CLIOPATRA: Extracting Private Information from LLM Insights | ScienceToStartup | ScienceToStartup

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References (54)

[1]

Anthropic Economic Index report: Uneven geographic and enterprise AI adoption

2025R. Appel, Peter McCrory et al.

[2]

Toward provably private analytics and insights into GenAI use

2025Albert Cheu, Artem Lagzdin et al.

[3]

The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injections

Founder's Pitch

"CLIOPATRA exposes vulnerabilities in privacy-preserving LLM systems, revealing the inadequacy of current protections."

Privacy in AI•Score: 4•View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

1/4 signals

2.5

Quick Build

1/4 signals

2.5

Series A Potential

0/4 signals

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CLIOPATRA: Extracting Private Information from LLM Insights

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References (54)

Founder's Pitch

"CLIOPATRA exposes vulnerabilities in privacy-preserving LLM systems, revealing the inadequacy of current protections."

Commercial Viability Breakdown

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Why It Matters

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Disruption

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CLIOPATRA: Extracting Private Information from LLM Insights

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References (54)

Founder's Pitch

"CLIOPATRA exposes vulnerabilities in privacy-preserving LLM systems, revealing the inadequacy of current protections."

Commercial Viability Breakdown

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