Verified Network Tap

The control plane that decides what flows where on a GPU cluster fabric — SDN controllers, fabric managers, tenant routing tables (§) — is the same piece of infrastructure whose compromise is the threat. An operator’s own logs about what crossed which link cannot be evidence in a threat model where the operator’s logging stack is on the attacker’s side of the trust boundary. Independent observation on the fiber itself is the difference between “the controller says traffic between tenants A and B was partitioned” and “no such packet appeared on the inter-pod link during the audit window.”

[1] develop this as the verification primitive for AI-datacenter compliance under mutual distrust between operator and external verifier. Their cost figures are the encouraging part of the picture: a north-south tap at the datacenter edge captures all external traffic at well under 0.01% of facility upfront cost; an east-west storage-fabric tap with full hash-and-timestamp capture sits at 0.3-0.75%; compute-fabric sampling via optical circuit switches at 0.2-1.5%. FPGA capture at 400 Gbps and above already has precedent in financial-regulation hardware (Arista 7130, Deutsche Börse). [2] adds the optical reality the spec has to live with: passive splitters add no latency but eat link budget — a 1 dB loss can break a 53 Gbaud link — while active OEO taps regenerate the signal at roughly 20 ns latency and tens of watts but introduce a new failure point on the live link. The same artifact serves an internal threat model (compromised SDN controller, dishonest fabric manager) and an external one (treaty verifier, regulatory audit, third-party red team); the LTL contract below is identical, and the threat-model split surfaces only in key custody and in who is allowed to read the monitor leg — policy rather than mechanism (§).

Solution/project Sketch

The deliverable is the LTL contract below plus an open-source RTL reference design proven against it, for an active optical-electrical-optical tap at 400 Gbps with a path to 800 Gbps. FPGA is the expected deployment target: [1]‘s 400 Gbps capture precedent (Arista 7130, Deutsche Börse) is FPGA-based, and the audit story benefits from a re-flashable bitstream tied to a published proof. But the contract is platform-agnostic — an ASIC implementation that meets P1-P6 is equally valid, and an open-source RTL reference is what gets verified, not any particular bitstream. Three pieces: a hardware specification in Cryptol or SystemVerilog with proofs in SymbiYosys or Kami against the contract below; a tamper-evident reference design with externally inspectable interfaces; and an out-of-band verification cluster that consumes the monitor stream and runs compliance checks asynchronously, so the wire-side hardware stays simple enough to verify while sophisticated analysis happens elsewhere.

Let live_in(p, t) mean packet p was clocked into the tap on the live ingress at time t; live_out(p, t) that it was clocked out on the live egress; mon(r, t) that the monitor leg emitted a record r at time t; and fail(t) that the tap has self-reported a fault. Let D and D' be the forwarding and mirroring deadlines in clock cycles, and let image(p) be the deterministic projection of p into the monitor record format (header parse + timestamp + payload hash, per [1]).

Using for “always”, for “eventually”, for the past-time “once”, and for “eventually within steps”:

P1 and P2 together discharge the transparency obligation against the live forwarding path: nothing dropped, nothing synthesized. P3 and P4 discharge the monitor-leg faithfulness obligation: no missing packets, no fabricated ones. P5 is a hyperproperty rather than a pure LTL formula — a noninterference statement that the live-out signal does not depend on any input received via the monitor leg — and is the property that defeats the verifier-collusion attack in [1]‘s threat model. P6 is the fail-open invariant from [2]: a tap component failure must downgrade the device to a transparent pass-through, not a link-cut, because the live link is load-bearing for production traffic.

The projection image(p) is where the spec interacts with policy. For east-west compute-fabric taps, image(p) is a header parse plus a SHA-3 payload hash — the verifier learns timing and routing without payload contents. For north-south edge taps, the operator may retain session keys for post-hoc decryption under audit. Both factor through the same LTL contract; only the definition of image changes, which is the spec-implementation separability principle from §.

Two natural stopping points. A verified single-port tap with a stub fail-detection path, proven against P1-P6 modulo a hand-modeled SerDes layer, is shippable as a reference design. The same tap proven against a co-developed model of a real 400G PCS/SerDes is the research contribution; this is the same hardware-model gap that blocks GPU driver verification (§). Multimode fiber is out of scope — the link budget does not admit passive splitting at high baud rates [2] — and the industry trend toward single-mode-only AI fabrics is the precondition this widget ships against.

Bibliography

// stack context

[orchestration-cloud] Orchestration & Cloud

Orchestration and Cloud Layer The orchestration layer manages the compute resources that ML workloads run on: scheduling jobs across GPU clusters, routing traffic between them, and controlling who can access what. It sits below the frameworks and above the firmware — a layer of distributed systems s

[hardware-supply-chain] Hardware & Physical Supply Chain

Hardware and Physical Supply Chain At the bottom of the stack is the silicon itself: the GPU, TPU, and NPU dies that run every training and inference workload, and the global supply chain that produces them. Compromise here is durable: a hardware trojan survives every software update, every OS reins

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