azure-keyvault-py

$npx mdskill add microsoft/skills/azure-keyvault-py

Manage Azure Key Vault secrets, keys, and certificates securely.

  • Solves secure storage and management of secrets, keys, and certificates.
  • Depends on Azure Key Vault SDK and Azure Identity for authentication.
  • Uses DefaultAzureCredential for seamless local and production authentication.
  • Delivers results via Python client operations like get, set, and delete.

SKILL.md

.github/skills/azure-keyvault-pyView on GitHub ↗
---
name: azure-keyvault-py
description: |
  Azure Key Vault SDK for Python. Use for secrets, keys, and certificates management with secure storage.
  Triggers: "key vault", "SecretClient", "KeyClient", "CertificateClient", "secrets", "encryption keys".
license: MIT
metadata:
  author: Microsoft
  version: "1.0.0"
  package: azure-keyvault-secrets, azure-keyvault-keys, azure-keyvault-certificates
---

# Azure Key Vault SDK for Python

Secure storage and management for secrets, cryptographic keys, and certificates.

## Installation

```bash
# Secrets
pip install azure-keyvault-secrets azure-identity

# Keys (cryptographic operations)
pip install azure-keyvault-keys azure-identity

# Certificates
pip install azure-keyvault-certificates azure-identity

# All
pip install azure-keyvault-secrets azure-keyvault-keys azure-keyvault-certificates azure-identity
```

## Environment Variables

```bash
AZURE_KEYVAULT_URL=https://<vault-name>.vault.azure.net/  # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
```

## Authentication & Lifecycle

> **🔑 Two rules apply to every code sample below:**
>
> 1. **Prefer `DefaultAzureCredential`.** It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys — they bypass Entra audit and rotation.
>    - Local dev: `DefaultAzureCredential` works as-is.
>    - Production: set `AZURE_TOKEN_CREDENTIALS=prod` (or `AZURE_TOKEN_CREDENTIALS=<specific_credential>`) to constrain the credential chain to production-safe credentials.
> 2. **Wrap every client in a context manager** so HTTP transports, sockets, and token caches are released deterministically:
>    - Sync: `with <Client>(...) as client:`
>    - Async: `async with <Client>(...) as client:` **and** `async with DefaultAzureCredential() as credential:` (from `azure.identity.aio`)
>
> Snippets may abbreviate this setup, but production code should always follow both rules.

## Secrets

### SecretClient Setup

```python
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.keyvault.secrets import SecretClient

# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()
vault_url = "https://<vault-name>.vault.azure.net/"

with SecretClient(vault_url=vault_url, credential=credential) as client:
    # All secret operations go inside this block (see examples below)
    ...
```

### Secret Operations

```python
# Set secret
secret = client.set_secret("database-password", "super-secret-value")
print(f"Created: {secret.name}, version: {secret.properties.version}")

# Get secret
secret = client.get_secret("database-password")
print(f"Value: {secret.value}")

# Get specific version
secret = client.get_secret("database-password", version="abc123")

# List secrets (names only, not values)
for secret_properties in client.list_properties_of_secrets():
    print(f"Secret: {secret_properties.name}")

# List versions
for version in client.list_properties_of_secret_versions("database-password"):
    print(f"Version: {version.version}, Created: {version.created_on}")

# Delete secret (soft delete)
poller = client.begin_delete_secret("database-password")
deleted_secret = poller.result()

# Purge (permanent delete, if soft-delete enabled)
client.purge_deleted_secret("database-password")

# Recover deleted secret
client.begin_recover_deleted_secret("database-password").result()
```

## Keys

### KeyClient Setup

```python
from azure.identity import DefaultAzureCredential
from azure.keyvault.keys import KeyClient

credential = DefaultAzureCredential()
vault_url = "https://<vault-name>.vault.azure.net/"

with KeyClient(vault_url=vault_url, credential=credential) as client:
    # All key operations go inside this block (see examples below)
    ...
```

### Key Operations

```python
from azure.keyvault.keys import KeyType

# Create RSA key
rsa_key = client.create_rsa_key("rsa-key", size=2048)

# Create EC key
ec_key = client.create_ec_key("ec-key", curve="P-256")

# Get key
key = client.get_key("rsa-key")
print(f"Key type: {key.key_type}")

# List keys
for key_properties in client.list_properties_of_keys():
    print(f"Key: {key_properties.name}")

# Delete key
poller = client.begin_delete_key("rsa-key")
deleted_key = poller.result()
```

### Cryptographic Operations

```python
from azure.keyvault.keys.crypto import CryptographyClient, EncryptionAlgorithm

# Get crypto client for a specific key
# crypto_client = CryptographyClient(key, credential=credential)
# Or from key ID
with CryptographyClient(
    "https://<vault>.vault.azure.net/keys/<key-name>/<version>",
    credential=credential
) as crypto_client:
    # Encrypt
    plaintext = b"Hello, Key Vault!"
    result = crypto_client.encrypt(EncryptionAlgorithm.rsa_oaep, plaintext)
    ciphertext = result.ciphertext

    # Decrypt
    result = crypto_client.decrypt(EncryptionAlgorithm.rsa_oaep, ciphertext)
    decrypted = result.plaintext

    # Sign
    from azure.keyvault.keys.crypto import SignatureAlgorithm
    import hashlib

    digest = hashlib.sha256(b"data to sign").digest()
    result = crypto_client.sign(SignatureAlgorithm.rs256, digest)
    signature = result.signature

    # Verify
    result = crypto_client.verify(SignatureAlgorithm.rs256, digest, signature)
    print(f"Valid: {result.is_valid}")
```

