Key concepts: AI in it & cybersecurity
Know these before you put a bot to work in it & cybersecurity. They are why the techniques and prompts are built the way they are.
Prompt injection
Text a bot reads (emails, web pages, logs) can carry hidden instructions. Never give a bot both untrusted input and powerful tools.
Secrets hygiene
Redact keys, tokens, hostnames and IPs.
OWASP Top 10 for LLM apps
Common risks in apps that use language models.
NIST CSF 2.0
Govern, identify, protect, detect, respond, recover.
How chatbots fail
Language models predict likely text. They can produce fluent, confident answers that are wrong, out of date, or that cite sources that do not exist. They also repeat errors in what you paste in. Ask for sources, ask the bot to mark uncertainty, and check everything that matters.
Accuracy and ethics, every time
- Confidentiality: never paste client, patient, student, employee or customer personal data (PII/PHI) into a public bot. Use tools your organization has approved, with contract terms that cover data use, or remove identifiers first.
- Verify everything: bots can invent citations, case law, statistics, doses, code sections and quotes that look real. Check each one against the original source before you rely on it.
- Not professional advice: these tutorials teach you how to use AI tools. They are not legal, medical, tax, financial or engineering advice.
- A human professional is responsible: the licensed or accountable person reviews, decides and signs. The bot drafts; you own the result.
- Prices change: we don't list product prices. Check each vendor's official pricing page.
Official sources for this section
- CISA: Artificial Intelligence: AI security resources
- NIST Cybersecurity Framework: CSF 2.0
- OWASP Top 10 for LLM Applications: LLM risks
- CISA Known Exploited Vulnerabilities: KEV catalog
Links checked Oct 30, 2026. Rules differ by state and country; follow your licensing body and employer policy.
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