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.

What the Data Says About AI in Security Operations in 2026

What Happened

AI is officially mainstream in security operations. According to Prophet Security's State of AI in Security Operations 2026 report (produced from ViB’s survey of 250+ cybersecurity pros), 40% of security teams now use AI daily. Another 56% are currently testing it out, and only 4% have no plans to adopt it. For the teams already using AI, what is actually changing? Here are the ten biggest

Why It Matters

The Prophet Security State of AI in Security Operations 2026 report, based on a survey of 250+ cybersecurity professionals, finds that 40% of security teams use AI daily, 56% are testing it, and only 4% have no plans to adopt AI. These data points indicate that AI has become mainstream in security operations and is rapidly approaching near-universal adoption. From a RealGround perspective, this scale of adoption increases the urgency of formal AI governance, clear policies, and readiness assessments to ensure AI-driven security workflows are compliant, auditable, and aligned with organizational risk appetite. Organizations should proactively define roles, controls, and monitoring around AI in SOC environments before usage outpaces governance.

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/2026/08/what-data-says-about-ai-in-security.html