Private Proving for Enterprises: Integrating TEEs Without Violating Security Policy

Why private proving now

Zero-knowledge proofs (ZKPs) are great for ensuring everything checks out, but there's a catch--they don't stop a prover operator from seeing the hidden witness (you know, those private inputs). That's why many businesses that are diving into privacy-preserving ledgers, identity, or compliance proofs are teaming up ZK with Trusted Execution Environments (TEEs). Think of the TEE as a protective shield for the witness data in action, while remote attestation verifies the environment, and the ZK proof does its thing without spilling any private info.

In Microsoft’s “Confidential Computing Proofs,” the authors lay out a comparison between ZKPs and hardware-based “confidential computing proofs.” They make a solid case that these two are actually best pals: ZK provides public verifiability, while TEEs offer high-throughput privacy for the prover. You can check it out here: (microsoft.com).

What’s Changed in 2024-2025:

Over the next couple of years, there are some notable shifts happening that you might want to keep an eye on. Here’s a quick rundown:

Key Updates

• Economic Shifts: The global economy is expected to see some ups and downs, with inflation rates adjusting and new trade agreements on the horizon.
• Tech Advancements: We’re in for some exciting tech developments! Expect breakthroughs in AI, renewable energy, and possibly even quantum computing.
• Climate Policies: Countries are stepping up their game on climate change initiatives. Look for new regulations and incentives aimed at sustainability.

Important Dates

• April 15, 2024: Tax day - make sure to file your taxes on time!
• November 8, 2024: The U.S. presidential election will be a hot topic that could lead to significant policy shifts.

What to Watch

1. Market Trends: Keep an eye on stock market fluctuations as new policies roll out.
2. Consumer Behavior: Changes in the economy could influence how we shop and spend.
3. Social Movements: Activism around social issues is likely to heat up, shaping public discourse.

Resources

For more detailed insights, check out:

• World Economic Forum
• United Nations Climate Change

Let’s brace ourselves for an interesting couple of years ahead!

• Cloud TEEs have really come a long way from early trials to general availability across both CPU and GPU. You've got Intel TDX and AMD SEV‑SNP VMs that are now pretty much everywhere, and NVIDIA's H100/H200 GPUs are pulling back the curtain on Confidential Computing with device attestation. Plus, Google’s Confidential Space is making it easier with container-level attestation policies. Check it out here: (cloud.google.com)
• On the KMS/HSM front, things are looking good too! These stacks now recognize attestation as a key authorization factor (we're talking AWS KMS, Azure Secure Key Release, and Google Workload Identity Federation + policy). This means you can keep a tight lid on key unwrap strictly to those reliable, production-mode workloads. For more details, have a look: (docs.aws.amazon.com)

The outcome? You can now run provers in TEEs, manage decryption through attestation, and send proofs on-chain--all without needing policy waivers.

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Executive snapshot: where TEEs fit in a ZK architecture

• Threat addressed: Keep prover operators, cloud admins, or anyone with root access from snooping around the witness or intermediate proving state. (docs.cloud.google.com)
• Control: Execute the prover within a TEE (Trusted Execution Environment) and only let remote attestation kick in to hand over witness keys or session secrets. If the measurement, image digest, or “debug” status isn’t spot on, just say no. (docs.aws.amazon.com)
• Evidence: Keep those attestation tokens and KMS audit logs on hand so that risk, compliance teams, and customers can confirm that each proof run was securely hardware-isolated. (docs.aws.amazon.com)

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TEE options for private proving (and what each buys you)

AWS: Nitro Enclaves for strong isolation and KMS‑gated decryption

• So, enclaves are like mini VMs that you create from a main EC2 instance. They operate without any external networking, have no persistent storage, and communicate with the parent instance using vsock-only IPC. This setup really helps to cut down the attack surface, but it does mean that the parent instance has to handle any outgoing traffic. You can find more details about this here.
• When it comes to cryptographic attestation, it’s top-notch! KMS policies can verify attested measurements, like ImageSha384 (PCR0) and other individual PCRs, before they hand out data keys or decrypt any ciphertext. Plus, CloudTrail records keep track of these attestation fields, which is super handy. Check out more information here.
• Let’s talk about practical constraints: you won’t find any GPUs in enclaves, and everything has to fit into the enclave’s RAM. Also, debugging isn’t allowed--if you try to debug an enclave, it just produces zeroed PCRs and fails attestation. Still, this setup works great for CPU-bound tasks, key management, or splitting workloads across multiple enclaves through the parent instance. For more insights, take a look at this article here.

