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.

Ruflo MCP Flaw Lets Unauthenticated Attackers Run Commands and Poison AI Memory

What Happened

Cybersecurity researchers have flagged a maximum-severity security flaw in Ruflo, an open-source agent meta-harness for Anthropic Claude Code and OpenAI Codex, that could result in unauthenticated remote code execution. The vulnerability, tracked as CVE-2026-59726 (CVSS score: 10.0), impacts all versions of the project before version 3.16.3. It has been codenamed RufRoot by Noma Security's

Why It Matters

The article reports a critical unauthenticated remote code execution flaw (CVE-2026-59726, CVSS 10.0) in Ruflo, an open-source agent meta-harness for Claude Code and Codex, where the default MCP bridge deployment exposed POST /mcp endpoints without authentication and bound them to all network interfaces, enabling arbitrary command execution, provider API key theft, conversation access, and AI memory poisoning on any network-reachable instance.[1][2][3][4][5][6] Project maintainers fixed the issue in version 3.16.3 by binding the MCP bridge to loopback by default, adding bearer-token authentication, gating terminal execution, and enabling MongoDB authentication, but affected operators must still firewall exposed ports, rotate keys, and audit memory and data stores for prior tampering.[1][4][5] From a RealGround perspective, this is a high-severity AI supply chain exposure: Ruflo sits in the agent orchestration layer and inherits broader MCP architectural weaknesses, meaning multiple downstream AI systems using Ruflo or similar MCP-based tooling can be compromised through one library misconfiguration.[5][8] Organizations need systematic SBOM-driven inventory and hardening of MCP-base

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://thehackernews.com/2026/07/ruflo-mcp-flaw-lets-unauthenticated.html