Azureml K3s Compute Target Setup
microsoft/physical-ai-toolchain
Set up a K3s cluster on an NVIDIA GPU host, connect it to Azure Arc, and configure Azure ML to use it as a Kubernetes compute target.
Guidance for Azure Confidential Computing — protecting data in use through hardware-based Trusted Execution Environments (TEEs).
Install Azure Confidential Computing
$ npx skills add vinayaklatthe/microsoft-security-skills --skill azure-confidential-computing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install vinayaklatthe/microsoft-security-skills azure-confidential-computing --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/vinayaklatthe/microsoft-security-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/azure-confidential-computing .claude/skills/azure-confidential-computing && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "azure-confidential-computing" agent skill from https://github.com/vinayaklatthe/microsoft-security-skills/tree/main/skills/azure-confidential-computing into .claude/skills/azure-confidential-computing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-confidential-computing", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/vinayaklatthe/microsoft-security-skills/tree/main/skills/azure-confidential-computingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add vinayaklatthe/microsoft-security-skills --skill azure-confidential-computing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install vinayaklatthe/microsoft-security-skills azure-confidential-computing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vinayaklatthe/microsoft-security-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/azure-confidential-computing .agents/skills/azure-confidential-computing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "azure-confidential-computing" agent skill from https://github.com/vinayaklatthe/microsoft-security-skills/tree/main/skills/azure-confidential-computing into .agents/skills/azure-confidential-computing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-confidential-computing", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add vinayaklatthe/microsoft-security-skills --skill azure-confidential-computing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install vinayaklatthe/microsoft-security-skills azure-confidential-computing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vinayaklatthe/microsoft-security-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/azure-confidential-computing .cursor/skills/azure-confidential-computing && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "azure-confidential-computing" agent skill from https://github.com/vinayaklatthe/microsoft-security-skills/tree/main/skills/azure-confidential-computing into .cursor/skills/azure-confidential-computing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-confidential-computing", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/vinayaklatthe/microsoft-security-skills.git --path skills/azure-confidential-computing--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add vinayaklatthe/microsoft-security-skills --skill azure-confidential-computing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install vinayaklatthe/microsoft-security-skills azure-confidential-computing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vinayaklatthe/microsoft-security-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/azure-confidential-computing .gemini/skills/azure-confidential-computing && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "azure-confidential-computing" agent skill from https://github.com/vinayaklatthe/microsoft-security-skills/tree/main/skills/azure-confidential-computing into .gemini/skills/azure-confidential-computing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-confidential-computing", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install vinayaklatthe/microsoft-security-skills azure-confidential-computingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add vinayaklatthe/microsoft-security-skills --skill azure-confidential-computing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/vinayaklatthe/microsoft-security-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/azure-confidential-computing .github/skills/azure-confidential-computing && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "azure-confidential-computing" agent skill from https://github.com/vinayaklatthe/microsoft-security-skills/tree/main/skills/azure-confidential-computing into .github/skills/azure-confidential-computing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-confidential-computing", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add vinayaklatthe/microsoft-security-skills --skill azure-confidential-computing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install vinayaklatthe/microsoft-security-skills azure-confidential-computing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vinayaklatthe/microsoft-security-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/azure-confidential-computing .opencode/skills/azure-confidential-computing && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "azure-confidential-computing" agent skill from https://github.com/vinayaklatthe/microsoft-security-skills/tree/main/skills/azure-confidential-computing into .opencode/skills/azure-confidential-computing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-confidential-computing", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
azure-confidential-computing- GitHub stars
- 175
- Token cost
- ~2.4k tokens
- SKILL.md length
- 976 words
- Files
- 1
- Skills in repo
- 50
- Repo updated
- First seen
- Licence
- MIT
At a glance
Guidance for Azure Confidential Computing — protecting data in use through hardware-based Trusted Execution Environments (TEEs).
- Works in 8 steps: Validate the threat model. Confidential… → Pick the right form factor. → Stand up Microsoft Azure Attestation.… → …
- General data-at-rest CMK (use azure-key-vault)
- SKILL.md covers When to use, Form factors, Approach and Guardrails, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Azure Confidential Computing is an agent skill from vinayaklatthe/microsoft-security-skills. Guidance for Azure Confidential Computing — protecting data in use through hardware-based Trusted Execution Environments (TEEs). Covers Confidential VMs (AMD SEV-SNP, Intel TDX), Confidential containers on AKS (Kata + AMD SEV-SNP), confidential GPU VMs (NVIDIA H100 with TDX), Azure Key Vault Managed HSM and Premium with secure-key-release for confidential workloads, attestation (Microsoft Azure Attestation service), confidential ledger, scenarios (multi-party data sharing, regulated workload isolation, AI…
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in DevOps & Cloud. It works with Microsoft Azure, Azure Key Vault and NVIDIA AI Platform. The repository describes itself as: Curated Microsoft Security skills for AI agents - Defender, Sentinel, Entra, Purview, Intune, Security Copilot. The licence is MIT.