When to Choose It

If you've got highly regulated workloads and need to keep the I/O surface super small, plus want some policy-driven KMS gating--all without switching up your cloud provider--this might be the right fit for you. Check out more details here.

Google Cloud: Confidential VM + Confidential Space for policy‑driven containers (with GPU support)

• CVMs work with either AMD's SEV‑SNP or Intel's TDX. With Confidential Space, you get a tougher OS and a verified container launcher that hands out a signed OIDC token packed with useful details like the container digest, support channel (STABLE/USABLE), debug status, and, in preview, GPU CC mode. You can link these details into IAM through Workload Identity Federation to control access to KMS, Storage, or other external resources. (cloud.google.com)
• The range of regions and hardware is always growing. You can find TDX on C3, SEV and SEV‑SNP on N2D/C3D/C4D, and NVIDIA Confidential Computing with H100 in select zones (like a3‑highgpu‑1g). Don’t forget to check the release notes for the latest on supported zones and any quirks related to attestation (like certain OS images that might mess with attestation temporarily). (cloud.google.com)
• Here are some security tips you can put into action right now: make sure that dbgstat is set to “disabled‑since‑boot,” pin the image_digest in your policy, and stay alert for CPU errata that impacted RDSEED back in early 2025 (there were workarounds rolled out). (docs.cloud.google.com)

When to choose it:

Containerized provers like Halo2, Plonky2, and SP1 are a great option when you need strong policy hooks and the flexibility of optional GPU acceleration in CC mode. You can find more about it here.

Azure: Confidential VMs + Secure Key Release (SKR) from (Managed) HSM

• CVM families have your back with support for AMD SEV‑SNP and Intel TDX, plus there's a cool H100‑backed confidential series. One of the standout features is Secure Key Release: Azure Key Vault (Premium/Managed HSM) can hand over an HSM-protected key only to a CVM that checks out according to your policy. This includes claims like TEE type and compliance status, all verified through Microsoft Azure Attestation. (learn.microsoft.com)
• With the SKR policy grammar, you can set specific claims (like “x‑ms‑isolation‑tee.x‑ms‑attestation‑type == sevsnpvm” along with compliance flags) and require that the target presents an encryption key that stays locked within the attested runtime. Just a heads-up, Managed HSM is FIPS 140‑3 Level 3 validated, so you know it’s secure. (docs.azure.cn)

When to Choose It

If you’re in need of FIPS-validated HSMs, top-notch attested key export for your enterprise, and seamless integration with Azure Active Directory (AAD) and Role-Based Access Control (RBAC), then this is the way to go. Learn more here.

NVIDIA H100/H200: GPU Confidential Computing for prover acceleration

• The H100 and H200 GPUs come with some pretty cool features like GPU-side memory encryption, supported by ECC‑384, and remote attestation. NVIDIA’s Remote Attestation Service (NRAS) is there to verify those GPU attestation reports. Just remember, the CVMs need to check the GPU's certificate chain and revocation status before they can trust the GPU. You can read more about it here.
• If you're working on GCP, you’ll find that Confidential Space tokens include an nvidia_gpu.cc_mode claim (in preview) which confirms that the GPU was running with CC enabled. This is a handy way to make sure that proofs are generated only on CC GPUs. Check it out here.

When to pick it: If you're dealing with large provers that face MSM/FFT performance slows and could really take advantage of some GPU acceleration, plus you need to keep your model parameters or witnesses secure throughout the whole process. Check out more details here.

