Shrinking the IAM Attack Surface through Identity Visibility and Intelligence Platforms (IVIP)

The Fragmented State of Modern Enterprise Identity Enterprise IAM is approaching a breaking point. As organizations scale, identity becomes increasingly fragmented across thousands of applications, decentralized teams, machine identities, and autonomous systems. The result is Identity Dark Matter...

The Alert Firehose Finally Meets Its Match

Ask a cybersecurity pro about Network Detection and Response NDR and you might still hear "Noisy," "Too much data." But ask the teams running NDR that includes agentic AI capabilities and you'll hear they're actually using it to catch threats earlier, triage faster, and chase fewer false positive...

LanG -- a Governance-Aware Agentic AI Platform for Unified Security Operations

Modern Security Operations Centers struggle with alert fatigue, fragmented tooling, and limited cross-source event correlation. Challenges that current Security Information Event Management and Extended Detection and Response systems only partially address through fragmented tools. This paper...

Policy-Guided Threat Hunting: An LLM Enabled Framework with Splunk SOC Triage

With frequently evolving Advanced Persistent Threats APTs in cyberspace, traditional security solutions approaches have become inadequate for threat hunting for organizations. Moreover, SOC Security Operation Centers analysts are often overwhelmed and struggle to analyze the huge volume of logs...

6 Ways Agentic AI Changes How Systems Act and Adapt

Learn how agentic AI changes system behavior in production environments through supervised fine-tuning, structured oversight, and lifecycle governance to improve reliability, manage risk, and support accountable deployment...

Viral AI, Invisible Risks: What OpenClaw Reveals About Agentic Assistants

OpenClaw aka Clawdbot or Moltbot represents a new frontier in agentic AI: powerful, highly autonomous, and surprisingly easy to use. In this research, we examine how its capabilities compare to its predecessors’ and highlight the security risks inherent to the agentic AI paradigm...

From Triage to Threat Hunts: How AI Accelerates SecOps

If you work in security operations, the concept of the AI SOC agent is likely familiar. Early narratives promised total autonomy. Vendors seized on the idea of the "Autonomous SOC" and suggested a future where algorithms replaced analysts. That future has not arrived. We have not seen mass layoff...

Your 100 Billion Parameter Behemoth is a Liability

The "bigger is better" era of AI is hitting a wall. We are in an LLM bubble, characterized by ruinous inference costs and diminishing returns. The future belongs to Agentic AI powered by specialized Small Language Models SLMs. Think of it as a shift from hiring a single expensive genius to runnin...

A Survey of Agentic AI and Cybersecurity: Challenges, Opportunities and Use-Case Prototypes

Agentic AI marks an important transition from single-step generative models to systems capable of reasoning, planning, acting, and adapting over long-lasting tasks. By integrating memory, tool use, and iterative decision cycles, these systems enable continuous, autonomous workflows in real-world...

Toward Trustworthy Agentic AI: A Multimodal Framework for Preventing Prompt Injection Attacks

Powerful autonomous systems, which reason, plan, and converse using and between numerous tools and agents, are made possible by Large Language Models LLMs, Vision-Language Models VLMs, and new agentic AI systems, like LangChain and GraphChain. Nevertheless, this agentic environment increases the...

Aembit Introduces Identity and Access Management for Agentic AI

Silver Spring, USA/ Maryland, 30th October 2025, CyberNewsWire...

The State of Agentic AI: Disrupting Publishing and Reshaping Ecommerce

Learn how agentic AI is transforming how users and automation interact with the web — changing how people shop, search, and consume content...

AgentCyTE: Leveraging Agentic AI to Generate Cybersecurity Training and Experimentation Scenarios

Designing realistic and adaptive networked threat scenarios remains a core challenge in cybersecurity research and training, still requiring substantial manual effort. While large language models LLMs show promise for automated synthesis, unconstrained generation often yields configurations that...

Securing AI to Benefit from AI

Artificial intelligence AI holds tremendous promise for improving cyber defense and making the lives of security practitioners easier. It can help teams cut through alert fatigue, spot patterns faster, and bring a level of scale that human analysts alone can't match. But realizing that potential...

Agentic AI’s OODA Loop Problem

The OODA loop --for observe, orient, decide, act--is a framework to understand decision-making in adversarial situations. We apply the same framework to artificial intelligence agents, who have to make their decisions with untrustworthy observations and orientation. To solve this problem, we need...

Zero Trust + AI: Privacy in the Age of Agentic AI

We used to think of privacy as a perimeter problem: about walls and locks, permissions, and policies. But in a world where artificial agents are becoming autonomous actors — interacting with data, systems, and humans without constant oversight — privacy is no longer about control. It's about trus...

A Novel Zero-Trust Identity Framework for Agentic AI: Decentralized Authentication and Fine-Grained Access Control

Traditional Identity and Access Management IAM systems, primarily designed for human users or static machine identities via protocols such as OAuth, OpenID Connect OIDC, and SAML, prove fundamentally inadequate for the dynamic, interdependent, and often ephemeral nature of AI agents operating at...