Novus BT
Artificial Intelligence and Security · October 27, 2026

Critical Risks in Agentic AI Security: An Autonomous Pentesting Analysis of Hermes Agent

The autonomous penetration testing analysis conducted on Hermes Agent examined critical security risks, including authorization bypasses, Server-Side Request Forgery (SSRF), and Remote Code Execution (RCE). SecureHup helps organizations identify vulnerabilities in AI agents and provides actionable security recommendations to mitigate potential threats.

Artificial Intelligence and Security

We are living in the age of AI. Everyone is building their own Agentic AI ecosystem and automating their workflows. Some of us run popular agents like Hermes locally, while others deploy them on VPS infrastructure. We use these agents to process corporate documents, manage social media, write code, and grant them extensive operational privileges.

**But how secure is the “intelligent agent” infrastructure you trust?**

Critical Risks in Agentic AI Security: An Autonomous Pentesting Analysis of Hermes Agent

Recently, our research team conducted an autonomous penetration testing analysis of Hermes Agent, one of the popular open-source AI agents, and uncovered some concerning security risks:

  • **🔴 Authorization Bypass (Gateway Bypass)**

A2A (Agent-to-Agent) gateway adapters may bypass caller identity whitelisting mechanisms, potentially opening the door to unauthorized command injection from external sources.

**🔴 Blind Spots in SSRF and Cloud Data Exposure**

Server-Side Request Forgery (SSRF) risks through the Model Context Protocol (MCP) could allow attackers to reach cloud metadata servers or internal network resources. This could expose secret keys and sensitive data stored on the servers running these agents.

**🔴 Chained Vulnerabilities (RCE and File Locking)**

When file-locking race conditions combine with critical dependency vulnerabilities (such as those involving Brotli and Undici), they may create attack chains capable of enabling Remote Code Execution (RCE) on the host server.

Many organizations running AI agents on their own servers or local machines remain unaware of these architectural weaknesses and dependency vulnerabilities. Traditional security scanners, meanwhile, often fail to identify such deeply interconnected logical attack paths.

At **SecureHup**, we go beyond providing theoretical lists of vulnerabilities. We analyze your entire attack surface, from externally exposed assets to the internal layers where your AI agents operate, using live exploit validation. We also provide developers with clear, actionable remediation recommendations.

**Before you trust your AI with critical operations, put it to the test with SecureHup.**

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