earlyink Record 4/286 confirmed · median 3d early
272 first flagged27 Oct 2026

Leak Probe: cross-tenant cache and egress tests for hosted inference providers

Canary tests showing whether hosted inference leaks one customer's prompts to another; inference providers and fintech buyers pay.

Early · Workers AI KV cache exposure

Written for: Small startup team

Next step

Call the head of security at an inference provider that sells to regulated buyers, such as Together AI or Fireworks AI. Offer to run the two-account canary test on their endpoints for free in exchange for a reference customer.

Why now

Providers share prefix and KV caches across requests to cut cost, and price cuts like Terra's add to that pressure. Bank vendor-risk questionnaires do not ask about cache isolation yet. Today's incident gives buyers a named bug class with a public discussion. Cohere's published Qwen traces add a second test: does an open-weight model call URLs it never announced? That claim is contested, so treat it as a test to run, not a verdict.

What became possible

A reported KV-cache exposure on Cloudflare Workers AI let one request see another's cached data on the GLM-5.3 model, and it drew 155 responses on Hacker News. Inference speed and cost depend on routing, caching and scheduling, as the YC Paper Club on inference laid out. Every cache shared between customers is a place where isolation can fail.

Three ways in

  1. Leak Probe CI

    A nightly harness on two accounts. It plants canary secrets from one account and probes for them from the other, checking for leaked content and for timing differences that reveal what is in a shared prefix cache.

    Customer
    Security teams at inference providers selling to regulated buyers
    Model
    Annual attestation report plus a monitoring subscription
  2. Vendor Pack

    Test results and a questionnaire addendum written for third-party risk reviewers at banks and fintechs.

    Customer
    Third-party risk teams at US fintechs using hosted open models
    Model
    Fee per vendor assessment
  3. Egress Check

    Run open-weight models in a sandbox that logs all network traffic. Replay published traces such as Cohere's and flag any unexplained outbound calls.

    Customer
    Model risk teams at banks
    Model
    Report per model and version

Competition

Early

I found no commercial product that runs continuous two-account canary and cache-timing tests against hosted inference providers and packages the results for bank and fintech third-party risk reviewers. The method itself is public and fairly mature: the Gu et al.

Full competition notes (11 competitors)

I found no commercial product that runs continuous two-account canary and cache-timing tests against hosted inference providers and packages the results for bank and fintech third-party risk reviewers. The method itself is public and fairly mature: the Gu et al. ICML 2025 paper, the CacheProbe preprint, NDSS work on vLLM/SGLang KV-cache timing, and Promptfoo's open-source cross-session leak plugin all cover it. So the harness is not the moat. The opening is to be the independent, repeatable source of evidence. Demand looks real. Cloudflare's recent GLM-5.3 cross-tenant KV cache leak was caught by an outside researcher, not by continuous testing. A 2026 comment letter on the OCC's proposed third-party risk guidance complains that banks have no standard for AI vendor evidence and that every bank sends its own questionnaire. FS-ISAC and similar questionnaires ask questions but attach no empirical tests. Vendor Pack combined with Leak Probe CI is where a new entrant could win. The pitch is a standing, third-party-run isolation attestation, along the lines of a SOC 2 style addendum that is re-tested nightly. Mid-tier inference hosts like Together, Fireworks, DeepInfra, Baseten and the gateways would buy it to shorten bank procurement, and fintech risk teams would accept it in place of custom questionnaires. There are risks. The largest providers already run canary tests in-house and may not want an outsider publishing timing results. Black-box timing probes are noisy, and with only two accounts you can't prove isolation, only fail to find leaks, so the attestation needs careful wording. Pentest firms and red-team platforms like Promptfoo could add the feature cheaply. Egress Check is the weakest of the three ideas. Running open weights offline in a network-logged sandbox is a commodity that NVIDIA OpenShell, OpenSandbox, Azure and Vercel sandboxes already provide. Model weights themselves don't make network calls; serving code does. So this is better folded in as a small feature for model risk teams than sold as a standalone product.

  • Auditing Prompt Caching in Language Model APIs (Gu et al., ICML 2025)

    Academic statistical timing audit. It found global prompt cache sharing across users at seven API providers, including OpenAI. This is the core method behind Leak Probe CI's timing probe, and it is published and reproducible by anyone, but it is not a product.

