Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Segmentation Built for the Hybrid Reality

Traditional, IP‑based segmentation can’t keep up with today’s hybrid networks. In this video, learn why visibility, device identity, and risk context are essential to segmenting modern IT, OT, and IoT environments — and how Forescout is redefining segmentation for the way enterprises actually operate.

What's new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations

Security teams face a threat landscape shaped by AI-driven attacks and identity misuse. Adversaries increasingly rely on compromised identities to blend in as legitimate users, making attacks harder to detect and slower to contain. On average, organizations take 241 days to identify and contain a breach.1 While threats have evolved, legacy SIEMs have not kept pace.

Secure Jira Cloud REST API Integrations: Beyond Atlassian Native Authentication

Jira Cloud APIs are widely used for automation and integrations across CI/CD, DevOps, reporting, and internal tools. Atlassian provides native REST API authentication using API tokens and OAuth. This works well for simple scripts and internal automation. However, modern organizations often require stronger controls when APIs are used by multiple services, integrations, and automated systems. As integrations grow, teams often need a more controlled authentication model than user-based tokens alone.

How to Manage Unauthorized AI Tool Usage in Your Business

In only a few years, artificial intelligence (AI) has changed almost every aspect of life, and especially so in business. Today, employees are using generative AI tools to draft emails, code software, and analyze data at lightning speed. However, there is a hidden side to this productivity boost: unauthorized AI use. Many employees are bypassing official IT channels and using shadow AI applications to get their work done.

How to Manage Identity Sprawl in the Age of AI Agents and NHIs

Non-human identities (NHIs) and AI Agents including service accounts, CI/CD credentials and cloud workload identities, now eclipse human identities in enterprise identity systems by 50:1 to 100:1. Modern identity security platforms must assign identities to these assets and furthermore, apply roles, access control policies, visibility and governance in order to secure the modern enterprise.

Homomorphic Encryption in LLM Pipelines: Why It Fails in 2026

There’s a claim gaining traction in the market: homomorphic encryption can preserve data privacy in AI workflows. Encrypt your data, run it through a language model, and never expose a single token. Sounds bulletproof. It isn’t. Homomorphic encryption (HE) was built for math, not language. Applying it to LLM pipelines is like encrypting a book and asking someone to summarize it without reading a word. The problem isn’t efficiency.

How SA Power Networks Accelerated Threat Detection with Exabeam

The small but mighty cyber security team at SA Power Networks, the sole electricity distributor for the state of South Australia, was challenged to keep up with numerous responsibilities, including preventive controls, patch management, and detect/respond functions. After choosing and implementing Exabeam, the platform has delivered the anticipated value: streamlining and accelerating the company’s TDIR function, strengthening security team bonds and collaboration, and cementing the critical link between security and business initiatives.

Exabeam: Real Intelligence. Real Security. Real Fast.

Security teams today face machine-speed threats, growing complexity, and overwhelming data. Exabeam helps you stay ahead with powerful AI, behavioral analytics, and automation designed to accelerate threat detection, investigation, and response (TDIR). With hyper-fast search, advanced analytics, and intelligent automation, Exabeam enables security teams to uncover threats faster, reduce manual work, and gain insights other tools miss. Since 2014, we’ve put AI and machine learning at the core of security operations—helping organizations modernize their SOC and improve outcomes at scale.

BewAIre: Detecting Malicious Pull Requests at Scale with LLMs

As AI coding assistants accelerate software development, the volume of pull requests at Datadog has grown to nearly 10,000 per week, increasing the risk that malicious changes slip through due to review fatigue. To address this, Datadog built BewAIre, an LLM-powered code review system designed to identify malicious source code changes introduced by threat actors. By reducing approval fatigue for developers while increasing friction for attackers, BewAIre guides human reviewers to the areas where judgment matters most, without slowing developer velocity.