[BREAKING] FEAT: Enable Entra ID Authentication across the codebase (#1124)

Author: jsong468

.env_example

@@ -1,4 +1,6 @@
 # This is an example of the .env file. Copy to .env and fill in your secrets.
+# Note that if you are using Entra authentication for certain Azure resources (use_entra_auth = True in PyRIT),
+# keys for those resources are not needed.
 
 
 ###################################
@@ -164,6 +166,8 @@ AZURE_STORAGE_ACCOUNT_SAS_TOKEN="xxxxx"
 
 AZURE_SPEECH_REGION = "eastus2"
 AZURE_SPEECH_KEY = "xxxxx"
+# Resource ID is needed when using Entra authentication
+AZURE_SPEECH_RESOURCE_ID = "xxxxx"
 
 AZURE_CONTENT_SAFETY_API_KEY="xxxxx"
 AZURE_CONTENT_SAFETY_API_ENDPOINT="https://xxxxx.cognitiveservices.azure.com/"

doc/code/scoring/1_azure_content_safety_scorers.ipynb

@@ -13,9 +13,9 @@
     "In order to use this API, you need to configure a few environment variables:\n",
     "\n",
     "- AZURE_CONTENT_SAFETY_API_ENDPOINT: The endpoint for the Azure Content Safety API\n",
-    "- AZURE_CONTENT_SAFETY_API_KEY: The API key for the Azure Content Safety API (if not using AAD Auth)\n",
+    "- AZURE_CONTENT_SAFETY_API_KEY: The API key for the Azure Content Safety API (if not using Entra Auth)\n",
     "\n",
-    "As an alternative to key-based authentication, you may set `use_aad_auth=True` and use identity-based authentication.\n",
+    "As an alternative to key-based authentication, you may set `use_entra_auth=True` and use identity-based authentication.\n",
     "\n",
     "Note that this api returns a value between 0 and 7. This is different from likert scales, which return a value between 1 and 5. Because both are `float_scale` scores, these values are all normalized to floating point values between 0.0 and 1.0 and can be directly compared. This is sometimes interesting as an operator e.g. if there are scenarios where a `SelfAskLikertScorer` and `AzureContentFilterScorer` produce very different values.\n",
     "\n",
@@ -52,9 +52,9 @@
     "\n",
     "# Set up the Azure Content Filter\n",
     "azure_content_filter = AzureContentFilterScorer(\n",
-    "    # Comment out either api_key or use_aad_auth\n",
+    "    # Comment out either api_key or use_entra_auth\n",
     "    api_key=os.environ.get(\"AZURE_CONTENT_SAFETY_API_KEY\"),\n",
-    "    # use_aad_auth=True,\n",
+    "    # use_entra_auth=True,\n",
     "    endpoint=os.environ.get(\"AZURE_CONTENT_SAFETY_API_ENDPOINT\"),\n",
     ")\n",
     "\n",

doc/code/scoring/1_azure_content_safety_scorers.py

@@ -22,9 +22,9 @@
 # In order to use this API, you need to configure a few environment variables:
 #
 # - AZURE_CONTENT_SAFETY_API_ENDPOINT: The endpoint for the Azure Content Safety API
-# - AZURE_CONTENT_SAFETY_API_KEY: The API key for the Azure Content Safety API (if not using AAD Auth)
+# - AZURE_CONTENT_SAFETY_API_KEY: The API key for the Azure Content Safety API (if not using Entra Auth)
 #
-# As an alternative to key-based authentication, you may set `use_aad_auth=True` and use identity-based authentication.
+# As an alternative to key-based authentication, you may set `use_entra_auth=True` and use identity-based authentication.
 #
 # Note that this api returns a value between 0 and 7. This is different from likert scales, which return a value between 1 and 5. Because both are `float_scale` scores, these values are all normalized to floating point values between 0.0 and 1.0 and can be directly compared. This is sometimes interesting as an operator e.g. if there are scenarios where a `SelfAskLikertScorer` and `AzureContentFilterScorer` produce very different values.
 #
@@ -43,9 +43,9 @@
 
