Practical guides, prompt libraries, and best practices for using AI in cybersecurity and beyond.
What Is a Large Language Model? A Large Language Model (LLM) is a type of AI trained on massive amounts of text data to predict the next most likely token in a sequence. That simple mechanic — predict the next token — is the foundation of everything from ChatGPT to Claude to Llama. ...
Why Prompt Engineering Matters The same model will give you dramatically different results depending on how you phrase your request. Prompt engineering is the practice of structuring your input to get consistently useful output. ...
Threat Hunting “You are a threat hunter. Given the following network logs, identify any patterns consistent with lateral movement, beaconing, or data exfiltration. Think step by step before giving your findings.” ...
Hallucination LLMs generate confident-sounding text that may be factually wrong. In security contexts this is dangerous. A model might: Fabricate a CVE number that doesn’t exist Invent tool flags or command syntax Cite statistics with no real source Describe a vulnerability incorrectly Mitigation: Always verify AI-generated technical claims against primary sources — NVD, vendor advisories, official documentation. ...
AI tools are showing up in analyst workflows whether your organization plans for it or not. A Tier 1 analyst dealing with a hundred alerts a day will find ways to work faster — and if the org hasn’t provided sanctioned tools, they’ll use unsanctioned ones. That’s not a criticism, it’s human nature under pressure. ...
Tier 1 analysts using AI for alert triage is one problem. Security engineers integrating AI into automated pipelines is a different one — and in some ways a harder one. When AI is in the pipeline, the decisions it influences happen at scale, without a human in the loop on every call, and the code you write today becomes the attack surface your team defends tomorrow. ...
AI adoption in SOCs is largely happening bottom-up. Analysts are finding tools that help them work faster. Engineers are integrating models into pipelines. This is happening whether or not there’s an organizational policy governing it — and in most cases, the policy comes after the adoption, not before. ...
Every major cloud provider has an AI product now. Most of them are genuinely useful. They’re also asking you to send your data — your queries, your context, your documents — to infrastructure you don’t control, operated by a company whose incentives around data retention may not align with yours. ...