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 Code Execution Vulnerability Patched in TeamCity

What Happened

Tracked as CVE-2026-63077, the security defect can be exploited without authentication via the agent polling protocol. The post Critical Code Execution Vulnerability Patched in TeamCity appeared first on SecurityWeek .

Why It Matters

The article reports a critical unauthenticated remote code execution vulnerability (CVE-2026-63077) in JetBrains TeamCity On-Premises, exploitable via the agent polling protocol and allowing attackers to bypass authentication and run arbitrary OS commands on the CI server.[1][2][3][7] All on-prem TeamCity versions before 2025.11.7 and 2026.1.3 are affected, and patches plus a security plugin for older versions have been released.[1][2][7] From a RealGround perspective, CI/CD platforms like TeamCity are core components in the software and AI supply chain: compromise of the build server can lead to tampered models, poisoned training data, malicious artifacts, and backdoored AI services. Organizations should treat this as a supply-chain exposure and ensure CI systems used to build or deploy AI models are inventoried in SBOMs, rapidly patched, and subject to hardened network access and continuous security monitoring.

Healthcare Fintech SaaS SMB AI startups

RealGround Analysis

This signal maps to AI supply chain. 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://www.securityweek.com/critical-code-execution-vulnerability-patched-in-teamcity/