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Reference architectures you can deploy this quarter

A. AWS “air‑gapped” private prover with KMS‑gated secrets (no GPU)

1. Start by creating an enclave image file (EIF) that includes your prover binary along with a minimal runtime.
2. Next, fire up the enclave from a Nitro-enabled parent instance. When it boots up, make sure to request an attestation document that includes the signed image digest in the PCRs.
3. Now it's time to call AWS KMS with cryptographic attestation. The KMS policy will let you perform Decrypt/GenerateDataKey actions only if the ImageSha384 (PCR0) and, if needed, PCR1 and others align with your production EIF. The response you get back is encrypted with the enclave's public key and can only be used within the enclave.
4. Once you're inside the enclave, decrypt the witness, proceed with the proving step, and then send just the proof back to the parent via vsock. Finally, make sure to publish that proof on-chain. (Check out the details here)

Policy Nucleus (Conceptual):

The concept of a policy nucleus is all about identifying the core elements that shape and guide specific policies. It's the foundational framework that helps us understand how different parts come together to form effective strategies. Here’s a breakdown of what this looks like:

Key Components

1. Core Values: At the heart of any policy nucleus are the fundamental values that drive decision-making. These could be anything from social justice to economic growth - whatever aligns with the goals of the policy.
2. Stakeholder Engagement: Involving the right people is crucial. Engaging stakeholders ensures that diverse perspectives are taken into account, making the policy more robust and inclusive.
3. Data-Driven Insights: Good policies are backed by solid data. Analyzing relevant information helps in making informed choices and predicting outcomes.
4. Implementation Strategy: Planning how to put the policy into action is essential. This includes outlining steps, resources needed, and timelines.
5. Evaluation Metrics: Finally, measuring success is key. Setting clear metrics allows us to determine if the policy is working and where adjustments might be needed.

Visual Representation

Here's a little diagram to illustrate how these components interact:

    +---------------------+
    |                     |
    |   Core Values       |
    |                     |
    +----------+----------+
               |
               |
    +----------v----------+
    |                     |
    | Stakeholder         |
    | Engagement          |
    |                     |
    +----------+----------+
               |
               |
    +----------v----------+
    |                     |
    | Data-Driven         |
    | Insights            |
    |                     |
    +----------+----------+
               |
               |
    +----------v----------+
    |                     |
    | Implementation      |
    | Strategy            |
    |                     |
    +----------+----------+
               |
               |
    +----------v----------+
    |                     |
    | Evaluation          |
    | Metrics             |
    |                     |
    +---------------------+

Conclusion

Understanding the policy nucleus gives us a clearer view of how to craft effective policies that resonate with people’s needs. By keeping these elements in mind, we can work towards more meaningful and impactful outcomes.

• kms:RecipientAttestation:ImageSha384 should match your EIF digest (PCR0)
• kms:RecipientAttestation:PCR1 should correspond to your kernel/bootstrap hash
• If the attestation is missing or invalid, deny access; make sure to audit CloudTrail for those fields. Check out the details in the AWS documentation.

Operational Guardrails:

When it comes to running a business smoothly, operational guardrails are your best friends. They help keep everything on track and ensure that everyone is on the same page. Here’s what you need to know:

What Are Operational Guardrails?

Operational guardrails are like guidelines or boundaries that help teams understand how to achieve their goals while staying compliant and efficient. They provide clarity, minimize risks, and keep the workflow organized.

Why Are They Important?

• Clarity: They give everyone a clear understanding of what’s expected.
• Risk Management: They help in identifying and mitigating potential risks before they turn into big issues.
• Efficiency: By establishing processes, they streamline operations, saving time and resources.

Key Components of Operational Guardrails:

1. Policies and Procedures: Clear documentation on how things should be done.
2. Decision-Making Framework: Guidelines on who can make what decisions and under what circumstances.
3. Performance Metrics: Specific metrics that help measure success and areas for improvement.
4. Training and Support: Resources and training programs to ensure everyone knows these guardrails and can apply them effectively.

How to Implement Operational Guardrails:

• Involve Your Team: Get input from team members to make sure the guardrails are practical and useful.
• Communicate Clearly: Make sure everyone knows about the guardrails and understands them.
• Review Regularly: As your business evolves, so should your guardrails. Regularly assess and update them as needed.

Conclusion

Operational guardrails are essential for any organization that wants to thrive. By providing a framework for action, they help ensure that everyone can work effectively towards common goals while minimizing risks. So, if you haven’t set up your guardrails yet, it’s time to get started!

For more resources and in-depth information, check out this article on operational excellence.

• It's best to avoid running debug enclaves since their PCRs are always zero, and they won't pass the policy checks.
• Make sure to set memory sizing properly to hold the entire proving state in the enclave's RAM. Also, steer clear of logging any secrets over vsock. You can find more details in the AWS documentation.

