AWS bedrock documentation change
Summary
Updated Amazon Bedrock Guardrails documentation with clarified language about safeguards, added examples, refined filter descriptions, and specified console limitations for selective input evaluation.
Security assessment
The changes enhance documentation of security features (content filtering, PII protection, etc.) but show no evidence of addressing a specific vulnerability. Updates clarify existing security controls without referencing incidents or weaknesses.
Diff
diff --git a/bedrock/latest/userguide/guardrails.md b/bedrock/latest/userguide/guardrails.md index a99dbe528..473322d98 100644 --- a//bedrock/latest/userguide/guardrails.md +++ b//bedrock/latest/userguide/guardrails.md @@ -7 +7 @@ -Amazon Bedrock Guardrails provides safeguards that you can configure for your generative AI applications based on your use cases and responsible AI policies. You can create multiple guardrails tailored to different use cases and apply them across multiple foundation models (FMs), providing a consistent user experience and standardizing safety and privacy controls across generative AI applications. You can use guardrails for both model prompts and responses with natural language. +Amazon Bedrock Guardrails provides configurable safeguards to help you build safe generative AI applications. With comprehensive safety and privacy controls across foundation models (FMs), Amazon Bedrock Guardrails offers a consistent user experience to help detect and filter undesirable content and protect sensitive information that might be present in user inputs or model responses (excluding reasoning content blocks). @@ -9 +9 @@ Amazon Bedrock Guardrails provides safeguards that you can configure for your ge -You can use Amazon Bedrock Guardrails in multiple ways to help safeguard your generative AI applications. For example: +You can use Amazon Bedrock Guardrails across multiple use cases and applications. Below are a few examples: @@ -11 +11 @@ You can use Amazon Bedrock Guardrails in multiple ways to help safeguard your ge - * A chatbot application can use guardrails to help filter harmful user inputs and toxic model responses. + * A chatbot application to help filter harmful user inputs and toxic model responses. @@ -13 +13 @@ You can use Amazon Bedrock Guardrails in multiple ways to help safeguard your ge - * A banking application can use guardrails to help block user queries or model responses associated with seeking or providing investment advice. + * A banking application to help block user queries or model responses associated with seeking or providing illegal investment advice. @@ -20 +20 @@ You can use Amazon Bedrock Guardrails in multiple ways to help safeguard your ge -Amazon Bedrock Guardrails provides the following safeguards (also known as policies) to detect and filter harmful content: +Amazon Bedrock Guardrails provides the following safeguards (also known as filters) to detect and filter undesirable content: @@ -22 +22 @@ Amazon Bedrock Guardrails provides the following safeguards (also known as polic - * **Content filters** – Detect and filter harmful text or image content in input prompts or model responses. Filtering is done based on detection of certain predefined harmful content categories: Hate, Insults, Sexual, Violence, Misconduct and Prompt Attack. You also can adjust the filter strength for each of these categories. These categories are supported for both Classic and Standard [tiers](./guardrails-tiers.html). With Standard tier, detection of undesirable content is extended to protection against harmful content introduced within code elements including comments, variable and function names, and string literals. + * **Content filters** – This filter helps you detect and filter harmful text or image content in input prompts or model responses. Filtering is done based on detection of certain predefined harmful content categories: Hate, Insults, Sexual, Violence, Misconduct and Prompt Attack. You can configure the filter strength for each of these categories based on your use cases. These categories are supported for both Classic and Standard [tiers](./guardrails-tiers.html). With Standard tier, detection of undesirable content is extended to protection against harmful content introduced within code elements including comments, variable and function names, and string literals. @@ -24 +24 @@ Amazon Bedrock Guardrails provides the following safeguards (also known as polic - * **Denied topics** – Define a set of topics that are undesirable in the context of your application. The filter will help block them if detected in user queries or model responses. With [Standard tier](./guardrails-tiers.html), detection of undesirable content is extended to protection against harmful content introduced within code elements including comments, variables and function names, and string literals. + * **Denied topics** – You can define a set of topics that are undesirable in the context of your application. The filter will help block them if detected in user queries or model responses. With [Standard tier](./guardrails-tiers.html), detection of undesirable content is extended to protection against harmful content introduced within code elements including comments, variables