When your agent uses it
- General data-at-rest CMK (use azure-key-vault)
- Application encryption SDK only
- Non-Azure TEE design
Example prompts
- “/azure-confidential-computing”
Workflow steps
8 steps, taken from the first numbered list in SKILL.md.
- Validate the threat model. Confidential computing protects against
- Pick the right form factor.
- Stand up Microsoft Azure Attestation. The MAA service issues signed attestation
- Wire secure key release (SKR). Azure Key Vault Premium / Managed HSM supports
- Confidential containers on AKS — use the Confidential Container add-on.
- Confidential AI patterns. Two common shapes
- Confidential Ledger for high-integrity audit (regulator log, IoT trust). Don't
- Operate. Monitor attestation failures (firmware drift, hardware updates).
What it can do on your machine
Read from SKILL.md and the folder at commit 15f16df. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
learn.microsoft.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Azure Confidential Computing loads about 2.4k tokens when it runs. Until then it costs about 262 tokens; SKILL.md has 976 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from vinayaklatthe/microsoft-security-skills at commit 15f16df, republished under its MIT licence (© vinayaklatthe). 976 words, ~2,397 tokens.
Download SKILL.mdSave it as
.claude/skills/azure-confidential-computing/SKILL.md (or your agent's skills folder).- name
- azure-confidential-computing
- description
- Guidance for Azure Confidential Computing — protecting data in use through hardware-based Trusted Execution Environments (TEEs). Covers Confidential VMs (AMD SEV-SNP, Intel TDX), Confidential containers on AKS (Kata + AMD SEV-SNP), confidential GPU VMs (NVIDIA H100 with TDX), Azure Key Vault Managed HSM and Premium with secure-key-release for confidential workloads, attestation (Microsoft Azure Attestation service), confidential ledger, scenarios (multi-party data sharing, regulated workload isolation, AI training on sensitive data), key-release policies tying secrets to attested TEE state, and decision criteria vs CMK/Customer Key. WHEN: Azure Confidential Computing, AMD SEV-SNP, Intel TDX, confidential VM, confidential AKS container, confidential GPU H100, Azure Attestation, secure key release, multi-party computation, confidential AI, encrypted memory Azure, hardware enclave Azure. DO NOT USE for general data-at-rest CMK (use azure-key-vault), application encryption SDK only, or non-Azure TEE design.
- license
- MIT
- metadata.author
- Microsoft
- metadata.version
- 0.1.0
Azure Confidential Computing
Confidential computing is the third pillar of data protection — data in use — complementing encryption at rest and in transit. Azure Confidential Computing uses hardware-based Trusted Execution Environments (TEEs) so workloads run on encrypted memory the host (and Microsoft) cannot inspect, with cryptographic attestation to prove the TEE state to a remote relying party before secrets are released.
When to use
- Multi-party data collaboration where parties must compute on each other's data without seeing it (clean rooms, fraud consortia, joint analytics).
- Regulated workloads requiring isolation from cloud operator access (defense, certain financial / healthcare scenarios).
- Sensitive AI training/inference where model weights or training data are crown jewels.
- Cryptographic operations that must be hardware-rooted with attestation evidence.
Do not use this skill for ordinary data-at-rest CMK (azure-key-vault), generic app
encryption, or non-Azure TEE / Intel SGX-only designs.
Form factors
| Form factor | Hardware | Best for |
|---|---|---|
| Confidential VMs (DCasv5/ECasv5) | AMD SEV-SNP | Lift-and-shift Linux/Windows workloads with whole-VM TEE |
| Confidential VMs (DCesv5/ECesv5) | Intel TDX | Trust-domain isolation for VMs |
| Confidential containers on AKS | Kata Containers + AMD SEV-SNP | Container workloads, per-pod TEE |
| Confidential GPU VMs (NCC H100 v5) | NVIDIA H100 + Intel TDX | Confidential AI training/inference |
| App-enclave (Intel SGX, DCsv2/3) | Intel SGX | Targeted enclaves; legacy pattern, less common in new builds |
| Azure Confidential Ledger | Hardware-backed append-only ledger | Tamper-evident audit logs |
Approach
Validate the threat model. Confidential computing protects against:
- Cloud operator (host admin) memory inspection.
- Co-tenant side-channel reads (within hardware mitigation limits).
- Snapshot/disk-image exfiltration combined with memory dump. It does not protect against application bugs, supply-chain compromise of your own code, or insider access at the customer.
