
Discover Hermes, an autonomous agentic AI that acts as a persistent digital worker for cybersecurity. Learn secure implementation, governance, and risk management, including prompt injection and attack surface considerations.
Explore Hermes architecture as a three-tier interface, core agent, and execution stack for a self-hosted AI assistant with an agent-first self-improvement loop, persistent memory, and YAML-based skills learned from interactions.
Evaluate Hermes installation options—from local deployment to cloud VPS and managed services—balancing performance, cost, uptime, and security, and prepare a quick proof of concept while hardening the setup.
Set up a Hermes instance on a cloud-based VPS or local server. Install Hermes via the terminal on Ubuntu, configure a Telegram bot, and run Hermes as a systemd service.
Configure Hermes by editing soul.md and user.md to establish a cybersecurity personality, inspect memory.md, and start fresh sessions to apply updates across Telegram and other interfaces.
Explore Hermes skills as reusable markdown workflows guiding cybersecurity tasks, with a CLI marketplace, inspect-before-install, security scans that quarantine risky skills, and self-improvement loops refining incident writing.
use the curator to archive unused skills and pin critical ones, with dry runs and guard and right-approval controls shaping the Hermes self-improvement loop.
Compare hermes and openclaw, highlighting hermes' self-improving agent with a long-lived model versus openclaw's gateway-first tool orchestration and vast claw hub skills.
Harden Hermes by performing a config-level security audit, verifying the Hermes version with hermes doctor, enforcing non-root operation, container deployment, and strict command approvals, including Telegram access restrictions.
Explore how Hermes uses a closed learning loop to act as a cybersecurity force multiplier, delivering automated daily briefings, CVE checks, and vendor breach monitoring via Zapier MCP.
Explore how agentic ai evolves from the gen ai era to autonomous systems that plan, act. Become an ai-literate cybersecurity orchestrator, embedding securities with Hermes to design smarter systems.
AI agents are no longer limited to answering questions or generating text. They can now execute commands, access files, connect to APIs, automate workflows, and operate continuously inside real environments. Platforms like Hermes Agent represent the next evolution of AI .. moving from passive assistants to autonomous systems that you self-host, run on your own infrastructure, and that act on your behalf around the clock.
For cybersecurity professionals, this shift creates a problem.
On one hand, Hermes can act as a powerful force multiplier .. automating security tasks, accelerating analysis, and, uniquely, getting better at your job the longer you use it through its self-improving learning loop.
On the other hand, it introduces a completely new attack surface — where an AI agent has access to systems, data, and execution capabilities without mature security controls, governance models, or visibility. And because Hermes is self-hosted and writes its own skills over time, securing it is now your responsibility, not a vendor's.
The "Hermes Agent for Cybersecurity Professionals" course is a practical, security-focused, hands-on course designed to help security engineers, cloud security professionals, DevSecOps practitioners, and security leaders understand, secure, and effectively use agentic AI systems .. using Hermes, the most-used AI agent in the world, as a real, working example you deploy and harden yourself.
What You Will Learn
How Hermes works as a self-hosted, open-source agentic AI platform — and why it is fundamentally different from traditional AI tools like ChatGPT
How autonomous agents interact with systems, including file access, command execution, API calls through MCP, and multi-step task orchestration
How Hermes's closed learning loop works — the feature that lets it write its own skills and improve over time, and why it is the single most novel attack surface in any agent framework
How to identify and analyse the new attack surface introduced by AI agents, including prompt injection, data leakage, over-privileged execution, poisoned skills, and supply-chain risks
How to design secure Hermes deployments using least privilege, container isolation, and Zero Trust principles
How to implement practical security controls hands-on — hardening a live Hermes instance on a VPS with a messaging gateway, step by step
How to govern the learning loop with write-approval gates, skill vetting, and the trust model
How to safely use Hermes as a cybersecurity force multiplier, including acting through Zapier MCP as a governed broker
How to prepare for the future of personal and enterprise AI agents, including digital employees and multi-agent ecosystems
Who Should Take This Course
This course is designed for cybersecurity professionals who want to understand and secure the next generation of AI systems, including:
Security analysts and SOC engineers looking to automate repetitive security workflows
Cloud security engineers working in AWS, Azure, or GCP environments
Application security and DevSecOps engineers integrating AI into pipelines
Security architects evaluating the risks of agentic AI systems
GRC professionals assessing governance, compliance, and audit implications
Security leaders and CISOs preparing for AI adoption in their organisations
Prerequisites
A basic understanding of cybersecurity concepts is recommended
General awareness of AI tools such as ChatGPT or Claude
No prior experience with Hermes or agentic AI systems is required
Comfort with a Linux command line and basic SSH is helpful for the hands-on hardening labs, but every command is provided and explained
No programming experience is required — this course focuses on security, architecture, and real-world usage