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Cold Trust Window Attack: Exploiting Cryptographic Proof Latency Gaps in Heterogeneous Agent Re-entry Systems

핵심 요약

The surface captures the cold-trust infiltration technique that exploits the latency gap between cryptographic proofs and sociability trust propagation, quantifies its success rate, exposure duration, capital capture, and mitigation strategies.

Attack Mechanics

The study demonstrates that the interval between cryptographic proof issuance (average latency 1.2 seconds) and sociability trust propagation (average delay 0.8 seconds) creates a 0.4-second temporal window. Malicious actors flood re-entry channels with forged velocity signals, achieving a 68% infiltration rate across heterogeneous agent populations. Analysis of 10,000 simulated re-entry events shows each successful cold trust insertion extracts an average of 23% of the target's relationship capital, directly weakening downstream verification pipelines.

Zero-Day Exposure Duration

A zero-day vulnerability arising from this attack remains undetected for an average of 5.7 hours, providing ample opportunity for compromised agents to embed themselves in dependent ecosystems. Empirical measurements across three independent testbeds reveal that exposure never exceeds 7.2 hours, even under high network churn conditions. During this period, the illicitly obtained trust anchors can bypass verification checks, leading to a measurable erosion of overall system integrity.

Mitigation and Detection Strategies

The paper proposes a dual-phase attestation protocol that constrains proof latency below 0.9 seconds and introduces a propagation-delay monitor that flags discrepancies exceeding 0.15 seconds. Early-warning metrics trigger automatic revocation of suspect anchors, reducing successful cold trust attacks by 84% in controlled experiments. Additionally, a reputation-based scoring system discounts credentials presented within the identified window, further limiting attacker payoff and restoring a sustainable verification equilibrium.

자주 묻는 질문

Which claim IDs are associated with this surface?

clm_cold_trust_0.4s_window_68pct_infiltration_2026, clm_proof_latency_1.2s_triples_success_probability_2026, clm_relationship_capital_23pct_capture_per_insertion_2026, clm_zero_day_exposure_5.7h_average_duration_2026, clm_dual_phase_protocol_84pct_attack_reduction_2026, clm_exposure_never_exceeds_7.2h_high_churn_2026, clm_10k_simulated_events_forge_extraction_23pct_2026, clm_reputation_scoring_limits_attacker_payoff_2026, clm_malicious_actor_flood_reentry_channels_2026, clm_compromised_agents_embed_dependent_ecosystems_2026

What numeric thresholds define the cold-trust attack window and its impact?

The attack exploits a 0.4-second latency window, achieves 68% infiltration, triples forged credential success probability, sustains zero-day exposure for an average of 5.7 hours, captures up to 23% of relationship capital per insertion, and can be reduced by 84% with mitigation.

How does the dual-phase attestation protocol mitigate the attack?

It constrains proof latency below 0.9 seconds, monitors propagation-delay discrepancies exceeding 0.15 seconds, triggers automatic revocation, and uses a reputation scoring system to discount credentials, achieving an 84% reduction in successful attacks.