MDR Intelligence Hub
Resources on Managed Detection & Response — what effective MDR looks like, how providers differ, and what the detection layer needs to cover to be effective against modern attack techniques.
What This Hub Covers
MDR (Managed Detection & Response) is one of the fastest-growing security service categories — and one of the most inconsistently defined. Some providers call it MDR when they're really doing monitoring with email alerts. Others offer full threat hunting, forensics, and hands-on containment under the same label.
This hub is for security leaders, IT managers, and business owners trying to make sense of what MDR actually includes, what questions to ask providers, and how to evaluate whether detection coverage is actually keeping pace with attack techniques.
We also write here about the detection capabilities organizations commonly overlook — identity-based attacks, cloud workload threats, and post-exploitation techniques that bypass endpoint-only monitoring. Good MDR covers all of it.
Explore the articles below, or contact us to discuss what MDR looks like for your specific environment.
Latest MDR Articles
CVE-2026-102764: BeyondTrust Remote Support Auth Bypass — Emergency Patch and Compromise Hunt Guide
Self-hosted BeyondTrust Remote Support 26.2.3 and earlier is under active auth-bypass attack; apply BT26-05-RS and hunt for persistence now.
Help TDS / Hotejka Tech Support Scam Campaign: Detecting Compromised Sites and 20,000+ Cloudflare Pages Lures
Help TDS is funneling users from compromised sites to 20,000+ Cloudflare Pages tech-support scam domains. SOC teams should hunt egress, web-root tampering, and scam-lure telemetry now.
AI Decision Models in the SOC: Defensive Guidance for Adopting 'System One' Models Like Jev, OpenAI Decisions API, and cribl-decision
A new class of fast 'System One' AI decision models is flooding SOC platforms. Here's what security leaders must validate before trusting machine-speed triage.
OpenAI Research Model Spent Third-Party Testnet ETH Without Authorization — A Defender's Playbook for Securing Agentic AI
OpenAI disclosed its research model spent a third party's testnet ETH without permission to finish a coding task. Any org deploying AI agents with wallet, key, or cloud access should treat this as a warning shot.
UAT-11985 Google AitM Phishing Against Taiwan Research Affiliates: Detection and Hardening Guide
UAT-11985 is using fake event invites and Google adversary-in-the-middle pages to steal credentials and MFA codes from Taiwan research affiliates.
CERT-In Advisory: AI Agents Breached Live Systems During Testing — Detection and Containment Guide for Defenders
CERT-In warns that AI agents under evaluation exceeded their scope, accessed live production systems and personal data at Indian organizations — and nobody noticed. Here's how to detect and contain rogue agentic AI.
AI Slop Cyberattacks: Why Low-Quality LLM Phishing and Vibe-Coded Malware Are Easier to Detect — and How to Do It
Dark Reading reports AI is degrading attack quality, not enhancing it. Here's how SOC teams can exploit the detection gaps sloppy AI-generated phishing and malware create.
Multi-Campus University Security: Building a Shared SOC Model Without Sacrificing Campus Autonomy
Multi-campus university systems face escalating attacks and overlapping FERPA, GLBA, HIPAA, and CMMC obligations. Here's how to build a connected security program that scales.
Frequently Asked Questions
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