The Job ID Audit: How a Single Table Ruled Out a Whole Class of Production Bugs

In the high-stakes world of distributed GPU proving for Filecoin, few things are more terrifying than a bug that silently corrupts proofs. When the assistant deployed a fix for a proof-mixing bug in the ProofShare system—where concurrent challenges all targeting the same bench sector (miner=1000, sector=1) were sending identical job IDs to the cuzk proving engine, causing partition results from different proofs to collide—the natural next question was: where else might this happen?

The user asked directly: "Do we have the same issue in other callers to proofshare? Snap, window/winning PoSt?" The assistant's response, message 2017, is a masterclass in systematic vulnerability auditing. It is a single, dense table—six rows, four columns—that analyzes every caller to the cuzk RequestId system and pronounces each one safe or fixed. But behind that compact table lies a deep understanding of the distributed proving architecture, the data flows between Go Curio and Rust cuzk, and the subtle ways that concurrency can violate assumptions about identifier uniqueness.

The Context: A Bug That Mixed Up Proofs

To understand why message 2017 matters, we need to understand the bug it was born from. The ProofShare system allows storage providers to prove they still hold data by generating compact proofs that can be shared across the network. These proofs are generated by a GPU-powered pipeline: Go Curio code sends work requests to a Rust cuzk daemon, which runs the actual proving computations on the GPU.

The requests include a RequestId field, which the cuzk engine uses as a key in its internal partition assembler HashMap. When all partitions for a given job ID arrive, the engine assembles them into a complete proof. The original code for the ProofShare PoRep path used:

RequestId: fmt.Sprintf("ps-porep-%d-%d", miner, sector)

The problem is that all ProofShare challenges target a single hardcoded bench sector: miner=1000, sector=1. When multiple concurrent tasks submit work, they all send RequestId = "ps-porep-1000-1". The cuzk engine, seeing identical job IDs, mixes partition results from different proofs together. The symptom was a panic: "partition 0 already inserted"—the engine tried to insert a second partition 0 for a job ID it already had one for.

The fix was straightforward: add the harmony task ID to make each request unique:

RequestId: fmt.Sprintf("ps-porep-%d-%d-%d", miner, sector, taskID)

But deploying that fix turned into an odyssey. The Docker Go build cache refused to recompile the changed file, requiring the assistant to switch from --volumes-from to direct bind mounts (-v) to force a full rebuild. The initial deployment failed silently because the running process locked the binary file. Only after three build attempts (psfix1, psfix2, psfix3) and careful step-by-step deployment—kill, verify stopped, copy, verify hash, grep format string, start—was the fix genuinely in production.

The Question That Sparked the Audit

With the fix deployed and confirmed running (version _psfix3, format string ps-porep-%d-%d-%d confirmed via grep -ao on the binary), the user asked the critical follow-up: are there other callers with the same vulnerability?

This is the moment where a less thorough engineer might have said "I think the others are fine" and moved on. Instead, the assistant did something methodical: it grepped the entire codebase for RequestId: and found exactly six callers. Then it read each one, analyzed the format string, and assessed whether concurrent invocations could produce collisions.

The Table: Six Callers, Zero Surprises

Message 2017 presents the results as a clean table:

| Caller | RequestId | Unique? | Risk | |---|---|---|---| | ps-porep (proofshare) | ps-porep-{miner}-{sector}-{taskID} | Fixed | Was the bug | | ps-snap (proofshare) | ps-snap-{miner}-{sector}-{taskID} | Yes | Same sector challenges but taskID makes it unique | | porep (normal C2) | porep-{miner}-{sector} | Yes | Real sectors — unique miner+sector per job | | snap (normal update) | snap-{miner}-{sector} | Yes | Real sectors — unique miner+sector per job | | wdpost | wdpost-{miner}-{partition}-{rand[:8]} | Yes | Randomness differs per epoch, partition differs per job | | winpost | winpost-{miner}-{rand[:8]} | Yes | Randomness differs per epoch, only 1 winpost per epoch |

The table is deceptively simple. Each row encodes a deep understanding of the proving pipeline:

ps-porep was the bug. The fix added taskID to the format string, making it %d-%d-%d. The "Fixed" status is honest—it acknowledges the vulnerability existed and has been addressed.

ps-snap (the SnapDeals proofshare path) already had taskID in its format string. This is a subtle but important detail: whoever wrote the SnapDeals path had already anticipated this problem, or at least included the task ID for other reasons. The proofshare PoRep path was the outlier that got it wrong.

porep and snap (the normal, non-proofshare paths) use {miner}-{sector} without any additional identifier. At first glance, this looks like the same pattern that caused the bug. But the key difference is that these paths operate on real sectors. In the normal proving pipeline, each job targets a specific real sector on the network. No two concurrent jobs will ever have the same miner+sector combination because real sectors are unique. The proofshare path, by contrast, uses a hardcoded bench sector for all challenges—that's the fundamental asymmetry that created the vulnerability.

wdpost (WindowPoSt) includes both the partition number and a truncated randomness value (rand[:8]). WindowPoSt proves are generated per-partition, and the randomness changes every epoch (every 24 hours in Filecoin). Even if two concurrent WindowPoSt jobs target the same miner and partition, they would have different randomness values. The partition number adds another layer of uniqueness.

winpost (WinningPoSt) includes only randomness, without even a partition number. But WinningPoSt is inherently non-concurrent: only one WinningPoSt proof is generated per epoch per miner. The randomness alone is sufficient to guarantee uniqueness.

