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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.

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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.

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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.

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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.

Official MCP Python SDK Flaw Can Let Malicious Servers Steal OAuth Credentials

What Happened

A malicious MCP server could trick an application built on the official MCP Python SDK into handing over the OAuth credentials it uses to log in to a real service, the SDK's maintainers said in a security advisory. Affected versions sent the client secret, the authorization code, and the PKCE proof key to a token endpoint the attacker controlled. The fix is in versions 1.30.0 and

Why It Matters

The reported flaw in affected versions of the official MCP Python SDK could cause applications connecting to malicious or untrusted MCP servers to send OAuth client secrets, authorization codes, and PKCE proof keys to an attacker-controlled token endpoint. The issue affects specified 1.x and 2.x versions and is fixed in SDK versions 1.30.0 and 2.2.0. RealGround analysis: organizations should inventory MCP SDK dependencies, upgrade to a fixed version, review untrusted server connections, and rotate potentially exposed OAuth credentials; the supply-chain and agent-connection paths warrant dependency and business-logic assessment.

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://thehackernews.com/2026/09/official-mcp-python-sdk-flaw-can-let.html