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.

Shai-Hulud's Reach Just Grew to 469 Credential Locations. Here's What That Means

What Happened

In early August, GitGuardian researchers found that a recent Shai-Hulud infostealer worm variant had evolved to scan for credentials across 469 locations across developer environments, Continuous Integration/Continuous Deployment (CI/CD) tooling, cloud configurations, and even AI tool configs. Earlier variants of the infostealer worm only checked 189 paths. The jump says a lot. Attackers have

Why It Matters

The report says a Shai-Hulud infostealer worm variant expanded its credential scanning from 189 to 469 locations, including developer environments, CI/CD tooling, cloud configurations, and AI tool configs. That is a factual indicator of broader credential exposure risk across software and AI-adjacent operational surfaces. RealGround analysis: this is primarily a data leakage and secrets-hygiene issue, with practical implications for secret inventory, environment scanning, access control review, and continuous detection of exposed AI-related configuration files.

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/shai-huluds-reach-just-grew-to-469.html