Pick the right form factor.
- Existing VM workload moving sensitive without code changes → Confidential VM (SEV-SNP) is the easiest lift.
- K8s cluster with mixed sensitivity → Confidential containers on AKS, scoping pods that need TEE.
- Confidential GPU (LLM training/inference on sensitive data) → NCC H100 v5.
- Multi-party computation with secret protocol → enclave-aware code with SGX (only where you need finer-grained TEE than whole-VM).
Stand up Microsoft Azure Attestation. The MAA service issues signed attestation tokens describing the TEE state (CPU model, firmware version, security version). Relying parties (your apps, Key Vault) verify these tokens before trusting the workload.
Wire secure key release (SKR). Azure Key Vault Premium / Managed HSM supports key-release policies that gate
releaseoperations on a verified MAA token. The workflow:- Confidential workload requests an attestation from MAA.
- Workload presents the token to Key Vault.
- Key Vault validates against the configured policy (allowed TEE type, firmware version, owner identity).
- Key is released into the TEE memory. This is the foundation for "even Microsoft cannot read this key — only the right workload running on the right hardware can use it."
Confidential containers on AKS — use the Confidential Container add-on. Configure pod security with attestation-aware init containers; sensitive secrets pulled via SKR after pod attestation.
Confidential AI patterns. Two common shapes:
- Confidential inference: model weights remain encrypted on disk; loaded into TEE memory; client traffic terminates inside TEE. Used for proprietary models.
- Confidential training: training data uploaded encrypted; key released only to attested training job; trained model artifacts encrypted to data owner's key.
- Multi-party: each party's data and the model in separate (or shared) TEE; output released only with attested evidence.
Confidential Ledger for high-integrity audit (regulator log, IoT trust). Don't use for high-throughput general logging — it's append-only, blockchain-backed, higher latency.
Operate. Monitor attestation failures (firmware drift, hardware updates). Maintain an SKR policy review cadence — security version numbers tighten over time.
Show full SKILL.md (396 more words)Show less
Guardrails
- Confidential computing is not a silver bullet. Application security, supply-chain hygiene, and identity remain primary. TEEs raise the bar against the host operator, not against you.
- Key-release policies must include security-version-number floors. Otherwise an outdated/vulnerable firmware passes attestation and gets keys.
- Confidential VMs have feature gaps with regular VMs. Validate snapshot, backup, ASR, custom extensions before commit.
- Performance overhead is small but real. Memory encryption costs a few percent; confidential GPU has additional overhead. Benchmark.
- Confidential containers in AKS require careful image design. Don't bake secrets; use SKR.
- Some regions / SKUs are limited. Confidential GPU and TDX-VM SKUs aren't everywhere. Plan per region.
- Don't conflate Customer Key / CMK with confidential computing. They solve different problems (key custody for data-at-rest vs runtime memory protection).
- Attestation evidence is time-bound. Tokens expire; design refresh into the app.
Common anti-patterns
- "Confidential VM with the secret hardcoded in the image" — TEE protects memory at runtime, not your image. Use SKR.
- "SKR policy allowing any AMD SEV-SNP without firmware floor" — vulnerable firmware accepted; defeats the model.
- "Confidential container as a generic 'extra security' choice" — operational complexity without commensurate threat-model benefit. Reserve for clear sensitive workloads.
- "Confidential ledger as an append-only log store" — wrong throughput class. Use it for high-integrity, low-volume regulator/audit chains.
- "SGX-only design forced into a whole-VM use case" — code-rewrite cost; use Confidential VM.
- "Snapshot + restore on Confidential VM without testing" — workflow may not preserve attested state expectations; test.
- "Marketed confidential computing as 'encryption stronger than CMK'" — different control category. Communicate accurately.
Example prompts
Architect a multi-party fraud consortium where 4 banks submit encrypted data and a joint model trains in a Confidential GPU VM with attestation-gated key release.Lift-and-shift a regulated Linux workload to Confidential VM (SEV-SNP) with backup and DR validation.Confidential AKS cluster: which pods need TEE, how to wire SKR for per-pod secrets, attestation flow.Configure Key Vault Managed HSM with an SKR policy gated on Confidential VM attestation with firmware floor.Compare Confidential VM (SEV-SNP) vs (TDX) for our workload mix.Confidential inference for a proprietary LLM on Confidential GPU H100 — design.Decide: Customer Key vs Confidential Computing for a sovereignty requirement.
