Curated cybersecurity insights, opinions, emerging technologies, AI security topics, and notable industry discussions.
1292 articles
The article examines AI-enabled attacks, supply-chain risks, quantum threats to encryption, and geopolitical cyber activity, with practical recommendations for strengthening organizational resilience.
Skycloak founder Guilliano Molaire explains how organizations can map hidden dependencies across vendors and reduce concentration risk through contract protections and architecture changes.
The guide outlines enterprise controls for AI-agent identities, including named owners, short-lived credentials, task-scoped authorization, runtime monitoring, and revocation. It emphasizes discovering activity across applications and infrastructure, beyond conventional
Huntress describes Athena, a system of more than 40 AI agents that investigates security signals, prepares reports, and escalates uncertain cases to human analysts. The company reports faster report generation and improved report quality.
The post questions whether frontier AI developers can manage the risks of AI models in the wild if they cannot secure them during testing.
Gen Digital’s cybersecurity perspective argues that malicious users—not autonomous intent—are AI’s main danger, as AI scales fraud and cyberattacks. It also warns of agent risks and failures, and calls for constrained access, oversight and independent testing.
The author says tests have shown frontier AI models escaping secured sandboxes and argues AI companies should invest in cybersecurity leadership, staff, tools, and capabilities to manage emerging risks.
Cyble argues that rapidly changing cloud environments make quarterly or annual external scans too outdated to catch newly exposed assets, and recommends continuous discovery, monitoring, prioritization, and remediation workflows.
Vectorize CEO Chris Latimer warns that AI agent memory can retain credentials and sensitive documents in plain text. He describes poisoning risks through plugins, skills, and MCP integrations, and recommends auditing agent memory for unvetted tools and exposed secrets.
A vendor-authored guide outlines how to assess insider risk platforms, emphasizing broad activity visibility, behavioral and rules-based detection, privacy controls, investigation evidence, AI-use monitoring, real-time intervention, scalability and operating costs.
The article argues that AI agent security should start with discovery and continuous monitoring. It describes visibility gaps across cloud, network, endpoint, browser, and SaaS environments, and recommends distinct identities, scoped permissions, and audit trails for AI
Unit 42 consultants argue that effective security depends on managing existing tools well, preparing smaller organizations for attacks, and treating security controls and GRC as active risk mitigation rather than paperwork.
AI can make failed intrusion attempts faster and cheaper to retry. The article argues that SOCs should preserve evidence, reasoning, uncertainty, constraints, and lessons across handoffs to reduce investigation delays and improve response.
Securonix describes combining UEBA baselines, cross-system activity correlation and an Insider Intent Agent to contextualize insider-risk signals, including AI use, with governed, human-supervised investigation workflows.
A Windows 10 walkthrough shows how attackers can abuse a misassigned SeManageVolumePrivilege to change C:\Windows permissions and escalate privileges through DLL hijacking. It also outlines monitoring and mitigation measures.
The author argues that AI is changing entry-level cybersecurity tasks, not eliminating the need for security professionals. Routine work may be automated, while fundamentals, contextual judgment, and responsibility remain essential.
An explainer on how weaknesses in telecom signaling, internet routing, and network routers can enable surveillance and persistent intrusions, and outlines defenses including SS7 firewalls, RPKI validation, and router audits.
An explainer on how AI is speeding up and scaling cyberattacks, with examples of agentic operations, pressure on vulnerability patching, and guidance for validating security controls.
Sponsored analysis argues that AI agents can evade the assumptions behind SOC 2 controls, obscuring ownership, authorization, activity, and offboarding. It recommends treating machine accounts as users and aligning agent access with intended tasks.
The article explains how regular CISO-CFO collaboration can align security investment with financial risk, strengthen controls over financial systems, and improve incident readiness. It recommends business-focused communication, shared planning, and clear governance.
Trend Micro CEO Eva Chen argues that AI agents can be made safer by governing their actions with cybersecurity measures such as authentication, permission controls, isolation, monitoring, testing, and stop gates.
Matthew Rosenquist argues that AI is making cyberattacks faster and more convincing, and that organizations must strengthen technology, people, and processes to keep pace.
The op-ed argues that federal tax incentives and clearer Section 174A guidance could help cash-strapped state and local governments invest in cybersecurity for critical infrastructure, citing threats to water systems and other public services.
The article argues that agentic AI could automate the remediation stage of continuous threat exposure management, recommending risk-based human oversight, constrained actions, rollback plans, standardized approvals, and failure rehearsals.
