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.

Windows, Linux, Android File Notification Systems Leak User Activity

What Happened

Researchers show that file-change notification systems can leak keystroke timing, browsing activity, and WhatsApp media events. The post Windows, Linux, Android File Notification Systems Leak User Activity appeared first on SecurityWeek .

Why It Matters

Researchers reported that file-notification mechanisms in Windows, Linux, Android, and macOS can expose file names, paths, and event timing without revealing file contents, enabling inference of keystrokes, browsing activity, and messaging events. The report does not identify an AI-specific vulnerability or exploitation of AI systems. RealGround analysis: organizations using AI applications on affected systems should assess whether local agents or other processes can observe these side channels and whether resulting metadata could expose sensitive user or workflow activity.

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.securityweek.com/windows-linux-android-file-notification-systems-leak-user-activity/