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.

Google Launches Gemini 3.5 Flash Cyber AI to Find and Fix Software Vulnerabilities

What Happened

Google's DeepMind on Tuesday announced the release of Gemini 3.5 Flash Cyber, a specialized artificial intelligence (AI) model built atop 3.5 Flash that's designed to discover, validate, and patch vulnerabilities quickly and efficiently. According to the tech giant, the model will be exclusively available to governments and trusted partners via CodeMender as part of a limited-access pilot

Why It Matters

Fact: Google DeepMind has launched Gemini 3.5 Flash Cyber, a cybersecurity-specialized derivative of Gemini 3.5 Flash that runs inside the CodeMender code security agent to discover, validate, and patch software vulnerabilities at scale, and is being restricted to governments and trusted partners in a limited-access pilot due to its dual‑use potential.[1][4][9] Fact: The model coordinates multiple agents to explore different code paths and merge findings into a combined report, and is already being used across Google’s internal codebases (Chrome, Android, Cloud, Ads, YouTube) to find and fix vulnerabilities.[1][3][4] Analysis: From a RealGround perspective, this is a powerful agentic security AI that can autonomously modify code, making AI agent abuse and misconfiguration a key risk—if similar capabilities are exposed more broadly, compromised agents or indirect prompt injection could cause destructive or insecure code changes at scale. Continuous AI red teaming and secure agent design are critical to test for misuse pathways, validate guardrails around automated patching, and ensure organizations understand the AI supply chain implications of depending on a single

Healthcare Fintech SaaS SMB AI startups

RealGround Analysis

This signal maps to AI agent abuse. 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/2026/07/google-launches-gemini-35-flash-cyber.html