vania-janet/multiturn-rag-retrieval-data huggingface dataset:
ibmcloud iam trusted-profile-rule-create my-profile --name my-rule --type Profile-CR --conditions claim:namespace,operator:EQUALS,value:default --conditions claim:crn,operator:EQUALS,value:crn:test:bluemix:public:containers-kubernetes:us-south:a/test:: --cr-type IKS_SA







 ibmcloud iam trusted-profile-rules 

List all rules for a specified trusted profile:

ibmcloud iam trusted-profile-rules (NAME|ID) [--output FORMAT] [-f, --force] [-q, --quiet]



 Command options 

NAME|ID (required)
: Name or ID of the trusted profile to retrieve rules for.

--output FORMAT.
: Specify output format. Only 'JSON' is supported.

-f, --force
: Force failure if multiple profiles are found.

-q, --quiet
: Suppress verbose output.





 Examples 

Display all rules in trusted profile my-profile:

ibmcloud iam trusted-profile-rules my-profile







 ibmcloud iam trusted-profile-rule-update 

Update a rule for a trusted profile:

ibmcloud iam trusted-profile-rule-update (NAME|ID) (RULE_NAME|RULE_ID) --name RULE_NAME --type RULE_TYPE [--realm-name REALM_NAME] --conditions <LIST_OF_CONDITIONS> [--cr-type CR_TYPE] [--expiration EXPIRATION_SEC] [--output FORMAT] [-q, --quiet] [-f, --force]

To view a full list of valid operator conditions for a claim rule, see [Trusted Profiles API](https://cloud.ibm.com/apidocs/iam-identity-token-apiupdate-claim-rule)



 Command options 

NAME|ID (required)
: Name or ID of the trusted profile to to update a rule for.

RULE_NAME|RULE_ID (required)
: The name or ID of the rule to update.

--type
* [Troubleshooting your CIS network connection](https://cloud.ibm.com/docs/cis?topic=cis-troubleshoot-your-cis-network-connection)
* [What do I do if I use the Cloudflare Origin root certificate, and it's expiring?](https://cloud.ibm.com/docs/cis?topic=cis-update-origin-root-ca)
* [Why is my website offline?](https://cloud.ibm.com/docs/cis?topic=cis-troubleshooting-cis-website-offline)
* [Why do I see a privacy warning?](https://cloud.ibm.com/docs/cis?topic=cis-troubleshooting-cis-privacy-warning)
* [What do I do if I’m under a DDoS attack?](https://cloud.ibm.com/docs/cis?topic=cis-troubleshooting-cis-ddos-attack)
* [Why am I not seeing any network traffic?](https://cloud.ibm.com/docs/cis?topic=cis-troubleshooting-cis-network-traffic)
* [How do I troubleshoot false positives and false negatives in WAF?](https://cloud.ibm.com/docs/cis?topic=cis-waf-false-pos-neg)
* [Troubleshooting CIS error codes](https://cloud.ibm.com/docs/cis?topic=cis-troubleshooting-cis-error-codes)
* [Why is my rule not working?](https://cloud.ibm.com/docs/cis?topic=cis-order-of-execution)
* [Troubleshooting 500 class errors](https://cloud.ibm.com/docs/cis?topic=cis-html-5xx-errors)
* [Troubleshooting 1000 class errors](https://cloud.ibm.com/docs/cis?topic=cis-html-1xxx-errors)
How do I troubleshoot false positives and false negatives in WAF? 

By default, the Web Application Firewall (WAF) is fully managed through the dashboard and is compatible with most websites and web applications. However, you might encounter false positives and false negatives.

 Why it’s happening 

False positives happen when legitimate requests are detected and filtered as malicious. False negatives occur when malicious requests are not filtered.



 Troubleshooting WAF false positives 

 What’s happening 

The definition of suspicious content is subjective for each website. For example, PHP code posted to your website is suspicious unless your website teaches how to code and requires PHP code submissions from visitors. Therefore, such a website must disable related WAF rules that interfere with normal operation.

To test for false positives, set the WAF to Simulate mode, to record the response to possible attacks without challenging or blocking. Also, use the Firewall Analytics Activity log to determine which WAF rules caused false positives.

 How to fix it 

If you encounter a false positive, there are several potential resolutions:



* Add the client’s IP addresses to the IP Access Rules allowlist: If the browser or client visits from the same IP addresses, allowing is recommended.
* Disable the corresponding WAF rules. Doing so stops blocking or challenging false positives, but reduces overall site security. A request blocked by WAF Rule ID 981176 refers to OWASP rules. Decrease OWASP sensitivity to resolve the issue.
* Bypass the WAF with a Firewall Rule: Create a Firewall Rule with the bypass action to deactivate the WAF for a specific combination of parameters. For example, bypass the WAF for a specific URL and a specific IP address or user agent.
* Disable WAF for traffic to a URL (not recommended). Disabling WAF using page rules lowers security on the particular URL endpoint.



If you contact IBM Support to verify whether a WAF rule triggers as expected, provide a HAR file captured while sending the specific request of concern.

