The Art of Systematic Elimination: Debugging a CuZK SNARK Verification Failure Through Enum Tracing and Structural Parity

Introduction

In any complex debugging effort, the most challenging bugs are often those that manifest intermittently and resist simple explanation. The PSProve PoRep (Proof-of-Replication) bug investigated in this session exemplifies this category: CuZK-generated SNARK proofs were failing ffi.VerifySeal while the same proofs generated through the standard FFI path passed verification. The failure was intermittent, appearing only some of the time, and the root cause was hidden somewhere in the chain of transformations that C1 output undergoes as it travels from the proof-of-work server through the provider service and into the CuZK proving engine.

This article examines a critical sub-session of that investigation, where the assistant employed a methodical strategy of systematic elimination: tracing enum mappings across three languages, verifying structural parity between Go and Rust type definitions, investigating a promising lead about seed masking, and ultimately building diagnostic infrastructure to capture the exact byte-level discrepancy. The work demonstrates a debugging methodology that is both rigorous and adaptive, combining forensic code archaeology with pragmatic instrumentation.

The Problem: An Intermittent Verification Failure

The bug manifested in a specific scenario: when the CuZK GPU proving engine was used to compute the C2 (SNARK compression) phase of a PoRep proof, the resulting SNARK proof would sometimes fail ffi.VerifySeal. The same C1 input, when processed through the standard Filecoin FFI path (SealCommitPhase2), would produce a valid proof that passed verification. This suggested that the issue was not in the C1 data itself—since the FFI path could produce valid proofs from it—but rather in how CuZK was interpreting or processing that data.

The user had already done significant groundwork, identifying that the CuSVC system operates along two distinct paths: a Proof-of-Work path using bench sectors with random seeds generated by the powsrv service, and a proof-outsourcing path using real sectors with original sealing parameters. The PoW path was the one exhibiting the intermittent failure, making it the focus of the investigation.

Tracing RegisteredSealProof Across Three Languages

The assistant's first major line of inquiry was to trace the RegisteredSealProof enum mappings across the three languages involved in the system: Go (in the filecoin-ffi bindings), C (in the cgo bridge layer), and Rust (in the cuzk-core proving engine). The hypothesis was that if any of these enum values were misaligned—if, for example, the Go code interpreted StackedDrg32GiBV1_1 as a different integer value than the Rust code—then the CuZK engine might be using the wrong proof parameters, leading to verification failures.

The assistant systematically read the enum definitions in each layer. In Go, the RegisteredSealProof enum is defined in the go-state-types package, mapping proof type strings to integer constants. In C, the cgo bridge layer translates between Go and Rust representations. In Rust, the cuzk-core library defines its own RegisteredSealProof enum for the GPU proving pipeline. The assistant confirmed that all three definitions were identical: StackedDrg32GiBV1_1 mapped to the same integer value in every layer, and the full set of proof types (2KiB, 8MiB, 512MiB, 32GiB, 64GiB) were consistently represented.

This was a significant finding. It ruled out the most obvious class of bugs—a simple enum mismatch that would cause the wrong proof parameters to be used. The enum mappings were structurally sound.

Verifying Structural Parity Between Go and Rust Types

With the enum mappings confirmed correct, the assistant turned to the next potential source of discrepancy: the structural alignment between the Go Commit1OutRaw type and the Rust SealCommitPhase1Output type. These two types represent the same data—the output of the Commit Phase 1 computation—but exist in different language ecosystems with different serialization conventions.

The Go Commit1OutRaw struct (defined in /tmp/czk/lib/proof/porep_vproof_types.go) contains fields for CommD, CommR, RegisteredProof, ReplicaID, Seed, Ticket, and VanillaProofs. The Rust SealCommitPhase1Output struct (in the cuzk-core codebase) contains the same logical fields. The assistant verified that the JSON serialization of both types produces identical field names and structure, and that the CuZK gRPC service layer correctly deserializes the Go-serialized JSON into the Rust struct.

Critically, the assistant confirmed that the non-CuZK FFI path works correctly with the Go-re-serialized JSON. This was a crucial control experiment: if the FFI path can produce valid SNARK proofs from the same JSON bytes that are sent to CuZK, then the JSON itself is semantically valid. The problem must lie in how CuZK processes those bytes—perhaps in how it derives public inputs, or in some subtle aspect of the proof computation that differs from the FFI implementation.

This finding narrowed the root cause to a subtle byte-level discrepancy in the JSON payload that causes the CuZK-generated SNARK to fail verification. The most likely explanation was a difference in how the public inputs are derived from the serialized data—perhaps CuZK and the FFI interpret a particular field differently, or one path applies a transformation that the other does not.

