In navigating the complex landscape of regulatory compliance and risk management, India's banking sector faces unique challenges, particularly in meeting directives outlined by the Reserve Bank of India (RBI) and the Indian Computer Emergency Response Team (CERT-In). As organizations strive to adhere to these stringent requirements, Elastic Observability emerges as a powerful ally, offering advanced log analytics capabilities tailored to address regulatory mandates and mitigate operational risks.

One of the biggest SIEM management problems SOC teams face is that they are often overwhelmed by false positives, leading to analyst fatigue and visibility gaps. In addition to that, one of the toughest challenges in security is detecting when SaaS access tokens are compromised without adding to the false positive problem. At Elastic, the InfoSec team tackles both of these issues by automating SIEM alert investigations with tools like Tines.

Real-world malware 100% protection with zero false positives Elastic Security has achieved remarkable results in the recent AV-Comparatives Malware Protection Test, with a protection rate of 100% and no false positives against real-world malware samples. This independent assessment underscores our commitment to providing world-class malware protection, with zero false positives and zero user impact.

From its beginning, the Elastic detection-rules repo not only contained Elastic’s prebuilt detection rules, but also additional tooling for detection rule management — like a suite of tests, CLI commands, and automation scripts used by the Elastic Threat Research and Detection Engineering (TRaDE) team.

For security analysts navigating an increasingly complex threat landscape, the ability to quickly identify and respond to attacks is critical. Security information and event management (SIEM) tools have been integral to helping security teams quickly respond to attacks. Now, in the era of generative AI, Elastic is changing the game by delivering AI-driven security analytics to replace SIEM and modernize the SOC.

Amazon Bedrock and Elastic’s Attack Discovery automate security analyst workflows As cyber threats grow increasingly sophisticated, the need for highly effective security measures becomes imperative. Traditional SIEMs aren’t equipped to address threats fast enough because they rely on too many manual and labor-intensive tasks. AI-driven security analytics from Elastic’s Search AI platform solves these challenges.

Prioritize attacks, not alerts, with new Attack Discovery capability, powered by Search AI.

In our previous installation, we discussed the history of security information and event management (SIEM) solutions — from collection to organizational detections and finally to response and orchestration. Now, we are firmly in the SIEM 3.0 revolution and focused on applying generative AI to every applicable process in the security operations center with tremendous success.

It’s vital to have a common understanding and shared context for complex technical topics. The previously adopted perimeter model of security has become outdated and inadequate. Zero Trust (ZT) is the current security model being designed and deployed across the US federal government. It’s important to point out that ZT is not a security solution itself. Instead, it’s a security methodology and framework that assumes threats exist both inside and outside of an environment.

The cybersecurity domain mirrors the physical space, with the security operations center (SOC) acting as your digital police department. Cybersecurity analysts are like the police, working to deter cybercriminals from attempting attacks on their organization or stopping them in their tracks if they try it. When an attack occurs, incident responders, akin to digital detectives, piece together clues from many different sources to determine the order and details of events before building a remediation plan.