, or mass downloads.
- Application Alerts: Anomalous application activity for eg: Creating guest user profiles with excessive privileges.
Non-AI vs AI-Augmented Alert Investigation
Traditional alert investigations rely heavily on manual processes, where security analysts sift through thousands of alerts in an attempt to identify threats. Not only is this significantly time-consuming but also riddled with false positives (with reported highs of up to 60% of alerts). This is where the analogy of finding the needle in a haystack has come to prominence. This also explains why the typical organization is only able to triage 49% of alerts in a day. With SOC teams typically understaffed, fatigue and analyst burnout are common.
In contrast, AI-powered alert investigation can quickly analyze vast amounts of data, identify patterns, and detect anomalies. With its human-in-the-loop approach and enabling analysts to query findings with natural language queries, it significantly improves triaging times—no more cumbersome scripts to run.
How Agentic AI is Being Used in Alert Investigations
AI is revolutionizing alert investigations in many ways:
- Tier 1 SOC automation: Freeing analyst time to focus on credible alerts and strategic tasks.
- Improved threat detection: Reducing false positives through continually improving anomaly detection efficacy based on historical data training.
- Behavioral-based detection: Detecting any deviation from a behavioral baseline, resulting in high-priority alerting.
- More context-rich alerting: By incorporating external threat intelligence feeds the detection efficacy improves as does the context.
- Continuous defense hardening: Cybersecurity resilience improves over time through the improvement in SOC alert investigation capabilities.
Benefits of Agentic AI in Alert Investigations
AI alert investigations offer significant advantages which include:
- Accelerated Incident Response: AI-driven automation significantly reduces MTTD and MTTR, enabling organizations to swiftly contain threats and minimize damage.
- Enhanced Threat Detection: AI can identify even subtle anomalies that humans may miss and uncover hidden threats.
- Improve SOC Productivity: Automating routine tasks frees security analysts to focus on high-value activities such as incident response, boosting overall team efficiency.
- Reduced Analyst Burnout: AI-powered alert prioritization and workload management help alleviate analyst fatigue, improve job satisfaction, and prevent attrition.
- Increased ROI on Security Investments: By enabling 100% alert coverage, AI maximizes the value of existing security solutions and delivers a higher return on security investments.
How Dropzone AI’s Alert Investigation Differs from Other AI Alert Investigation Solutions
Dropzone AI is trained to function as Tier 1 SOC analysts. Unlike other AI SOC solutions, it leverages the power of pre-trained AI security agents, performs end-to-end investigations autonomously, and presents human analysts with detailed reports. No coding or playbooks are required.
The AI agents from Dropzone AI replicate expert human analysts’ decision-making process, understand your team and company’s context, and adapt to an ever-changing threat landscape.
The outcome: Accurately investigate all security alerts faster, spot real threats quicker, and augment your human analysts to improve overall security posture.
See the case study here to learn why customers love Dropzone AI.
Agentic AI Alert Investigation FAQs
1. What types of alerts can Dropzone AI investigate?
Dropzone AI is designed to handle a wide range of security alerts. This includes
- Network security alerts
- Phishing alerts
- Endpoint security alerts
- Identity and access Management alerts
- Cloud security alerts
- Insider threat
2. How quickly can Dropzone AI process an alert investigation?
Dropzone AI is designed to significantly reduce the time it takes to investigate security alerts. While processing times can vary based on alert complexity and data volume, the platform often completes investigations within minutes. For instance, phishing investigations that typically consume 20 minutes manually can be resolved in under 5 minutes using Dropzone AI.
3. What kind of integration support does Dropzone AI provide?
Dropzone AI offers over 50+ integrations including integrations with leading cybersecurity solutions, ticketing, and data tools. Dropzone seamlessly integrates with these tools so it can tap into organization-specific data, understand context, and conclude investigations with improved precision. For a complete list of integrations, click here.
4. How does Dropzone AI ensure the accuracy of its alert investigations?
Our system was engineered with a specific focus on guardrails, explainability, and data lineage. For example, every alert conclusion is accompanied by a complete report of crucial factors and a chain of raw evidence and sources so human analysts can quickly validate the AI's logical reasoning at the click of a button.
5. What are the common outcomes of using Dropzone AI for alert investigations?
Dropzone AI reinforces your SOC with AI analysts. The common outcomes Dropzone AI customers see include:
- Reduction on MTTD
- Focus on real threats
- Reduced alert fatigue
- Free analysts for higher-value work
- Get more out of existing security tooling
If you are interested in learning more about how Dropzone AI can help streamline your SOC, request a demo today!