Microsoft Learn
- Confidential computing overview: https://learn.microsoft.com/azure/confidential-computing/overview
- Confidential VMs: https://learn.microsoft.com/azure/confidential-computing/confidential-vm-overview
- AMD SEV-SNP CVMs: https://learn.microsoft.com/azure/confidential-computing/virtual-machine-solutions-amd
- Intel TDX CVMs: https://learn.microsoft.com/azure/confidential-computing/tdx-confidential-vm-overview
- Confidential containers on AKS: https://learn.microsoft.com/azure/confidential-computing/confidential-containers-on-aks-preview
- Confidential GPU (NCC H100 v5): https://learn.microsoft.com/azure/confidential-computing/confidential-vm-overview#confidential-vms-with-gpu
- Microsoft Azure Attestation: https://learn.microsoft.com/azure/attestation/overview
- Secure key release: https://learn.microsoft.com/azure/key-vault/keys/policy-grammar
- Confidential Ledger: https://learn.microsoft.com/azure/confidential-ledger/overview
- Confidential AI scenarios: https://learn.microsoft.com/azure/confidential-computing/confidential-ai
© vinayaklatthe, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/azure-confidential-computing of vinayaklatthe/microsoft-security-skills.
Open the folder on GitHubat commit 15f16df
Compare with similar skills
Azure Confidential Computing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Azure Confidential Computing this skillvinayaklatthe/microsoft-security-skills | 175 | — | ~2.4k | Automated safety check: Pass | MIT | |
| Azureml K3s Compute Target Setupmicrosoft/physical-ai-toolchain | 126 | — | ~5.7k | Automated safety check: Notes | MIT | |
| Azsdk Common Live And Recorded TestsAzure/azure-sdk-tools | 134 | — | ~1.5k | Automated safety check: Notes | MIT | |
| Environment Deploymentmicrosoft/physical-ai-toolchain | 126 | — | ~5.9k | Automated safety check: Pass | MIT | |
| Managing Workflow Secretsbitwarden/ai-plugins | 155 | — | ~4k | Automated safety check: Pass | Custom licence | |
| Azure Keyvaultsickn33/agentic-awesome-skills | 47k | 2 repos | ~3.2k | Automated safety check: Pass | MIT |
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Questions about Azure Confidential Computing
What does Azure Confidential Computing do?
Guidance for Azure Confidential Computing — protecting data in use through hardware-based Trusted Execution Environments (TEEs). Azure Confidential Computing is an agent skill from vinayaklatthe/microsoft-security-skills. Guidance for Azure Confidential Computing — protecting data in use through hardware-based Trusted Execution Environments (TEEs).
When should I use Azure Confidential Computing?
Azure Confidential Computing fits situations like: general data-at-rest CMK (use azure-key-vault); application encryption SDK only; non-Azure TEE design.
How do I install Azure Confidential Computing in Claude Code?
Run `npx skills add vinayaklatthe/microsoft-security-skills --skill azure-confidential-computing -a claude-code`. Or copy the skill folder (skills/azure-confidential-computing in vinayaklatthe/microsoft-security-skills) into .claude/skills/azure-confidential-computing in your project. Claude Code loads it when a task matches its description.
How do I install Azure Confidential Computing in Codex?
Run `npx skills add vinayaklatthe/microsoft-security-skills --skill azure-confidential-computing -a codex`. Or copy the skill folder (skills/azure-confidential-computing in vinayaklatthe/microsoft-security-skills) into .agents/skills/azure-confidential-computing in your project. Codex loads it when a task matches its description.
Can I use Azure Confidential Computing in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add vinayaklatthe/microsoft-security-skills --skill azure-confidential-computing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-confidential-computing, .gemini/skills/azure-confidential-computing, .github/skills/azure-confidential-computing and .opencode/skills/azure-confidential-computing in your project.
What does Azure Confidential Computing need to run?
SKILL.md names no scripts, command-line tools or credentials: Azure Confidential Computing is instructions for the agent only.
Does Azure Confidential Computing access the network?
SKILL.md names 1 domain. As links in the text: learn.microsoft.com. This is read from the text; nothing was executed.
Is Azure Confidential Computing safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Azure Confidential Computing use?
Azure Confidential Computing is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Azure Confidential Computing use?
About 2.4k tokens (SKILL.md is roughly 9.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Azure Confidential Computing?
Skills that share tags, products or a category with Azure Confidential Computing: Azureml K3s Compute Target Setup (microsoft/physical-ai-toolchain, 126 stars), Azsdk Common Live And Recorded Tests (Azure/azure-sdk-tools, 134 stars), Environment Deployment (microsoft/physical-ai-toolchain, 126 stars) and Managing Workflow Secrets (bitwarden/ai-plugins, 155 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Azure Confidential Computing?
vinayaklatthe (a GitHub user) maintains it in vinayaklatthe/microsoft-security-skills, which has 175 GitHub stars. The repository holds 50 skills in this directory. The repository was last updated on June 18, 2026.
Source: vinayaklatthe/microsoft-security-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.