CyberED

Entering Cybersecurity Without a Specialized Degree: Sector Rules and Practical Entry Points

The article examines whether a specialized higher education diploma is necessary to start a career in information security. It breaks down three main industry segments—state security structures, regulated government organizations, and private business—and explains the differing formal and practical requirements in each. In government-related roles, candidates must meet strict regulatory standards for education and approved programs. Private companies instead focus on demonstrable technical skills in networks, Windows Server, Linux, and security tools. The piece also covers typical junior engineer expectations, real-world career paths from unrelated backgrounds, and four key ways to prove competence without a diploma. It concludes with advice on building home labs, troubleshooting skills, and accessing open training resources like the CyberED course.

How to Build an AI Agent for Pentesting Without Turning It Into a Black Box

Most security specialists use language models as advanced references where the human reviews every suggestion before execution. With autonomous AI agents the workflow changes dramatically as the agent plans steps, calls tools, analyzes outputs and maintains memory across multiple iterations. This automation introduces serious risks because specialists may see only the final result without understanding which hypotheses were tested or why specific commands were chosen. CyberED and Standoff Hackbase are running a practical AI pentesting challenge to help participants build controllable agents. The event includes a live webinar on 10 September followed by a week-long hands-on period on the Standoff Hackbase training range. Experts emphasize defining strict technical boundaries, logging every decision, and keeping high-risk actions under human oversight.

AI Agents Given Code and API Access Can Now Assist Attackers

An AI assistant that only answers questions can make mistakes, but an AI agent with access to email, code execution, corporate APIs and internal data can make those mistakes inside production infrastructure. The difference is fundamental: once tools, credentials and internal data are connected to the model, it becomes a privileged user that may not distinguish legitimate commands from hidden instructions on a web page. OWASP lists prompt injection, sensitive data disclosure, unsafe output handling and excessive autonomy as key risks for LLM applications. MITRE ATLAS specifically describes techniques involving prompt injection, context poisoning and tool invocation by AI agents. The article examines how agents differ from chatbots, how attackers can control them through untrusted content, and why a system prompt alone cannot protect code, data and APIs. CyberED is running its free NeuroAugust series of events and materials on AI in cybersecurity, including a session on secure AI system development.