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.

Honeywell: OT Security Teams Embrace AI, but Autonomy Still Rare

What Happened

Only 21% of industrial security leaders report a complete OT asset inventory, even as 88% call their programs mature. The post Honeywell: OT Security Teams Embrace AI, but Autonomy Still Rare appeared first on SecurityWeek .

Why It Matters

Honeywell’s 2026 OT Cybersecurity Benchmark Report found that 88% of surveyed industrial security leaders considered their OT programs mature, while only 21% reported a complete OT asset inventory. AI is already used for threat detection, monitoring, and asset inventory, but only 23% reported using autonomous or agentic AI for threat detection. The report emphasizes decision rights, human oversight, and testing for operational consequences; RealGround analysis: organizations adopting AI in OT should establish governance, inventory, approval controls, and safety-focused validation before expanding autonomous actions.

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://www.securityweek.com/honeywell-ot-security-teams-embrace-ai-but-autonomy-still-rare/