Follow these steps if you are onboarding the AI Runtime Security: API intercept for the first time, or when you have already onboarded the AI API
intercept and want to manage the API security profile.
For the first time onboarding, ensure you Onboard AI Runtime Security: API Intercept in Strata Cloud Manager. For updating an exisiting API security
profile, navigate to Insights → AI Runtime Security and click
Manage from the top right corner and select Security
Profiles.
Create Security profile or edit and existing one with the following
configurations:
Enter a Security Profile Name.
Select the following protections with Allow or Block
actions:
Protection Type
Configurations
AI Model Protection
Enable Prompt Injection Detection and
set it to Allow or Block
The
feature supports the following languages: English,
Spanish, Russian, German, French, Japanese,
Portuguese, and Italian.
.
Enable Toxic Content Detection in LLM
model requests or responses.
This
feature helps protect the LLM models from
generating or responding to inappropriate
content.
The actions include Allow
or Block, with the following severity
levels:
Moderate: Detects content that some
users may consider toxic, but which may be more
ambiguous. The default value is Allow.
High: Content with a high likelihood of
most users considering it toxic. The default value
is Allow.
AI Application Protection
Enable Malicious Code Detection
This feature is used to analyze code snippets
generated by Large Language Models (LLMs) and
identify potential security threats.
Set the action to Block to prevent the
execution of potentially malicious code or set it
to Allow to ignore the “malicious” verdict
if needed.
To test your LLMs, trigger a scan API with a
response containing malicious code for supported
languages (Javascript, Python, VBScript,
Powershell, Batch, Shell, and Perl).
The system provides a verdict on the code
snippet and generates a detailed report with
SHA-256, file type, known verdict, code action,
and malware analysis.
Enable Malicious URL Detection
Basic: Enable the Malicious URL
Detection in a prompt or AI model response and
set the action to Allow or Block.
This is to detect the predefined malicious
categories.
Advanced: Provide URL security
exceptions:
The default action
(Allow or Block) is applied to all
the predefined URL security
categories.
In the URL Security Exceptions table, you
can override the default behavior by specifying
actions for individual URL categories.
Select the plus (+) icon to add the
predefined URL categories and set an action for
each.
Refer to the API reference
docs to trigger the scan APIs with the
intended detections. Also, generate the reports
with report ID and scan ID displayed in the output
snippet.
AI Data Protection
Enable Sensitive Data Detection
Basic: Enable sensitive DLP protection
for predefined data patterns with Allow or
Block action.
Advanced: Select the predefined or
custom DLP profile.
The
drop down list shows your custom DLP profiles and
all the DLP profiles linked to the tenant service
group (TSG) associated with your AI Runtime
Security: API intercept deployment profile.
Navigate to Manage > Configuration
> Data Loss Preventions > Data Profiles to
create a new DLP profile (Add a data
profile).
The prompts and
responses will be run against this DLP profile
attached to the AI security profile and action
(allow or block) will be taken based on the output
of the DLP profile.
Enable Database Security
Detection:
This detection is for AI
applications using genAI to generate database
queries and regulate the types of queries
generated.
Set an Allow or
Block action on the database queries
(Create, Read, Update, and Delete) to prevent
unauthorized actions.
You can use a single API key to manage
multiple AI security profiles for testing.
Latency Configuration: Define acceptable API response times by
setting a latency threshold in seconds. This threshold will determine
when API responses exceed the permissible limit, impacting how quickly
threats are detected and actions are executed. You can set the action to
Allow or Block when the latency threshold
exceeds.
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