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.

40,000 Impacted by SafePal Data Breach

What Happened

Hackers exploited a vulnerability in the order-tracking function of a plugin to access SafePal customer information. The post 40,000 Impacted by SafePal Data Breach appeared first on SecurityWeek .

Why It Matters

Report facts: Hackers exploited a vulnerability in the order-tracking function of a plugin used by SafePal, leading to a data breach impacting roughly 40,000 customers and exposing their information. RealGround analysis: While the incident is not explicitly described as AI-related, it highlights third-party component and plugin risks that are directly applicable to AI supply chains, where external tools, plugins, and integrations can expose sensitive user or transactional data. Organizations deploying AI systems should apply similar SBOM, dependency, and integration risk management practices to AI-related plugins and agents, including rigorous security testing and continuous assessment of third-party components.

Healthcare Fintech SaaS SMB AI startups

RealGround Analysis

This signal maps to AI supply chain. 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/40000-impacted-by-safepal-data-breach/