Where it shines: static circuits, KMS‑wrapped witnesses, and regulated environments where having “no external network” is a big plus. (aws.amazon.com)

B. GCP GPU‑accelerated private proving with Confidential Space + H100 CC

1. First off, package your prover as a container and sign it, maybe using something like Cosign.
2. Next up, get a Confidential Space workload running on a CVM that’s got an NVIDIA H100 in CC mode (check out a3‑highgpu‑1g in the supported zones).
3. The launcher will then grab an attestation OIDC token that includes the container image_digest, support_attributes (just look for STABLE), dbgstat, and in preview, the nvidia_gpu.cc_mode claim.
4. Make sure to set up your IAM with Workload Identity Federation, so that KMS/Storage only accepts tokens where the assertions line up with your attestation policy (like a specific image_digest and gpu.cc_mode set to ON).
5. Finally, the prover will fetch the encrypted witness, use a short-lived KMS DEK based on those conditions, generate the proof on the GPU, write out the proof, and then wipe the DEK clean. (cloud.google.com)

Why It’s Enterprise-Ready:

When we talk about being "enterprise-ready," we mean that a solution is designed to handle the complex needs of larger organizations. Here are a few key reasons why our platform fits the bill:

• Scalability: As your business grows, our platform can easily scale with you, ensuring you don’t have to worry about outgrowing your tools.
• Security: We prioritize security with robust protocols in place, including encryption and compliance with industry standards, keeping your sensitive data safe.
• Integration: Seamlessly connect with your existing systems and tools. Our platform supports a variety of integrations, making it easy to incorporate into your workflow.
• Support: Receive dedicated support options tailored for enterprises, so you always have the assistance you need when you need it.
• Customization: Tailor features to fit your unique business processes. We understand that one size doesn't fit all, especially in large organizations.

For more details about our enterprise solutions, check out our Enterprise Solutions page!

• Make sure to have claim-rich, auditable policies covering both the container and the platform, not just the VM family.
• Keep an eye on the documented caveats and release notes. For instance, certain OS images had a hiccup with remote attestation in mid-2025. It’s best to stick with supported images (like Ubuntu 24.04) until that gets sorted out. (docs.cloud.google.com)

C. Azure CVM with Secure Key Release (HSM‑attested key unwrap)

1. First, you’ll want to create an exportable key in either Key Vault Premium or Managed HSM. Make sure to add an SKR policy that requires a Microsoft Azure Attestation (MAA) token with specific claims, like sevsnpvm and “azure-compliant-cvm.”
2. Once you have that set up, the attested CVM can request a key release. Key Vault will check the token against your policy and encrypt the key using a runtime public key provided by the TEE. Only the CVM will be able to unwrap it.
3. Now, the prover runs inside the CVM, using the released key to decrypt the witness, generate the proof, and then toss the key away. Plus, Managed HSM has FIPS 140‑3 Level 3 validation for audits. You can find more details here.

Why it's compelling: The HSM-backed policy grammar along with a solid enterprise compliance posture really shines, thanks to the detailed “environment assertion” checks integrated right into the HSM release workflow. You can check out more about it here.

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Enforcing “no policy exceptions” with attestation

To set up private proving without the need for security waivers, make sure your controls are designed so that keys, data, and egress are pretty much useless unless the prover has been properly attested:

• Bind decryption to attestation
  • AWS: You can set up kms:RecipientAttestation:ImageSha384/PCRn conditions. This way, KMS will only give you ciphertext that's sealed to the enclave's key. Check out more details here.
  • GCP: Leverage Workload Identity Federation to map your token claims. You’ll only get access if assertion.swname is set to CONFIDENTIAL_SPACE, the image_digest checks out, and support_attributes include STABLE. Get the full scoop here.
  • Azure: You can implement an SKR policy to enforce sevsnpvm and compliance claims, ensuring that resources are only released to that specific environment. Dive deeper into this here.
• Need to have “production mode”
  • GCP tokens contain dbgstat; make sure disabled‑since‑boot is set up. Just a heads up, Nitro debug enclaves aren’t applicable for cryptographic attestation. Check out the details here.
• Pin supply chain artifacts
  • GCP tokens contain the image_digest and image_signatures key_id, so make sure to pin those in your policy. For AWS, PCR0 handles the EIF image hash. Check it out here: (cloud.google.com)
• Log and prove it
  • CloudTrail provides attestation fields for Nitro-gated KMS calls, making it super easy to track things. On the GCP side, you'll find logs that capture the subject (like the VM selfLink) and the federated identity used for every access. Don’t forget to archive those attestation tokens alongside the proofs to ensure everything is auditable from end to end. (docs.aws.amazon.com)