  • CacheProbe: Auditing Prompt Cache Isolation in Gateway APIs

    May 2026 preprint that applies cache-timing audits to OpenRouter. It reports cache sharing under shared default credentials but not with direct API access or BYOK. More research showing the technique is getting known, but there is no commercial offering.

  • Promptfoo Cross-Session Leak plugin

    Open-source red-team plugin. One simulated user plants data and a second session tries to pull it out. It works at the application level and doesn't use two real tenant accounts or timing analysis. Still, it is the closest packaged tool, and a team could adapt it.

  • Cloudflare Workers AI GLM-5.3 cross-tenant leak disclosure

    Not a competitor. It shows the need is real: 155 responses leaked across tenants through a KV cache bug. Cloudflare checked its fix with the researcher's reproduction script and its own canary-marker tests, so big providers build this kind of testing in-house.

  • RedFox Security multi-tenant AI leakage testing

    Pentest firm that publishes a two-tenant canary method for AI apps. This points to manual consulting engagements as the current alternative to automated nightly testing.

  • Oxyne AI agent tenant isolation testing

    Security testing vendor writing about tenant isolation for AI agents in multi-tenant SaaS. It is aimed at app builders, not inference providers, and doesn't cover cache side channels.

  • FS-ISAC Generative AI Vendor Risk Assessment workbook

    Free Excel questionnaire that banks use to tier due diligence on GenAI vendors. It is the default artifact Vendor Pack would have to plug into. It asks questions but includes no technical test evidence.

  • Batoi community bank AI vendor assessment framework

    Weighted-scoring AI vendor questionnaire for banks. It covers the questionnaire side of Vendor Pack but not empirical isolation testing.

  • Abrigo AI vendor questionnaire

    Bank-focused AI governance vendor checklist built for exam-ready documentation. Same limitation: questionnaire only.

  • NVIDIA NemoClaw / OpenShell sandbox monitoring

    Live view of a sandbox's network connections and blocked egress. It is a general building block that could do what Egress Check proposes. Not aimed at model risk teams.

  • Alibaba OpenSandbox egress sidecar

    Open-source FQDN egress allowlist for sandboxes. Another free building block for Egress Check.

Checked 2026-10-27

Risks

  • Providers may ban this kind of testing in their terms of service
  • Timing measurements on shared infrastructure are noisy
  • If the bug is fixed fast, the urgency fades
  • The Qwen exfiltration claim is publicly disputed, which weakens the egress pitch

Strong tech readiness and team fit; market pull is the weak point (6).

tech 8 · pull 6 · space 7 · fit 8 · build 8

Exposed

Companies that could benefit or be threatened. News and context, not investment advice.

Momentum of its main topic

49 developments this week -2 vs last week
28 Sep: 0 developments29 Sep: 0 developments30 Sep: 0 developments1 Oct: 0 developments2 Oct: 0 developments3 Oct: 0 developments4 Oct: 0 developments5 Oct: 0 developments6 Oct: 0 developments7 Oct: 0 developments8 Oct: 9 developments9 Oct: 8 developments10 Oct: 10 developments11 Oct: 7 developments12 Oct: 9 developments13 Oct: 8 developments14 Oct: 12 developments15 Oct: 7 developments16 Oct: 5 developments17 Oct: 7 developments18 Oct: 8 developments19 Oct: 3 developments20 Oct: 9 developments21 Oct: 11 developments22 Oct: 6 developments23 Oct: 4 developments24 Oct: 12 developments25 Oct: 6 developments26 Oct: 2 developments27 Oct: 8 developments
Stage: Coverage

Sources

  1. Cross-request KV cache exposure in the GLM-5.3 Workers AI model (155 responses)Hacker News
  2. Why Inference Matters 12x More Than Training | YC Paper ClubY Combinator
  3. Cohere says Alibaba’s Qwen model tried to send a file to BeijingTechCrunch AI
  4. Qwen investigation traces releaser/LocalLLaMA
  5. Debunking Cohere's claim of Qwen 3.8 Flash Next uploading to Alibaba remote URLr/LocalLLaMA
  6. Concerning behavior from a popular open-weight AI modelHacker News

Status history

  • 2026-10-27 Flagged as buildable