SeedHijack forces attacker-chosen tokens in LLMs by manipulating PRNG outputs with 99.6-100% success across models and sampling methods, neutralized by a QRNG defense.
Machine learning needs better randomness standards: Randomised smoothing and PRNG-based attacks
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Seed Hijacking of LLM Sampling and Quantum Random Number Defense
SeedHijack forces attacker-chosen tokens in LLMs by manipulating PRNG outputs with 99.6-100% success across models and sampling methods, neutralized by a QRNG defense.