87 stories
An agentic security strategy must account for software that can act on legitimate instructions in unexpected ways. Agents can use credentials, call tools and choose their own routes toward a goal, expanding the paths security teams need to watch.
As enterprises face AI-driven cyberattacks, AI security governance must control autonomous systems that can reach data, connect applications and act on users’ behalf. That makes human accountability a core security requirement.
As director of HPE Labs, Andrew Wheeler (pictured) is uniquely positioned to observe rapid advancements in artificial intelligence and new developments for the emerging field of quantum computing.
Getting AI into production has become the real test for enterprises. As the proof-of-concept phase ends, harder questions about cost, data and control are taking its place.
Identity and access management is getting a second look as AI agents move from pilots into production. The rush to deploy them is exposing decades of stitched-together identity tools, integration costs and security gaps that enterprises can no longer ignore.
AI agent identity security is testing whether consolidated platforms can protect a growing class of machine identities. Palo Alto Networks Inc.’s acquisition of CyberArk Software Ltd. reflects broader consolidation in the identity security market. Okta Inc.
Agent runtime security requires controls across the technology stack as enterprises move AI agents into production. This week, Okta turned its agent security framework into a multivendor reference architecture through the Blueprint Alliance.
The practice of building cybersecurity directly into networks and databases has taken on greater importance in the new era of agentic AI. Trust boundaries are being relocated to the database itself, where access policies can be enforced regardless of the instructions an AI agent has received.
The enterprise artificial intelligence conversation is moving past models and compute. As companies push projects into production, the harder problem is increasingly what sits underneath them: getting distributed, messy and often sensitive enterprise data ready for systems that need reliable…
AI agent access is complicating identity controls as agents log in, carry credentials and act on someone’s behalf. They have characteristics of both human and machine users.
Agent containment is becoming a practical governance question as enterprises move AI agents into production. ServiceNow Inc. is betting that the response to a misbehaving agent must account for both risk and the business work it supports.
Qiagen N.V. is betting that drug discovery agents need a trustworthy knowledge foundation as much as capable models. For biopharma companies, that means giving agents information with clear provenance and enough context to support their answers.
Security operations teams are changing their approach in the world of artificial intelligence, adopting automation to turn signals into outcomes while maintaining the right context and control.
Knowledge graphs are moving to the center of autonomous software development as enterprises push coding agents beyond quick fixes and into large, interconnected codebases. The more code an agent touches, the more it needs to know about everything that code connects to.
As artificial intelligence matures, the security guardrails — and the computer system itself — are changing. This week, the conversation centered around agents going rogue.
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