[Feat/Security]: Implement Dynamic Zero-Knowledge Local PII Masking & Token Obfuscation at the Transport Proxy Ingress

Problem

Large enterprises routing automated agent workloads through cloud nodes risk exposing sensitive corporate datasets (PII, API keys, compliance logs) to public third-party model endpoints. Injecting standard application-layer masking tools spikes processing latency and drops system throughput.

Proposed Solution

Build an integrated, high-throughput string-matching PII and Data Masking Engine within internal/gateway/handlers.go operating natively at the raw byte stream layer.

• Implement an allocation-optimized pattern matcher utilizing Aho-Corasick or vectorized bit manipulation algorithms inside Go runtime memory pools.
• Intercept raw payloads on the fly, dynamically swapping out sensitive matching indices (Credit Cards, Social Security numbers, internal keys arrays) with transient, salted anonymous hash tracking tokens before data bytes leave the enterprise VPC parameter.
• Cache the matching mapping keys inside the local thread-safe InMemoryStore to decode returning model responses transparently.

Alternatives

• Forcing enterprises to use application layer governance tools, which increases code integration friction and introduces noticeable latency spikes inside the hot routing loop.

Use Case

Unlocks total data sovereignty and automated regulatory compliance for strict banking, defense, and multi-tenant enterprise cluster installations with under < 1ms overhead.

Additional Notes

Must remain fully non-invasive, preserving full formatting arrays integrity so the target model execution runs cleanly without context deformation.

Start by reading internal/gateway/handlers.go and locating the thread-safe InMemoryStore path; the issue provides no test or narrower entry point. Scope and acceptance criteria need maintainer clarification for matcher coverage, token round-tripping, formatting preservation, and latency before implementation can be considered done.