Equation 7 · AI and Cybersecurity in Practice: An Advanced Technical Guide
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the better monitoring reduces your uncertainty about. Read the equation part by part below; each part has a contextual explanation and a link to its mathematical background.
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Two of the terms in that sum are hard to know honestly. An estimate of assumes a threat model that has to guess at an adversary’s behaviour, and is only bounded once you have already imagined the worst plausible use of the capability — the same failure of imagination that undermines defense-in-depth probability estimates generally. But there is one operation available to a system designer that requires no estimate at all: revoke the capability, and its term leaves the sum exactly, not approximately. Better monitoring reduces your uncertainty about . Removing c removes the need to know it. That is the quantitative case for treating scope reduction as the first move rather than “we…
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Two of the terms in that sum are hard to know honestly. An estimate of assumes a threat model that has to guess at an adversary’s behaviour, and is only bounded once you have already imagined the worst plausible use of the capability — the same failure of imagination that undermines defense-in-depth probability estimates generally. But there is one operation available to a system designer that requires no estimate at all: revoke the capability, and its term leaves the sum exactly, not approximately. Better monitoring reduces your uncertainty about . Removing c removes the need to know it. That is the quantitative case for treating scope reduction as the first move rather than “we will detect misuse if it happens” — detection is a hedge against the terms you decided you could not remove, not a substitute for removing the ones you could.
Sources cited in the article section
- [4] LLM06:2025 Excessive Agency ↗
- [12] Security Best Practices ↗
- [5] OWASP Top 10 for Agentic Applications ↗
These citations give research context. Read each source to check which claims it supports.
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