The fr32 Seed Masking Investigation

The user provided a specific hint that proved valuable: an observation about fr32 seed masking. In the Filecoin proof system, when a 32-byte seed is used as an Fr (field) element, the standard practice is to mask the most significant byte with seed[31] &= 0x3f to ensure the value fits within the field modulus. The user had noticed that the powsrv service does not apply this masking, while the standard sealing pipeline does.

The assistant investigated this lead thoroughly. It traced the seed generation in powsrv (which uses crypto/rand to generate 32 random bytes without masking) and compared it to the standard sealing path (which applies the mask). It then analyzed the Rust challenge derivation code in cuzk-core to understand how the seed is actually used.

The analysis revealed that the seed is used as raw bytes for SHA256 hashing in the challenge derivation process, not directly as an Fr element. The masking is only relevant when the seed is interpreted as a field element, which happens in a different part of the pipeline. Since CuZK and the FFI both use the same challenge derivation code (which treats the seed as raw bytes), the missing mask in powsrv does not explain the intermittent verification failure.

However, the assistant noted that the missing mask remains a correctness issue in powsrv—it could cause problems if the seed is ever used as an Fr element in a different context. But for the specific bug under investigation, it was ruled out as the root cause.

Building Diagnostic Infrastructure

With the enum mappings confirmed correct, the structural parity verified, and the seed masking lead ruled out, the assistant pivoted to a different strategy: building diagnostic infrastructure to capture the exact byte-level discrepancy at the moment of failure.

The assistant extended the existing 2KiB roundtrip test to cover the full CuZK wrapper and FFI C2 verification path. This test exercises both the CuZK and FFI proving paths with the same C1 input, capturing the SNARK proof output from each path and comparing them. If the proofs differ, the test can pinpoint where they diverge.

More importantly, the assistant added comprehensive diagnostic logging to the computePoRep function in /tmp/czk/tasks/proofshare/task_prove.go. This logging captures:

• The exact JSON bytes of the C1 input as received by the worker
• The wrapped C1 output as sent to CuZK
• The SNARK proof returned by CuZK
• The verification result from ffi.VerifySeal
• The full SealVerifyInfo structure used for verification This instrumentation transforms a black-box failure into a observable data flow. When the next failure occurs, the logs will show exactly which bytes entered CuZK, which proof came out, and what verification parameters were used. This is the debugging equivalent of adding a flight recorder to an aircraft—it doesn't prevent the crash, but it ensures that when it happens, the investigators have the data they need to understand why.

The Broader Significance

The debugging methodology demonstrated in this session is worth examining for its broader applicability. The assistant employed a strategy of systematic elimination: ruling out entire classes of potential causes through targeted investigation before drilling down into the remaining possibilities. Each investigation was designed to produce a definitive yes/no answer:

• Are the enum mappings consistent? Yes.
• Is the structural parity between Go and Rust types correct? Yes.
• Does the FFI path work with the same JSON? Yes.
• Is the missing seed masking the cause? No. Each "no" eliminated a branch of the possibility tree, narrowing the search space. Each "yes" confirmed that a particular layer of the system was functioning correctly, allowing the investigation to move to the next layer. This approach is particularly valuable in multi-language systems where bugs can lurk at the boundaries between components. The enum tracing across Go, C, and Rust is a textbook example of boundary verification: when data crosses a language boundary, the representation of that data must be verified on both sides. The assistant didn't assume that the enum values were the same—it read the definitions in each language and confirmed them empirically. The seed masking investigation also demonstrates an important principle: follow the user's hints, but verify them independently. The user's observation about seed masking was a valuable lead, but the assistant didn't accept it as the root cause without analysis. It traced the actual usage of the seed in the challenge derivation code and determined that the masking was irrelevant to the specific computation path. This saved time that might have been spent implementing a fix that wouldn't solve the problem.

Conclusion

The PSProve PoRep debugging session represents a masterclass in systematic debugging of distributed proving systems. By tracing enum mappings across three languages, verifying structural parity between Go and Rust types, investigating and ruling out a promising lead about seed masking, and building diagnostic infrastructure to capture the exact byte-level discrepancy, the assistant narrowed the search space from a broad "something is wrong with CuZK" to a precise "there is a subtle byte-level discrepancy in how CuZK derives public inputs from the JSON payload."

The work is not yet complete—the diagnostic logging and extended roundtrip test will need to be exercised against a real failure to capture the definitive evidence. But the investigation has been structured so that when that evidence arrives, it will be interpretable. The flight recorder is installed. The next failure will tell the story.

This session also illustrates a deeper truth about debugging complex systems: the most effective approach is often not to guess the root cause and test it, but to systematically eliminate possibilities until only one remains. Each confirmed alignment, each verified mapping, each ruled-out hypothesis brings the investigator closer to the truth. The bug is still at large, but its hiding places are dwindling.