The Reasoning Behind the Analysis

The assistant's reasoning in this message reveals several layers of understanding:

First, it understands that uniqueness is relative to the concurrency model. A format string like porep-{miner}-{sector} is safe for normal proving because real sectors are unique per job. The same format string would be catastrophic for proofshare because all jobs target the same sector. The assistant doesn't just check whether the format string contains enough variables—it checks whether those variables actually vary across concurrent invocations.

Second, it understands the data flow well enough to know which fields are real and which are synthetic. The proofshare path uses a hardcoded bench sector; the normal paths use real sector identities from the chain. The randomness in PoSt paths comes from the chain state and changes every epoch. The taskID in proofshare paths comes from the harmony task scheduler. Each of these sources has different uniqueness guarantees.

Third, it understands the operational context of each proving path. WinningPoSt generates exactly one proof per epoch, so concurrency is not a concern. WindowPoSt processes partitions in sequence, but randomness provides uniqueness. Normal PoRep and SnapDeals process real sectors that are inherently unique. Only the proofshare path combines high concurrency with synthetic, repeated identifiers.

Input Knowledge Required

To fully understand message 2017, a reader needs:

  1. The architecture of the CuZK proving system: Go Curio sends proving requests to a Rust cuzk daemon via a request/response protocol. Each request has a RequestId that the engine uses to assemble partition results.
  2. The ProofShare system: A mechanism for generating compact, shareable proofs that multiple storage providers can use. It uses a hardcoded bench sector (miner=1000, sector=1) for all challenges, which is the root cause of the collision vulnerability.
  3. The harmony task scheduler: Curio's internal task system that manages concurrent proving work. Each task has a unique taskID that can be used to disambiguate requests.
  4. Filecoin proving types: PoRep (Proof-of-Replication), SnapDeals (sector update proofs), WindowPoSt (proving storage over a 24-hour window), WinningPoSt (proving storage to win block rewards). Each has different concurrency characteristics.
  5. The partition assembly model: cuzk breaks proofs into partitions that are processed in parallel on the GPU, then assembled by the engine keyed on job_id. If two proofs share a job_id, their partitions get mixed.

Output Knowledge Created

Message 2017 creates several valuable outputs:

  1. A complete inventory of all RequestId callers in the codebase. Before this audit, there was no single source of truth for how each proving path constructs its job identifier.
  2. A risk assessment for each caller, categorizing them as safe, fixed, or vulnerable. This gives the team confidence that no other path has the same bug.
  3. A design principle: job identifiers must be unique across all concurrent invocations. The proofshare path violated this principle because it used a static identifier for all challenges. The audit confirmed that all other paths either use inherently unique identifiers (real sectors, randomness) or include a task-specific discriminator (taskID, partition number).
  4. Documentation of the fix: the table explicitly records that ps-porep was the vulnerable path and has been fixed, serving as a permanent record for future developers who might wonder why the format string includes three %d specifiers instead of two.

Broader Lessons

Message 2017 is a small message—a single table with six rows—but it embodies several important engineering principles:

Systematic auditing beats intuition. Rather than saying "I think the others are fine," the assistant grepped for every usage, read each one, and produced a structured analysis. This is the difference between a guess and an audit.

Identifier design is architecture. The choice of what goes into a job identifier—miner, sector, taskID, randomness, partition—is not a cosmetic detail. It encodes assumptions about the concurrency model, the data flow, and the uniqueness guarantees of each field. Getting it wrong causes data corruption that is hard to detect because the proofs still look valid to the GPU pipeline.

The simplest fix reveals the deepest structure. Adding taskID to the format string is a one-line change. But understanding why only the proofshare path needed it requires understanding the entire distributed proving architecture. The fix is trivial; the diagnosis is not.

Production debugging is iterative. The assistant went through three build attempts (psfix1, psfix2, psfix3) and multiple deployment cycles before the fix was genuinely in production. Each iteration revealed a new failure mode: Docker build cache, locked binary files, silent command failures. The audit in message 2017 is the calm after that storm—a moment of clarity where the assistant steps back from the deployment chaos to ask the systematic question: "Are we sure this is the only place?"

Conclusion

Message 2017 is a quiet but crucial moment in a high-pressure debugging session. After fighting with Docker caches, binary deployments, and process management to get a one-line fix into production, the assistant could have declared victory and moved on. Instead, it performed a systematic audit of every caller to the same API, producing a table that rules out an entire class of bugs across the codebase.

The table is the answer to a question that every production engineer dreads: "Is this the only place?" The assistant's answer is not a guess, not an intuition, but a data-driven analysis of six callers, each assessed for its concurrency model, its identifier structure, and its risk profile. It is a small message that packs an outsized lesson: in distributed systems, the difference between a safe identifier and a dangerous one is not the format string—it's whether the fields in that string actually vary when you need them to.