 # Set up the Azure Content Filter
 azure_content_filter = AzureContentFilterScorer(
-    # Comment out either api_key or use_aad_auth
+    # Comment out either api_key or use_entra_auth
     api_key=os.environ.get("AZURE_CONTENT_SAFETY_API_KEY"),
-    # use_aad_auth=True,
+    # use_entra_auth=True,
     endpoint=os.environ.get("AZURE_CONTENT_SAFETY_API_ENDPOINT"),
 )
 

doc/code/scoring/prompt_shield_scorer.ipynb

@@ -106,6 +106,8 @@
     "initialize_pyrit(memory_db_type=IN_MEMORY)\n",
     "\n",
     "pst = PromptShieldTarget()\n",
+    "# For an Azure Content Safety endpoint with Entra ID authentication enabled, use the following command instead. Make sure to run `az login` first.\n",
+    "# target = PromptShieldTarget(use_entra_auth=True)\n",
     "\n",
     "scorer = PromptShieldScorer(prompt_shield_target=pst)\n",
     "\n",
@@ -148,7 +150,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.11"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

doc/code/scoring/prompt_shield_scorer.py

@@ -5,7 +5,7 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.17.3
+#       jupytext_version: 1.17.2
 # ---
 
 # %% [markdown]
@@ -48,6 +48,8 @@
 initialize_pyrit(memory_db_type=IN_MEMORY)
 
 pst = PromptShieldTarget()
+# For an Azure Content Safety endpoint with Entra ID authentication enabled, use the following command instead. Make sure to run `az login` first.
+# target = PromptShieldTarget(use_entra_auth=True)
 
 scorer = PromptShieldScorer(prompt_shield_target=pst)
 

doc/code/targets/1_openai_chat_target.ipynb

@@ -69,6 +69,8 @@
     "\n",
     "\n",
     "target = OpenAIChatTarget()\n",
+    "# For an AzureOpenAI endpoint with Entra ID authentication enabled, use the following command instead. Make sure to run `az login` first.\n",
+    "# target = OpenAIChatTarget(use_entra_auth=True)\n",
     "\n",
     "attack = PromptSendingAttack(objective_target=target)\n",
     "\n",
@@ -117,7 +119,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.9"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

doc/code/targets/1_openai_chat_target.py

@@ -30,6 +30,8 @@
 
 
 target = OpenAIChatTarget()
+# For an AzureOpenAI endpoint with Entra ID authentication enabled, use the following command instead. Make sure to run `az login` first.
+# target = OpenAIChatTarget(use_entra_auth=True)
 
 attack = PromptSendingAttack(objective_target=target)
 

doc/code/targets/5_multi_modal_targets.ipynb

@@ -118,6 +118,8 @@
     "objective = \"Give me an image of a raccoon pirate as a Spanish baker in Spain\"\n",
     "\n",
     "img_prompt_target = OpenAIDALLETarget()\n",
+    "# For an AzureOpenAI endpoint with Entra ID authentication enabled, use the following command instead. Make sure to run `az login` first.\n",
+    "# target = OpenAIChatTarget(use_entra_auth=True)\n",
     "\n",
     "image_scorer = SelfAskTrueFalseScorer(\n",
     "    chat_target=OpenAIChatTarget(),\n",
@@ -1108,7 +1110,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.11"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

doc/code/targets/5_multi_modal_targets.py

@@ -5,7 +5,11 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.17.3
+#       jupytext_version: 1.17.2
+#   kernelspec:
+#     display_name: pyrit-dev
+#     language: python
+#     name: python3
 # ---
 
 # %% [markdown]
@@ -35,6 +39,8 @@
 objective = "Give me an image of a raccoon pirate as a Spanish baker in Spain"
 
 img_prompt_target = OpenAIDALLETarget()
+# For an AzureOpenAI endpoint with Entra ID authentication enabled, use the following command instead. Make sure to run `az login` first.
+# target = OpenAIChatTarget(use_entra_auth=True)
 
 image_scorer = SelfAskTrueFalseScorer(
     chat_target=OpenAIChatTarget(),

doc/code/targets/8_openai_responses_target.ipynb

@@ -55,6 +55,8 @@
     "initialize_pyrit(memory_db_type=IN_MEMORY)\n",
     "\n",
     "target = OpenAIResponseTarget()\n",
+    "# For an AzureOpenAI endpoint with Entra ID authentication enabled, use the following command instead. Make sure to run `az login` first.\n",
+    "# target = OpenAIResponseTarget(use_entra_auth=True)\n",
     "\n",
     "attack = PromptSendingAttack(objective_target=target)\n",
     "\n",
@@ -243,7 +245,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.11"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,