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GPU proving with confidentiality: what to verify

If you're looking to speed up proof verification on GPUs, it’s a good idea to also expand the trust chain right to the device itself.

• Check the NVIDIA device identity and attestation
  • Start by fetching the device certificate (ECC‑384) and make sure it checks out with the NVIDIA CA. Then, verify the OCSP and validate the attestation reports using NRAS. Only accept the GPU after you’ve done all that. (developer.nvidia.com)
• Utilize platform signals when you can
  • If you’re on GCP, ensure you assert nvidia_gpu.cc_mode == ON in the Confidential Space token policy. (cloud.google.com)

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Emerging practices we recommend (and implement for clients)

• Short-lived, nonce-bound attestation tokens
  • Always ask for fresh attestation with a unique nonce to dodge replay issues; make those time-limited tokens your best friends. AWS Nitro attestation comes with a nonce, and GCP tokens have support for eat_nonce claims. (docs.bluethroatlabs.com)
• Prohibit “debuggable” builds by policy
  • Make sure to enforce dbgstat == disabled and block any dev builds from getting access to keys. If you spot Nitro debug PCR zeros, that's a big red flag. (docs.aws.amazon.com)
• Circuit-prover separation of duties
  • Keep your circuit definitions and public parameters safely stored in source control; send out a prover container with a policy-pinned digest. Whenever you rotate it, just update the policy digest and attest again. (cloud.google.com)
• Attestation-aware KMS/HSM schemas
  • AWS: KMS keys that can only decrypt for certain PCR measurements;
  • Azure: SKR policies that link releases to MAA claims;
  • GCP: IAM conditions on image_digest/STABLE, with federated identities that are limited to that digest. (docs.aws.amazon.com)
• Side-channel hygiene in TEEs
  • Aim for constant-time cryptographic libraries; keep secrets out of your logs; and steer clear of 16/32-bit RDSEED instructions that could give you trouble based on the 2025 advisories--stick with 64-bit or platform RNG instead. (cloud.google.com)
• Multi-vendor attestation verification
  • If you need a single verifier that works across AMD and Intel, check out Intel Trust Authority, which recently added preview support for attesting AMD SEV-SNP on Azure. (docs.trustauthority.intel.com)

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Concrete example: Policy snippets you can adapt

Below are some minimal policy fragments that you’d tweak in a production setting. The key idea here is to use the attestation facts as the main checkpoint.

• AWS KMS Condition Keys (Quick Overview):
  • You can allow actions like Decrypt or GenerateDataKey only if kms:RecipientAttestation:ImageSha384 matches your EIF’s SHA‑384 digest. Plus, you might want to make sure that PCR1 lines up with the enclave kernel hash. Don't worry, CloudTrail will keep track of these details for audits. Check out the fine print in the AWS docs.
• Here are some cool IAM condition ideas for GCP Confidential Space:
  • Check if assertion.swname is set to "CONFIDENTIAL_SPACE"
  • Look for "STABLE" in assertion.submods.confidential_space.support_attributes
  • Make sure assertion.submods.container.image_digest matches "sha256:…"
  • For those systems that support it, verify that assertion.submods.nvidia_gpu.cc_mode is "ON" (docs.cloud.google.com)
• The Azure SKR policy has some key claims to keep in mind:
  • It checks that x‑ms‑isolation‑tee.x‑ms‑attestation‑type is set to "sevsnpvm"
  • It verifies that x‑ms‑isolation‑tee.x‑ms‑compliance‑status is equal to "azure‑compliant‑cvm"
  • It only allows access to the runtime public key presented for the session (that’s x‑ms‑runtime/keys). You can dive deeper into this here.

