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Tag: machine

Manage machine identities: The hidden privileged access layer you need to manage

Why are machine identities becoming the majority of “things with access”? Every automation, integration, and workload needs a way to authenticate and the right permissions to act. That quiet requirement has created a massive population of machine identities, also called non-human identities (NHIs): service accounts, service principals, workload roles, OAuth apps, AI agents, and IAM…

When Identity is the Attack Path

Consider a cached access key on a single Windows machine. It got there the way most cached credentials do – a user logged in, and the key stored itself automatically. Standard AWS behavior. No one misconfigured anything or violated a policy. Yet that single key, which was easily accessible to a minor-league attacker, could have…

SHARED INTEL Q&A: PKI’s unfinished business—’digital passports’ for content, models and agents

As if keeping track of machine identities wasn’t hard enough. AI agents are now arriving by the thousands — and most enterprises are just handing them borrowed credentials and hoping for the best. Meanwhile, the cryptographic infrastructure asked to absorb these threats faces a hard regulatory countdown requiring digital certificates — the credentials securing every…

Sevii unveils Cyber Swarm Defense Mode to stop AI-driven attacks at scale

Sevii has unveiled a new capability designed to stop high-volume, AI-powered cyberattacks at machine speed and scale, without the burden of unpredictable AI token costs. Sevii’s Cyber Swarm Defense Mode (CSD) addresses a critical gap created by AI, namely the inability to sustain cyber performance and cost efficiency during large-scale, AI-driven attack swarms. As technologies…

How Phishing Is Targeting Germany’s Economy: Active Threats from Finance to Manufacturing

Germany’s economy is a precision machine: finance fuels it, manufacturing builds it, telecom connects it, IT optimizes it, and healthcare sustains it. The country sits at the crossroads of industrial power and digital transformation, making it irresistibly attractive to attackers. In this article, we explore real-world attacks targeting five critical German industries, analyzed by ANY.RUN’s analysts using Interactive…

Malware detectors trained on one dataset often stumble on another

Machine learning models built to catch malware on Windows systems are typically evaluated on data that closely resembles their training set. In practice, the malware arriving on enterprise endpoints looks different, comes from different sources, and in many cases has been deliberately obfuscated to evade detection. A study from researchers at the Polytechnic of Porto…

Llamafile, Mozilla’s portable LLM runner, gets GPU support and a rebuilt core

Running a large language model on a single machine without cloud access or a container runtime remains a priority for practitioners working in air-gapped or resource-constrained environments. Llamafile, Mozilla-AI’s project for packaging and running LLMs as self-contained executables, has received its most significant architectural overhaul to date with version 0.10.0. A rebuild from the ground…

5 trends that should top CISO’s RSA 2026 agendas

RSA 2026 is still weeks away and the hype machine is humming. This year’s theme, “The Power of Community,” is somewhat ironic as the overwhelming chatter at the Moscone Center in San Francisco from March 23 to March 26 will be about AI agents, not humans. Welcome to the cybersecurity community, agents, automatons, and robots!…

Implementing data governance on AWS: Automation, tagging, and lifecycle strategy – Part 1

Generative AI and machine learning workloads create massive amounts of data. Organizations need data governance to manage this growth and stay compliant. While data governance isn’t a new concept, recent studies highlight a concerning gap: a Gartner study of 300 IT executives revealed that only 60% of organizations have implemented a data governance strategy, with…

Implementing data governance on AWS: Automation, tagging, and lifecycle strategy – Part 1

Generative AI and machine learning workloads create massive amounts of data. Organizations need data governance to manage this growth and stay compliant. While data governance isn’t a new concept, recent studies highlight a concerning gap: a Gartner study of 300 IT executives revealed that only 60% of organizations have implemented a data governance strategy, with…

Implementing data governance on AWS: Automation, tagging, and lifecycle strategy – Part 1

Generative AI and machine learning workloads create massive amounts of data. Organizations need data governance to manage this growth and stay compliant. While data governance isn’t a new concept, recent studies highlight a concerning gap: a Gartner study of 300 IT executives revealed that only 60% of organizations have implemented a data governance strategy, with…

Implementing data governance on AWS: Automation, tagging, and lifecycle strategy – Part 1

Generative AI and machine learning workloads create massive amounts of data. Organizations need data governance to manage this growth and stay compliant. While data governance isn’t a new concept, recent studies highlight a concerning gap: a Gartner study of 300 IT executives revealed that only 60% of organizations have implemented a data governance strategy, with…