AI Watermark Robustness Lab EU AI Act & Kirchenbauer Engine
Simulate token-level greenlist watermarking and test evasion workarounds (synonyms, homoglyphs, paraphrasing).
Watermark Generator & Token Config
Evasion & Perturbation Attack
⚠️ Warning: Short token sample (< 25 tokens) reduces statistical power; high false negative risk.
Statistical Detection MetricsLive Testbench
Clean Z-Score
5.84
Green: 76.7%
Attacked Z-Score
0.73
Green: 53.3%
Entropy Delta
+3.8%
T = 120 tokens
Attacked Watermark Status:
Watermark Evaded (Inconclusive, z < 2.33)
Gaussian Hypothesis Distribution (Null H₀ vs Watermark H₁)
Under unwatermarked null hypothesis H₀, expected greenlist count is 60.0 (50%). Clean stream contains 92 greenlist tokens (76.7%, z = 5.84, p < 0.0001). Under 35% synonym attack, greenlist count degrades to 64 (53.3%, z = 0.73), evading EU AI Act threshold.