The Grilling
📰 Dev.to AI
Learn to identify and address the structural blind spot in spec-driven AI frameworks by checking specs against potential attacks before implementation
Action Steps
- Identify potential attack vectors in your AI system's spec
- Implement a threat modeling process to check specs against attacks
- Integrate security checks into your CI/CD pipeline
- Test and validate your AI system's security using penetration testing and vulnerability assessments
- Continuously monitor and update your AI system's security posture
Who Needs to Know This
AI engineers, DevOps teams, and security experts can benefit from understanding this concept to improve the security and reliability of their AI systems
Key Insight
💡 Checking specs against potential attacks before implementation can significantly improve the security and reliability of AI systems
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💡 Identify the blind spot in spec-driven AI frameworks: check specs against attacks before implementation #AI #Security
Full Article
In Part 1 I argued that every spec-driven AI framework on the market - sixteen of them in my survey - has the same structural blind spot. They all check the implementation against the spec. None of them check the spec against attack before it gets written. Part 2 is the operational deep dive. What does the missing phase actually look like when you build it? How does it ru
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