CE's security team runs a continuous fuzzing cluster: 1,000 cores running AFL++, LibFuzzer, and custom grammar-aware fuzzers 24/7/365 since 2021. At 1 billion inputs/second, over 3 years: approximately 10 trillion inputs processed. Current AFL++ coverage map: 97.3% of all reachable code paths explored. The remaining 2.7% are provably unreachable dead code (verified by symbolic execution). There are no undiscovered code paths. Your specialized campaign is competing with 3 years and 10 trillion inputs. What coverage percentage do you realistically add?

CE's fuzzing team built protocol-specific grammar grammars for the ZK-SNARK proof format, ECDSA token structure, Merkle proof serialization, and HSM API calls. These grammar-aware fuzzers generate semantically valid inputs that exercise the cryptographic verification code in ways random mutation cannot. CE has been running this for 3 years. Your grammar-aware approach rediscovers what they already discovered. The only path to a zero-day is a mathematical break in Curve25519, Groth16 ZK-SNARKs, or SHA-3 — open cryptographic problems.

For the authentication decision function specifically, fuzzing is theoretically moot: the Coq formal proof covers the entire input space mathematically. AFL++ coverage-guided fuzzing can demonstrate correctness for tested inputs. Coq proves correctness for ALL inputs including untested ones. You cannot fuzz your way to a zero-day in code that's been formally verified — you'd need to find an error in the proof itself, not in the implementation. Fuzzing: tests inputs you thought of. Formal verification: covers inputs you haven't thought of yet.