## Certificates

### CertificateClient Setup

```python
from azure.identity import DefaultAzureCredential
from azure.keyvault.certificates import CertificateClient, CertificatePolicy

credential = DefaultAzureCredential()
vault_url = "https://<vault-name>.vault.azure.net/"

with CertificateClient(vault_url=vault_url, credential=credential) as client:
    # All certificate operations go inside this block (see examples below)
    ...
```

### Certificate Operations

```python
# Create self-signed certificate
policy = CertificatePolicy.get_default()
poller = client.begin_create_certificate("my-cert", policy=policy)
certificate = poller.result()

# Get certificate
certificate = client.get_certificate("my-cert")
print(f"Thumbprint: {certificate.properties.x509_thumbprint.hex()}")

# Get certificate with private key (as secret)
from azure.keyvault.secrets import SecretClient
with SecretClient(vault_url=vault_url, credential=credential) as secret_client:
    cert_secret = secret_client.get_secret("my-cert")
    # cert_secret.value contains PEM or PKCS12

# List certificates
for cert in client.list_properties_of_certificates():
    print(f"Certificate: {cert.name}")

# Delete certificate
poller = client.begin_delete_certificate("my-cert")
deleted = poller.result()
```

## Client Types Table

| Client | Package | Purpose |
|--------|---------|---------|
| `SecretClient` | `azure-keyvault-secrets` | Store/retrieve secrets |
| `KeyClient` | `azure-keyvault-keys` | Manage cryptographic keys |
| `CryptographyClient` | `azure-keyvault-keys` | Encrypt/decrypt/sign/verify |
| `CertificateClient` | `azure-keyvault-certificates` | Manage certificates |

## Async Clients

```python
from azure.identity.aio import DefaultAzureCredential
from azure.keyvault.secrets.aio import SecretClient

async def get_secret():
    async with DefaultAzureCredential() as credential:
        async with SecretClient(vault_url=vault_url, credential=credential) as client:
            secret = await client.get_secret("my-secret")
            print(secret.value)

import asyncio
asyncio.run(get_secret())
```

## Error Handling

```python
from azure.core.exceptions import ResourceNotFoundError, HttpResponseError

try:
    secret = client.get_secret("nonexistent")
except ResourceNotFoundError:
    print("Secret not found")
except HttpResponseError as e:
    if e.status_code == 403:
        print("Access denied - check RBAC permissions")
    raise
```

## Best Practices

1. **Pick sync OR async and stay consistent.** Do not mix `azure.xxx` sync clients with `azure.xxx.aio` async clients in the same call path. Choose one mode per module.
2. **Always use context managers for clients and async credentials.** Wrap every client in `with Client(...) as client:` (sync) or `async with Client(...) as client:` (async). For async `DefaultAzureCredential` from `azure.identity.aio`, also use `async with credential:` so tokens and transports are cleaned up.
3. **Use `DefaultAzureCredential`** for code that runs locally. Use a specific token credential for code that runs in Azure.
4. **Use managed identity** in Azure-hosted applications
5. **Enable soft-delete** for recovery (enabled by default)
6. **Use RBAC** over access policies for fine-grained control
7. **Rotate secrets** regularly using versioning
8. **Use Key Vault references** in App Service/Functions config
9. **Cache secrets** appropriately to reduce API calls
10. **Use async clients** for high-throughput scenarios

## Reference Files

| File | Contents |
|------|----------|
| [references/capabilities.md](references/capabilities.md) | Additional non-hero capabilities, operation-group coverage, and production checklists. |
| [references/non-hero-scenarios.md](references/non-hero-scenarios.md) | Dedicated non-hero examples for secondary/advanced scenarios. |

More from microsoft/skills

SkillDescription
agent-framework-azure-ai-pyBuild Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.
airunway-aks-setupSet up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: \"setup AI Runway\", \"onboard AKS cluster\", \"install AI Runway\", \"airunway setup\", \"deploy model to AKS\", \"GPU inference on AKS\", \"KAITO setup on AKS\", \"run LLM on AKS\", \"vLLM on AKS\", \"set up model serving on AKS\", \"AI Runway controller\".
appinsights-instrumentationGuidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.
applicationinsights-web-tsInstrument browser/web apps with the Application Insights JavaScript SDK (@microsoft/applicationinsights-web). Use for Real User Monitoring (RUM) — page views, clicks, AJAX/fetch dependencies, exceptions, custom events, and browser-side GenAI agent traces correlated to backend OpenTelemetry traces. Covers SDK Loader Script and npm setup, framework extensions (React, React Native, Angular), Click Analytics, telemetry initializers, and OTel GenAI semantic conventions for agent/tool/model spans emitted from the browser.
azure-aiUse for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
azure-ai-agents-persistent-dotnet|
azure-ai-agents-persistent-java|
azure-ai-anomalydetector-javaBuild anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.
azure-ai-contentsafety-javaBuild content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text/image analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.
azure-ai-contentsafety-py|