Gurucul AI-IRM: Detect Insider Threats Faster
▼ Summary
– Gurucul launched its AI Insider Risk Management (AI-IRM) product to automate and enhance insider threat detection and response workflows.
– Organizations face rising insider threats, with 83% reporting at least one insider attack in the past year according to a 2024 report.
– The product addresses challenges like siloed tools and noisy alerts by combining UEBA, identity analytics, intelligent DLP, and automated response.
– Key capabilities include reducing insider risk by over 50%, accelerating triage and remediation, and providing real-time data loss prevention.
– AI-IRM ensures compliance with regulations like GDPR and NIST 2, and offers comprehensive coverage across human and non-human threats.
Gurucul has introduced its AI Insider Risk Management (AI-IRM) platform, a solution designed to accelerate the detection and response to insider threats through autonomous triage, bias-free risk scoring, and context-rich investigation. This system integrates human-AI collaboration to automate response workflows directly within insider risk operations, addressing a critical need as organizations report a sharp increase in threats originating from employees, contractors, third parties, and even non-human entities like AI agents.
Recent data underscores the urgency: 83% of organizations experienced at least one insider attack in the past year, according to the 2024 Insider Threat Report by Cybersecurity Insiders. Many security teams have struggled with fragmented tools, excessive alerts, and slow response times due to resource and process limitations. Gurucul’s platform aims to resolve these issues by unifying User and Entity Behavior Analytics (UEBA), identity and access analytics, intelligent data loss prevention, and native automated response (SOAR) into a single, cohesive system.
Saryu Nayyar, Gurucul’s CEO, emphasized that the product enables teams to move beyond isolated point solutions. “Our AI-Insider Analyst transforms detection and response by automating alert triage and enabling human collaboration,” she stated. “This allows organizations to leverage an expansive use case library for Day 0 coverage, freeing analysts to focus on high-risk investigations.”
Gurucul’s AI-IRM platform offers significant advantages for managing insider risk. The system is designed to reduce this risk by over 50% using AI-driven identity analytics and privileged access intelligence.
According to Gurucul’s CTO, Nilesh Dherange, a key strength of the platform is its transparency. He noted, “Our AI-Insider Analyst is trained on contextualized data and continuously improved through historical cases and human feedback. This ensures bias-free, reliable outcomes.”
The platform’s features are extensive, including prebuilt detection models, broad use case coverage, and flexible data ingestion. It combines advanced UEBA (User and Entity Behavior Analytics) with user activity monitoring. The system also supports natural language search, the development of custom detections, and automated response playbooks. Its lightweight, agentless architecture simplifies deployment, and location trust services help pinpoint unauthorized access attempts with high accuracy.
Gurucul AI-IRM is built to function in any data lake or cloud environment, such as Snowflake, AWS, and Azure, allowing companies to maintain full control over their data and deployment strategy. By bringing together behavioral analytics, identity intelligence, and automated response, Gurucul is setting a new standard in insider risk management, giving organizations the tools to detect and contain threats quickly and precisely.
(Source: HelpNet Security)
