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Prompt injection is when hidden instructions hijack an AI's behavior. Here's how it works, the main types, real examples, and how enterprises stop it.

ORION Security's Data Loss Threat Model maps how sensitive data can move and leave an organization, from traditional DLP paths to AI-native ones like MCP and shadow AI.

Agentic DLP works by reading the intent behind every data movement and producing a verdict, not an alert, then acting before data leaves

Agentic DLP vs. legacy DLP comes down to the engine. See the same data movements handled by each, and what changes for your security team.

DLP for AI agents watches the data an agent reads, carries, and sends, and stops sensitive content from leaving before it reaches an external model or service.

The ORION and Torq integration brings AI-native DLP alerts directly into SOAR workflows, giving security teams the context they need to automate response without manual triage.

The acceleration of AI requires a new data loss prevention playbook, said CISOs at the Gartner Cybersecurity & Risk Management Summit.

DLP for ChatGPT stops sensitive data from leaving in a prompt before it reaches OpenAI, and lets teams keep using ChatGPT safely across the enterprise.

Agentic DLP is data loss prevention run by autonomous AI agents that read intent and context, then act before data leaves.

There's a 'DLP Reset' underway, according to new, independent cybersecurity research. Jonathan Kreiner explains how ORION Security was built to lead this transformation.

Agentic DLP classifies data in motion from day one, eliminating the need to spend months getting DSPM in place first.

Cybersecurity analyst Lawrence Pingree shares new research on the DLP reset at an ORION Security webinar.

AI is changing how data leaks. We built a framework that helps security teams map risks, test controls, and protect data across AI systems.

ORION and Grip Security join forces to secure sensitive data across SaaS and AI ecosystems with identity context and real-time data loss prevention.

AI data exfiltration dominates security headlines, but the biggest DLP risks may still be the oldest ones - because they were never solved.

Why policy-based DLP fails in the age of Shadow AI. Discover modern, AI-driven data protection strategies built for generative AI workflows.

Learn why DSPM or DLP alone isn’t enough for AI and SaaS security. Discover how Sentra and ORION deliver end-to-end, context-aware data protection.

ORION Security closes $32M in funding to build autonomous, AI-powered DLP that replaces policies with real-time contextual data loss prevention.

The three biggest hazards of data loss are human error, insider risk, and malicious actors. Learn why most DLP tools fail to stop them, and how intent-awareness can help organizations prevent breaches without slowing down employees.

Deepfake remote workers blur insider and external threats. Learn how AI-driven, contextual DLP can stop data exfiltration before damage is done.

Learn how ORION replaces static DLP policies with automated data loss indicators to detect intent, prevent exfiltration, and reduce false positives at scale.

Learn how ORION replaces static DLP policies with automated data loss indicators to detect intent, prevent exfiltration, and reduce false positives at scale.