Attacks on GenAI Data & Using Vector Encryption to Stop Them

Security Gaps in Vector Databases

The rapid adoption of generative AI tools has led to massive stores of sensitive health, financial, and HR data being indexed inside vector databases without native encryption controls.

Embedding Inversion Attacks

Contrary to common assumptions, vector embeddings are not secure one-way hashes. Inversion attacks can reconstruct original text, faces, and documents directly from stored vector embeddings.

Vector Encryption Cryptographic Principles

Researchers developed vector encryption algorithms that enable privacy-preserving similarity searches over fully encrypted vectors without decrypting underlying embeddings.

Open Source Implementation and Tradeoffs

Benchmarking open-source vector encryption tooling demonstrates practical trade-offs between computational latency, search accuracy, and mathematical data privacy.