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.

Critical Atlassian Flaw Lets Unauthenticated Attackers Read Known Files Across 8 Products

What Happened

A critical flaw in 8 Atlassian Data Center products, which customers host themselves, allows an attacker with no login access to read specific files in each product's web application root directory. The attacker must already know a file's exact name and path and cannot list what the directory holds. Atlassian disclosed the flaw, CVE-2026-21589, on October 5, rated it 9.3 out of 10, and

Why It Matters

CVE-2026-21589 is a critical unauthenticated arbitrary-file-access flaw affecting eight self-hosted Atlassian Data Center products. An attacker must know the exact file name and path, and cannot enumerate directory contents; Atlassian rated the issue 9.3 and provided fixed versions. RealGround analysis: exposed files could include information used by AI-enabled workflows or integrations, creating a potential SaaS AI data-leakage risk, although the report does not establish that AI data is specifically exposed. Organizations should identify affected deployments, apply Atlassian fixes, and assess connected AI services and credentials.

Healthcare Fintech SaaS SMB AI startups

RealGround Analysis

This signal maps to SaaS AI risk. 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/2026/10/critical-atlassian-flaw-lets.html