Audits a synthetic dataset (SDG output) for membership-inference and record-linkage leakage from the real training set — runs a shadow-model MIA attack against the SDG, computes distance-to-closest-record (DCR) and nearest-neighbor distance ratio (NNDR) between synth and real-train, flags any exact / near-exact duplicates, and produces a release recommendation (publish / publish-with-DP / restrict / withhold). Triggers whenever the user intends to share, publish, or release synthetic tabular data derived from sensitive real data (PHI, PII, financial, customer records). Refuses to certify privacy on utility metrics alone, refuses to substitute k-anonymity-on-real for MIA-o…
