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.

SMB survival requires cybersecurity transformation with AI

What Happened

Fast Company outlines how small and midsize businesses adopting AI must strengthen basic cybersecurity, including data mapping, access controls, encryption, MFA, and incident response planning.[6] While not focused solely on LLMs, it frames AI-driven transformation as increasing exposure to data leakage and supply-chain issues through cloud and SaaS dependencies commonly used by startups and SMBs.[6]

Why It Matters

The Fast Company article explains that as SMBs adopt AI and rely more heavily on cloud and SaaS platforms, they must strengthen foundational cybersecurity controls such as data mapping, role-based access, encryption, MFA, backups, and incident response planning.[1] It highlights increased exposure to data leakage and supply-chain vulnerabilities because sensitive business data is dispersed across third-party services and AI-powered tools commonly used by startups and SMBs.[1] From a RealGround perspective, this maps directly to AI-driven data leakage risk and AI supply-chain exposure, indicating that SMBs need structured AI security readiness assessments and CISO-level advisory to inventory AI use, classify data, and enforce access, encryption, and MFA across cloud/SaaS dependencies. Practical security implications include establishing AI usage and data-handling policies, conducting vendor and SBOM-style assessments of AI and SaaS providers, and implementing tested incident response plans tailored to AI-related breaches.

Healthcare Fintech SaaS SMB AI startups

RealGround Analysis

This signal maps to data leakage. 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://www.fastcompany.com/91346052/smb-survival-requires-cybersecurity-transformation-with-ai