IA Utils — Adversarial Vector Attack
A gradient-based (PGD-style) stress test for
enhanced_dense_healing_hybrid's
Phi-Trigger decision. evaluate_phi_trigger
(dense_evolution.healing) thresholds |v_dinamic| with a
hard step (not differentiable at the boundary), but v_dinamic itself is
built entirely from JAX-differentiable operations — this crafts the
minimal perturbation (projected into an L2 epsilon-ball) that flips the
trigger either direction, rather than adding random noise and hoping.
Adapted from IGME's chained-differentiable-attack idea (arXiv:2607.27465, "Efficient Chained Method Ensemble for Transferable Semantic Segmentation Attacks", He & Zhang), applied here to vector sequences instead of image segmentation.
::: ia_utils.adversarial_vector_attack
Two directions of attack:
flip_to_dynamic(evade) — make static-looking corruption pass through unhealed.flip_to_static(suppress) — make genuine dynamic signal get wrongly median-replaced.
Two real bugs were found and fixed during this utility's own
verification, not assumed correct: the default step_size used to scale
with the epsilon budget (a larger budget converged to a worse
result — verified directly, non-monotonic in epsilon — now a small fixed
default independent of epsilon), and calculate_phi_ab's [0,1] clip
saturating for inputs whose semantic distance exceeds
MAX_SEMANTIC_DISTANCE, giving an exact-zero gradient (a real property
of the formula, now detected and reported — perturbation_norm == 0,
success == False — rather than silently misreported as "no better
point found").
See also: ia_utils.vector_healing for
the function under test, and dense_evolution.healing for
the underlying Phi-Trigger primitives.