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# STOIC Security: Shielding Your Generative AI App from the Five Deadly Risks - Jeff Watkins

**[NDC Conferences](https://daily.dev/sources/ndc)** · 57 min read · 0 upvotes · 0 comments

## Summary

The STOIC framework provides a structured approach to securing generative AI applications through five threat categories: Stolen (data/model theft), Tricked (prompt injection and adversarial manipulation), Obstructed (denial of service), Infected (model poisoning and backdoors), and Compromised (infrastructure vulnerabilities). The framework draws parallels to Microsoft's STRIDE methodology but addresses AI-specific risks like model extraction, jailbreaking, resource exhaustion, and training data poisoning. Key mitigations include input/output validation, supply chain security, access controls, network segregation, continuous monitoring, and integrated DevSecOps pipelines. Unlike traditional software, generative AI's probabilistic nature and unbounded outputs create unique security challenges requiring lifecycle-wide defensive thinking.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=rfh_8vyi3OE>

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---

Tags: [#ai-security](https://daily.dev/tags/ai-security), [#cyber](https://daily.dev/tags/cyber), [#llm](https://daily.dev/tags/llm), [#prompt-injection](https://daily.dev/tags/prompt-injection), [#security](https://daily.dev/tags/security)

[View this post on daily.dev](https://daily.dev/posts/stoic-security-shielding-your-generative-ai-app-from-the-five-deadly-risks---jeff-watkins-uvdv04nig)

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