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.

Meta's New AI Image Tool Lets Others Use Your Public Instagram Photos in AI Images

What Happened

Meta has announced that its new artificial intelligence (AI) model Muse Image lets people use public Instagram posts and reels to generate AI content, and it's enabled by default. "You can also @-mention Instagram accounts in the Meta AI app to bring specific Instagram profiles right into your images," the social media giant said in a post. "Whether you want to design a custom event invitation

Why It Matters

The article reports that Meta’s Muse Image generative AI model can use any public Instagram user’s posts, reels, and profile photos in AI-generated images by @-mentioning their account, with participation enabled by default unless users actively opt out via buried “Sharing and reuse” settings.[1][2][4] Users are not notified when their content is reused and previously generated AI images remain even after opting out, raising privacy, consent, and reputational concerns.[1][2][4] From a RealGround perspective, this reflects a significant training data and content-reuse governance risk: organizations need clear AI policies on how their brand assets, employee photos, and customer-facing content may be ingested or remixed by external AI platforms, including opt-out procedures and communication to staff and marketing teams. Robust AI data governance and policy frameworks can help prevent unintended exposure of corporate or employee imagery to third‑party generative AI systems and support compliance with emerging privacy and consent regulations.

Healthcare Fintech SaaS SMB AI startups

RealGround Analysis

This signal maps to training data 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://thehackernews.com/2026/07/metas-new-ai-image-tool-lets-others-use.html