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.

Amazon Kiro vulnerability enabled data exfiltration through prompt injection and Kiro Powers

What Happened

Researchers disclosed a vulnerability in Amazon Kiro, an agentic AI development environment, where attacker-controlled repository content influenced the agent through prompt injection. The issue could cause sensitive local information to be transmitted to an external endpoint, according to the report.

Why It Matters

Researchers reported that attacker-controlled repository content could influence the Amazon Kiro agent through indirect prompt injection, causing it to access sensitive local information and transmit it to an external endpoint via Kiro Powers. The reported issue affected Kiro IDE 0.7.45 on Windows and was exploitable after specific user interactions, according to the report. RealGround analysis: agent permission boundaries, untrusted-content handling, tool-use controls, and outbound data-flow protections should be tested and strengthened to reduce prompt-injection-driven exfiltration.

Healthcare Fintech SaaS SMB AI startups

RealGround Analysis

This signal maps to indirect prompt injection. 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/search/label/Application%20Security?m=1&hl=ko_KR