and function names, and string literals. @@ -26 +26 @@ Amazon Bedrock Guardrails provides the following safeguards (also known as polic - * **Word filters** – Configure filters to help block undesirable words, phrases, and profanity (exact match). Such words can include offensive terms, competitor names, etc. + * **Word filters** – You can define a set of custom words or phrases (exact match) that you want to block in the interaction between end users and generative AI applications. For example, you can block profanity (use a ready-to-use option) as well as custom words such as competitor names. @@ -28 +28 @@ Amazon Bedrock Guardrails provides the following safeguards (also known as polic - * **Sensitive information filters** – Configure filters to help block or mask sensitive information, such as personally identifiable information (PII), or custom regex in user inputs and model responses. Blocking or masking is done based on probabilistic detection of sensitive information in standard formats in entities such as SSN number, Date of Birth, address, etc. This also allows configuring regular expression based detection of patterns for identifiers. + * **Sensitive information filters** – You can configure this filter to help block or mask sensitive information, such as personally identifiable information (PII), in user inputs and model responses. Blocking or masking is done based on probabilistic detection of sensitive information in in entities such as SSN number, Date of Birth, address, etc. This filter also allows configuring regular expression based detection of patterns (custom regex). @@ -30 +30 @@ Amazon Bedrock Guardrails provides the following safeguards (also known as polic - * **Contextual grounding checks** – Help detect and filter hallucinations in model responses based on grounding in a source and relevance to the user query. + * **Contextual grounding checks** – This filter helps you detect hallucinations in model responses if they are not grounded (factually inaccurate or add new information) in the source or are irrelevant to to the user's query. For example, you can block or flag responses in retrieval-augmented generation (RAG) applications. If the model responses deviate from the information in the retrieved source or doesn't answer the question from the user. @@ -32 +32 @@ Amazon Bedrock Guardrails provides the following safeguards (also known as polic - * **Automated Reasoning checks** – Can help you validate the accuracy of foundation model responses against a set of logical rules. You can use Automated Reasoning checks to detect hallucinations, suggest corrections, and highlight unstated assumptions in model responses. + * **Automated Reasoning checks** – This filter helps you validate the accuracy of foundation model responses against a set of logical rules. You can use Automated Reasoning checks to detect hallucinations, suggest corrections, and highlight unstated assumptions in model responses. @@ -37 +37 @@ Amazon Bedrock Guardrails provides the following safeguards (also known as polic -In addition to the above policies, you can also configure the messages to be returned to the user if a user input or model response is in violation of the policies defined in the guardrail. +In addition to the above filters, you can also configure the messages to be returned to the user if a user input or model response is in violation of the filters defined in the guardrail. @@ -41 +41 @@ Experiment and benchmark with different configurations and use the built-in test -Guardrails can be used directly with FMs during the inference API invocation by specifying the guardrail ID and the version. Guardrails can also be used directly through the `ApplyGuardrail` API without invoking the foundation models. If a guardrail is used, it will evaluate the input prompts and the FM completions against the defined policies. +Guardrails can be used directly with FMs during the inference API invocation by specifying the guardrail ID and the version. Guardrails can also be used directly through the `ApplyGuardrail` API without invoking the foundation models. If a guardrail is used, it will evaluate the input prompts and the FM completions against the defined filters. @@ -43 +43 @@ Guardrails can be used directly with FMs during the inference API invocation by -For retrieval augmented generation (RAG) or conversational applications, you might need to evaluate only the user input in the input prompt while discarding system instructions, search results, conversation history, or a few short examples. To selectively evaluate a section of the input prompt, see [Apply tags to user input to filter content](./guardrails-tagging.html). +For retrieval augmented generation (RAG) or conversational applications, you might need to evaluate only user input prompts while discarding system instructions, search results, conversation history, or a few short examples. To selectively evaluate a section of the input prompt, see [Apply tags to user input to filter content](./guardrails-tagging.html) The ability to evaluate only a section of the input prompt is available through the AWS SDK and not available on the management console including the Bedrock Playground and the Bedrock Guardrails management console.