Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

How the MOD can reduce investigation fatigue and boost operational efficiency Security analysts at the UK Ministry of Defence (MOD) — and everywhere — face an overwhelming challenge: They can receive thousands of alerts daily, and distinguishing genuine threats from false positives in a timely fashion has become nearly impossible without technological intervention.

AI as a force multiplier for cyber resilience in defence Military leaders are well-acquainted with the expansion of conventional warfare into digital battlefields. The recent attack and breach of a UK Ministry of Defence (MoD) supplier exposed data of 270,000 service personnel,1 representing not an isolated incident but a pattern in an escalating cyber conflict.

Cyber threats (also known as cybersecurity threats) are events, actions, or circumstances that have the potential to negatively impact an individual or an organization by taking advantage of security vulnerabilities. Cyber threats can affect the confidentiality, integrity, or availability of data, systems, operations, or people’s digital presence.

Artificial intelligence is rewriting the rules for cybersecurity on both sides of the battle. Cloud adoption, a broadening attack surface, and AI-fueled cyber threats are driving organizations to rethink their approach to security. Discussions on the best way to adapt to a highly dynamic threat environment will naturally steer toward updating SIEM, as it is core to today’s security operations.

Elastic’s piped query language, ES|QL, brings joins to the party Threat hunters rejoice! Have you been looking for a way to join data with the speed and power of Elastic? Well, we heard you! Elastic can now join data sources with a new function for the piped query language, ES|QL (Elasticsearch Query Language). This will enable robust searches that range from advanced behavior detections to alert triage and of course, threat hunting.

Financial services can’t rely on manual review alone. Discover how unified data and explainable AI are helping firms detect risk, reduce cost, and stay ahead of evolving regulations. Financial services organizations are drowning in data. From emails and Bloomberg chats to WhatsApp messages and calls, the need to review communications data to detect potential misconduct and financial crime by employees and third parties is a mandated regulatory requirement for compliance and risk teams in 2025.

The 2025 State of Detection Engineering at Elastic explores how we create, maintain, and assess our SIEM and EDR rulesets. Today, Elastic Security Labs is releasing the 2025 State of Detection Engineering at Elastic! This brand new report is the first of its kind — we’re pulling back the curtain on our Detection Engineering practices, going beyond the traditional survey-style State of Detection Engineering report.

When an EDR tool generates too much endpoint telemetry, security teams quickly run into problems. Mountains of process events, network connections, and file operations can overwhelm analysts, making it harder to spot real threats in the noise. High data volumes drive up storage costs, slow down searches, and contribute to alert fatigue — leading to longer investigation times and potential blind spots.

A guide to aligning with SEBI’s CSCRF using Elastic's integrated security and observability capabilities Financial institutions in India are preparing for a new era of cybersecurity compliance with the Securities and Exchange Board of India’s (SEBI) Cybersecurity and Cyber Resilience Framework (CSCRF).