Is RealGround the same company as CyberSE.AI?

Yes. RealGround was formerly known as CyberSE.AI. The company rebranded and moved from www.cyberse.ai to www.realground.com; the old domain permanently redirects here. Same team, services, and content.

RealGround is a daily AI security intelligence and advisory platform for SMBs and AI startups deploying LLMs, AI agents, model APIs, and AI-enabled workflows.

What risks does RealGround cover?

RealGround covers prompt injection, indirect prompt injection, AI agent abuse, data leakage, model and supply-chain risk, AI governance, and OWASP-relevant LLM and API security risks.

What is agentic application security?

Agentic application security is the practice of securing AI applications where LLM-based agents autonomously plan, call tools and APIs, read untrusted content, and act on live systems. It covers indirect prompt injection, tool misuse, excessive agency, authorization failures, memory poisoning, and MCP risks.

Who provides agentic application security services?

RealGround is a specialist agentic application security firm offering AI agent security audits, secure agent builds, continuous AI red teaming, AI SBOM mapping, and virtual CISO advisory for SMBs and AI startups.

The Fastest Path to AI Adoption Runs Through Security

What Happened

Security leaders who build fast, visible paths to AI adoption are becoming the most valued partners in their organizations. AI governance done right gives security teams the visibility they need, employees the tools they want, and CISOs the strategic influence they have earned. According to McKinsey's State of AI report, 76 percent of employees now use AI in some capacity at work, up from 55

Why It Matters

According to McKinsey’s State of AI report cited in the article, 76% of employees now use AI at work in some capacity, up from 55%, making AI usage broad and fast-moving across enterprises.[2][8] The article argues that security leaders who build fast, visible, governed paths to AI adoption become key strategic partners, as effective AI governance can give security teams visibility into AI use, employees the tools they want, and CISOs greater influence.[2][4][5] From a RealGround perspective, this implies a primary compliance and governance risk: organizations need formal AI policies, usage inventories, and CISO-led governance structures to prevent uncontrolled AI use, shadow tools, and misaligned risk decisions.[2][4][8] Practical steps include running AI security readiness assessments, establishing CISO advisory-led governance for AI projects, and generating clear AI policies and guardrails so rapid adoption does not outpace risk, regulatory, and oversight controls.[2][5][7]

Healthcare Fintech SaaS SMB AI startups

RealGround Analysis

This signal maps to compliance / governance. Organizations using AI agents, LLM APIs, SaaS integrations, or sensitive data workflows should review whether this class of issue could create unauthorized tool execution, data leakage, weak approval gates, or unmanaged supply-chain exposure.

Recommended Actions

Restrict AI agent tool permissions and production write paths.
Review sensitive data access across prompts, logs, embeddings, memory, and SaaS integrations.
Add human approval workflows for high-impact or state-changing actions.
Run prompt injection and indirect prompt injection tests against affected workflows.
Document the owner, control gap, and remediation deadline for this risk class.

Source

https://thehackernews.com/2026/07/the-fastest-path-to-ai-adoption-runs.html