All news with #attack surface management tag

🔒 Regular network scans are no longer sufficient to secure modern environments. This article reviews a dozen Attack Surface Management solutions—covering both CAASM and EASM approaches—that automate asset discovery, continuous monitoring, and risk prioritization. Vendors highlighted include Axonius, CrowdStrike, Microsoft Defender, Palo Alto Xpanse, and others that integrate with existing SOC tooling and often leverage agentic AI to assist detection and remediation. It concludes with seven practical questions to evaluate ASM needs, automation, remediation paths, and pricing models.

🔒 Enterprises face expanding, complex attack surfaces driven by IoT growth, API ecosystems, remote work, shadow IT and multi-cloud sprawl. The author predicts 2026 will bring centralized cloud control—led by SASE—a shift to proactive, continuous ASM, stricter zero trust enforcement and widespread deployment of intelligent, agentic AI for autonomous detection and remediation. The analysis also emphasizes greater attention to third‑party and supply-chain risk.

🔒 Join a free webinar from The Hacker News and Bitdefender to learn how Dynamic Attack Surface Reduction (DASR) proactively closes exposures and reduces risk without adding operational burden. Experts will explain why traditional scans fall short, how automation and context reduce risks in real time, and how to safely test DASR in your environment. Register to save your seat.

🔗The Unified Linkage Model (ULM) reframes cyber risk by focusing on the relationships — not just individual assets — that allow vulnerabilities and adversaries to propagate across systems. Drawing on the Okta 2023 support-credential compromise, the model highlights three structural linkage types: adjacency, inheritance and trustworthiness. ULM shifts analysis from topology or isolated CVE lists to the connective tissue that enables systemic exposure. Applied correctly, it clarifies prioritization, accelerates impact analysis and unifies threat and vulnerability data into actionable risk pathways.

🔎 Cyber asset attack surface management (CAASM) and external ASM (EASM) solutions help organizations discover and continuously monitor internet-facing assets to reduce exposure and harden security. The article surveys a dozen commercial offerings — including Axonius, CrowdStrike Falcon Exposure, Microsoft Defender EASM, and Palo Alto Cortex Xpanse — highlighting discovery methods, integrations, AI features, and sample pricing. It stresses continuous monitoring, asset context and prioritization, and recommends vetting vendor automation, remediation workflows, and pricing transparency.

🔒 Modern MSSP and MDR models that focus on detection and response are increasingly insufficient as hybrid infrastructures and rapid cloud and third‑party changes expand attack surfaces. Unified Exposure Management Platforms (UEMPs) continuously discover assets, validate exploitability with automated simulations and penetration testing, and coordinate remediation to produce verifiable, business‑aligned risk reduction. Vendors like Picus Security package CTEM stages into a workflow that prioritizes, validates, and mobilizes fixes to shift security from reaction to prevention.

🔎 External Attack Surface Management (EASM) continuously discovers, inventories, and monitors internet‑facing assets — domains, subdomains, cloud workloads, IPs, and third‑party exposures — to reveal shadow IT and misconfigurations before attackers can exploit them. EASM platforms deliver automated discovery, continuous monitoring, and risk‑based prioritization so teams can focus remediation on high‑impact threats. Integrated workflows and ticketing accelerate fixes and improve cross‑team visibility.

🔒 Fortinet played a central role at Black Hat USA 2025, engaging thousands of attendees through demos, theater sessions, and partner presentations. At Booth #2446 and the Security Fabric Theater, Fortinet highlighted integrated capabilities across secure networking, SOC transformation, endpoint protection, and CNAPP, and showcased research on adversarial AI. The program extended into DEF CON 33, reinforcing the urgency of attack surface management and rapid threat detection.