OWASP's Top 10 Ways to Attack LLMs: AI Vulnerabilities Exposed
IBM Technology. Zooms out from prompt injection to the wider OWASP Top 10 for LLMs — insecure output handling, sensitive information disclosure, excessive agency — which is exactly the failure-mode catalogue you want in mind before you grant Gmail or HubSpot scopes to anything.
AI Expert note
Treat this as conceptual guidance. Do not use real company data until permissions, retention, logging and human-review boundaries are clear.
What you should get from this
Use the OWASP LLM risk categories to review tool access, output handling and sensitive-data exposure.
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Fireship's three rules — pick a boring popular stack, get good at Git, treat yourself as the product manager — are the same guardrails the article is trying to install.
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Take it further
Hand-picked external courses that go deeper on this topic.
EIPA — European Institute of Public AdministrationAI & EU Law: Definition and Developments
The fastest credible briefing on what the AI Act actually says — written by the institute that trains EU civil servants. Forty-five minutes; covers the risk-tier classification, who's responsible for what, and what changes for your product roadmap. The single best starting point for EU-deployed AI systems.
Coursera · University of MichiganGenerative AI: Governance, Policy, and Emerging Regulation
Few courses survey the regulatory landscape across the US, EU, and G7 in one place; this one does. Useful for compliance officers and product leaders trying to ship into multiple jurisdictions without inheriting hidden legal exposure. Pairs well with the EIPA EU AI Act primer for the European-specific detail.