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.

How to Run a Deepfake Readiness Drill Before a Cloned Voice Calls Your Team

What Happened

Cloned voices and synthetic video calls now show up in payment fraud, help desk resets, and access requests. A structured drill shows security teams exactly where verification breaks down, while nothing is at stake. The call comes in at 4:40 on a Friday. It's the CFO, or it sounds exactly like her, asking the controller to push a supplier payment out before the weekend because a deal closes

Why It Matters

The report describes cloned-voice and synthetic-video impersonation scenarios targeting payment approvals, supplier bank changes, help desk resets, and access requests, and recommends tabletop exercises, live simulations, out-of-band callbacks, and strict verification thresholds. RealGround analysis: these controls can expose gaps in identity verification and authorization workflows before attackers exploit them; organizations should test high-impact requests using safe, non-production scenarios and establish executive-level response guidance.

Healthcare Fintech SaaS SMB AI startups

RealGround Analysis

This signal maps to malicious AI use. 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/2026/10/how-to-run-deepfake-readiness-drill.html