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.

Clean GitHub Repo Tricks AI Coding Agents into Running Malware

What Happened

Agentic Threat Tracker reports a vulnerability (CVE-2026-10591) in AWS Kiro, an agentic IDE, where hidden prompt injection instructions in web pages or source files allowed attackers to rewrite Kiro's MCP server configuration or allowlist arbitrary Bash commands, leading to arbitrary code execution on developers' machines without approval prompts.[9] The same feed details a supply chain attack where trojanized LiteLLM releases on PyPI exfiltrated model API keys, cloud access keys, SSH keys, and Kubernetes tokens, illustrating AI tooling and library supply chain risks for organizations relying on open-source LLM gateways.[9]

Why It Matters

According to Agentic Threat Tracker, CVE-2026-10591 in AWS Kiro, an agentic IDE, allowed hidden prompt injection instructions in web pages or source files to rewrite Kiro's MCP server configuration or allowlist arbitrary Bash commands, resulting in arbitrary code execution on developers' machines without approval prompts. The same report describes trojanized LiteLLM releases on PyPI that exfiltrated model API keys, cloud access keys, SSH keys, and Kubernetes tokens, demonstrating AI tooling and library supply chain compromise. From a RealGround perspective, these incidents highlight that autonomous or semi-autonomous AI coding agents and IDE integrations can be turned into powerful attack vectors when configuration, tool invocation, and command execution are not strictly constrained and monitored. Organizations should enforce hardened agent designs, robust business-logic and tool-usage audits, and supply chain security (including SBOM and dependency validation) for AI gateways and developer tooling to reduce the risk of silent code execution and credential exfiltration.

Healthcare Fintech SaaS SMB AI startups

RealGround Analysis

This signal maps to AI agent abuse. 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://agentic-threat-tracker.com/?itemType=incident