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.

250,000 Impacted by Data Breaches at New Jersey, Texas Healthcare Firms

What Happened

Hackers stole patient information from Clover Health Investments and AngMar Management Services in July. The post 250,000 Impacted by Data Breaches at New Jersey, Texas Healthcare Firms appeared first on SecurityWeek .

Why It Matters

SecurityWeek reports that separate July 2026 breaches at Clover Health Investments and AngMar Management Services exposed or stole personally identifiable and protected health information affecting more than 250,000 people, including medical and insurance data. The report describes social engineering that compromised three Clover employee accounts and unauthorized access at AngMar. RealGround analysis: although no AI system is identified, healthcare organizations handling sensitive patient data should assess AI-related data flows, access controls, governance, and incident readiness.

Healthcare Fintech SaaS SMB AI startups

RealGround Analysis

This signal maps to healthcare AI risk. 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.securityweek.com/250000-impacted-by-data-breaches-at-new-jersey-texas-healthcare-firms/