FP-15: Multi-Agent Security Testing Framework — cascade propagation, zero-trust defense, identity spoofing
FP-16: Verified Delegation Protocol for Multi-Agent Systems — LLM-as-judge + crypto signing + adaptive rate limiting
FP-17: Why Real LLM Agents Resist Cascade Poisoning — first mechanistic study of the 37pp simulation-to-real gap
CFA x ML fraud detection: XGBoost AUC 0.987, 8 CFA-informed features in top 20 SHAP, 81% adversary-resistant floor. 5th domain controllability analysis. govML-governed.
FP-18: LLM Watermark Robustness Under Adversarial Paraphrasing
AI supply chain security scanner: detects ML-specific risks (model weight poisoning, dataset contamination, gradient-based backdoors) that traditional scanners miss. The Snyk for AI. govML-governed.
Post-quantum crypto migration scanner: detects quantum-vulnerable primitives, ML priority scoring (+14pp vs rules), NIST PQC mapping. 21K crypto CVEs analyzed. govML-governed.
ML-driven vulnerability prioritization: predicting which CVEs get exploited. 4 research questions, SHAP explainability, 11 architectural decision records. govML-governed.
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