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“Do we lose performance?” What our clients should expect

• CPU TEEs (SEV‑SNP/TDX): There’s a bit of overhead with memory encryption and attestation, but honestly, it's usually pretty minor compared to the time it takes to prove things. Just keep an eye on those release notes for any patches that might temporarily tweak performance. (cloud.google.com)
• GPU CC (H100/H200): NVIDIA’s Confidential Computing mode keeps your data locked up tight in GPU memory. If you get your batching just right, you can expect pretty close to native throughput. Just remember to confirm device attestation before you add that GPU to your trust boundary. (developer.nvidia.com)

Tip: Go ahead and profile those MSM/FFT phases, and don’t forget to batch your proof jobs! This way, you can spread out those TEE setup costs over bigger workloads, making it way more efficient.

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Implementation checklist (prover teams)

• Governance
  • Identify who owns the attestation policies and set up procedures for recording digest pinning and rotation.
  • Get the green light on allowed TEEs (like Nitro Enclaves, Confidential Space TDX/SNP, Azure SKR) and list them in the security catalog. (learn.microsoft.com)
• Supply chain
  • Make sure to sign containers; pin the image_digest/key_id in the attestation policy, and set it to fail closed if there's a mismatch. (cloud.google.com)
• Keys and secrets
  • For AWS: Use KMS RecipientAttestation keys;
  • For GCP: Check out Workload Identity Federation with attestation assertions;
  • For Azure: Use the SKR from Managed HSM along with MAA claims. (docs.aws.amazon.com)
• Attestation
  • Always require a nonce; keep tokens cached for only a few minutes, and make sure to archive tokens with proof artifacts. (docs.cloud.google.com)
  • For GPU workloads: Verify NVIDIA device certs, check OCSP, and review NRAS reports before you turn on CC mode workloads. (developer.nvidia.com)
• Operations
  • Stick to a “no debug” policy; keep an eye on any policy denials and send alerts if proof is generated outside of TEEs.
  • Always use supported OS/kernel versions for attestation, and take a peek at the release notes before you think about upgrading. (docs.cloud.google.com)

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Real‑world momentum: private proving at scale

The industry is really starting to focus on “ZK proof generation inside TEEs.” A cool example of this is Succinct’s Private Proving. Their SP1 zkVM runs right inside TEEs with some GPU computation, keeping the witness safe and only spitting out proofs. This method shows how we can mix ZK verifiability with hardware-level privacy without the hassle of rewriting prover stacks. It’s all packed up nicely as a Docker container, deployed onto a TEE platform, and managed through attestation. Check it out here: (blog.succinct.xyz)

When you're dealing with GPU-backed workloads, it's super important to make sure you have dual attestation, which means using both CPU TEE and GPU CC. Google makes it easy by showing GPU CC status as a token claim in Confidential Space. On the other hand, NVIDIA has your back with device certificates and NRAS for verification. These are the clear signals that auditors are now looking for in regulated deployments. Check it out here: (cloud.google.com)

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How 7Block Labs engages

• Architecture and vendor selection: We’ll help you match your circuits and SLAs with the best TEE stack for your needs, whether it’s Nitro, Confidential Space, Azure SKR, or GPU CC.
• Policy engineering: We create KMS/HSM policies designed to stop decryption outside of verified workloads, and we make sure those checks are seamlessly integrated into your CI/CD process.
• Attestation pipelines: We set up attestation capture, verification, and archiving for each run, all while keeping your proofs private, so you can confidently show that your proofs were generated securely.

If you're looking for a proof‑of‑concept, we usually have an end‑to‑end private prover ready for you in about 3 to 6 weeks. This will include everything from policy and attestation to audit artifacts.

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Key takeaways for decision‑makers

• Just a heads-up: ZK on its own doesn’t keep witnesses hidden from the prover operator, but TEEs do. By using attestation-gated key release, you can really make “privacy by default” a reality. Check it out here: (microsoft.com).
• Good news! You don’t need any fancy waivers anymore. All three big cloud providers now back attestation-aware authorization paths that meet strict security requirements. Get the details here: (docs.aws.amazon.com).
• For better performance, combine CPU TEEs with GPU Confidential Computing and make sure to pin those states in your policy. Just remember to validate device attestation before you trust that acceleration. Learn more here: (developer.nvidia.com).

Private proving is all set for production--and for policy--and we’re here to help you roll it out with confidence.