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.

AI Agent Business Logic Audit

Comprehensive review of LLM-based agent workflows, permission boundaries, tool invocation APIs, human-in-the-loop authorization gates, and downstream side effects.

Engagement Methodology

Who is AI Agent Business Logic Audit for?

Fintech Healthcare SaaS SMB

What use cases does this service cover?

Workflow Vulnerability Mapping
Privilege Escalation Scans
Tool Permission Audit
Human-in-the-loop Gate Review

Standard Deliverables

Detailed risk surface and model architecture mapping
Exploit scenarios, payload reports, and recreations
Specific prompt guardrails and output sanitizer templates
CISSP/CEH-informed security attestation letter

Schedule Engagement Briefing

In The News

Related Threat Reports

We monitor curated channels for live security compromises. Below are recent approved threat intelligence incidents relating to AI Agent Business Logic Audit risk scopes:

Published: 2026-xx-xx | Source: Attentus Technologies

AI Security Issues SMBs Need To Solve Before Rolling Out AI Tools

The article says SMBs should control AI use with company-managed accounts, role-based permissions, SSO, MFA, approved integrations, offboarding, monitoring, and a clear AI governance policy to reduce data leakage and unauthorized access.[2] It also highlights risks such as employees pasting sensitive data into AI tools, personal accounts being used for business tasks, and shadow AI creating visibility gaps.[2] RealGround analysis: this is primarily a data-leakage and governance issue, so the most relevant services are readiness assessment, policy support, and advisory to establish controls before wider AI rollout.

Severity Score: 72/100

Published: 2026-xx-xx | Source: Check Point Research

AI Security Report 2026

Check Point Research reports that indirect prompt injection is rising, with detections of longer malicious payloads increasing sharply between March and May 2026, and that enterprise AI data leakage remains persistent as more organizations use multiple AI apps, including some without official approval. The report also indicates higher-risk prompts are becoming more common. RealGround analysis: this points to a growing attack surface where malicious content can influence AI behavior and where governance gaps can increase the chance of unintended data exposure, so organizations should test agent boundaries, validate tool-use logic, and assess whether unsanctioned AI usage is creating leakage pathways.

Severity Score: 89/100

Published: 2026-10-09 | Source: thehackernews.com

FBI Says China-Linked Hackers Ran Portal Giving Third Parties Access to Stolen Emails

The FBI and international partners reported that China-linked actors associated with Integrity Technology Group compromised organizations and operated a web application that gave unidentified third parties access to stolen email content. Reported victims included government, law enforcement, healthcare, and religious organizations, with techniques including vulnerability scanning, password attacks, and mailbox collection. This is primarily a data leakage risk; RealGround analysis: organizations using AI systems with access to email or other sensitive repositories should assess exposure paths, access controls, monitoring, and incident-response readiness.

Severity Score: 95/100