If one specific rule causes false positives, set rule’s Mode to Disable rather than turning Off the entire rule group.
* FRONT-END TO PAYMENT TOOLS: fee systems, payment tracking including cross-border, regulatory compliance, biometrics, remittance, and more
* REGULATION-SPECIFIC FEATURES: each country has unique regulations so that the overall toolset might look similar but show country-specific benefits
* DEVELOPER-FRIENDLY TOOLS that accelerate roll-out of features and bug fixes
* FRAUD DETECTION AS A SERVICE (FDaaS) uses Watson AI to keep one step ahead of frequent and growing fraudulent actions



Compute, DevOps tools, and AI that run in public cloud with access to back-end payment systems. Implement a CI/CD process to dramatically shorten delivery cycles.

Technical solution:



* IBM Cloud Kubernetes Service
* IBM Cloud® Continuous Delivery
* IBM Cloud Logging and Monitoring
* IBM Watson for Financial Services
* IBM Cloud App ID



They started by containerizing the payment tool VMs and putting them in the cloud. In a flash, their hardware headaches went away. They were able to easily design Kubernetes clusters to fit their CPU, RAM, storage, and security needs. And when their payment tools need to change, they can add or shrink compute without expensive and slow hardware purchases.

With IBM Cloud Kubernetes Service horizontal scaling, their apps scale with the growing number of partners, resulting in faster growth. IBM Cloud Kubernetes Service provides elastic compute resources around the world that are secure for full usage of modern compute resources.

Accelerated development is a key win for the Exec. With the use of modern containers, Developers can experiment easily in the languages of their choice, pushing changes to Development and Test systems, scaled out on separate clusters. Those pushes were automated with open toolchains and IBM Cloud® Continuous Delivery. No longer were updates to the tools languishing in slow, error-prone build processes. They can deliver incremental updates to their tools, daily or even more frequently.

Also, logging and monitoring for the tools, especially where they used Watson AI, rapidly integrate into the system. Developers don’t waste time building complex logging systems, just to be able to troubleshoot their live systems. A key factor for less staffing costs is that IBM manages Kubernetes, so the Developers can focus on better payment tools.
"evidence_type_id": "com.ibm.code_cis_check",
"rules": {
"required": ],
"optional":
{
"tool": ""
}
],
"ignore": ]
}
},
{
"evidence_type_id": "com.ibm.code_bom_check",
"rules": {
"required": ],
"optional":
{
"tool": ""
}
],
"ignore": ]
}
},
{
"evidence_type_id": "com.ibm.acceptance_tests",
"rules": {
"required": ],
"optional":
{
"tool": ""
}
],
"ignore": ]
}
}
]
},
{
"asset_type": "image",
"evidences":
{
"evidence_type_id": "com.ibm.cloud.image_signing",
"rules": {
"required": ],
"optional":
{
"tool": ""
}
],
"ignore": ]
}
},
{
"evidence_type_id": "com.ibm.cloud.image_vulnerability_scan",
"rules": {
"required": ],
"optional":
{
"tool": ""
}
],
"ignore": ]
}
},
{
"evidence_type_id": "com.ibm.dynamic_scan",
"rules": {
"required": ],
"optional":
{
"tool": ""
}
],
"ignore": ]
}
}
]
},
{
curl -X POST https://api.cis.cloud.ibm.com/v1/:crn/alerting/policies -H 'content-type: application/json' -H 'x-auth-user-token: Bearer xxxxxx' -d '{"name":"Example Policy","enabled":true,"alert_type":"dos_attack_l7","mechanisms":{"email":[{"id":"cistestemail@ibm.com"}],"webhooks": [{"id": "6d16fcab3e8044b3b59ba3716237832e"}]}}'







 Editing alerts using the API 

To edit an email alert, run the following command:

curl -X PUT https://api.cis.cloud.ibm.com/v1/:crn/alerting/policies/:policy_id -H 'content-type: application/json' -H 'x-auth-user-token: Bearer xxxxxx' -d '{"name":"Example Policy","enabled":true,"alert_type":"dos_attack_l7","conditions":{},"mechanisms":{"email":[{"id":"cistestemail@ibm.com"}],"webhooks":[]}}'

The conditions field is required, even though it might be empty.

To edit a webhook, use the following PUT request:

curl -X PUT https://api.cis.cloud.ibm.com/v1/:crn/alerting/destinations/webhooks/:webhook_id -H 'content-type: application/json' -H 'x-auth-user-token: Bearer xxxxxx' -d '{"name":"Example Webhook","url":"https://hooks.slack.com/services/Ds3fdBFbV/456464Gdd"}'





 Deleting alerts using the API 

To delete an email alert, run the following command:
ibmcloud cis ratelimit-rule-create 31984fea73a15b45779fa0df4ef62f9b --json '{"id":"372e67954025e0ba6aaa6d586b9e0b59","disabled":false,"description":"Prevent multiple login failures to mitigate brute force attacks","match":{"request":{"methods":"GET","POST"],"schemes":"HTTP","HTTPS"],"url":".example.org/path"},"response":{"status": 403, 401],"headers":{"name":"Cf-Cache-Status","op":"ne","value":"HIT"}]}},"bypass":{"name":"url","value":"api.example.com/"}] ! ! ! ,"threshold":60,"period":900,"action":{"mode":"challenge","timeout":86400,"response":{"content_type":"text/xml","body":"<error>This request has been rate-limited.</error>"}}}' -i "cis-demo"
<-- </section "id="section-create-ratelimit-examples" "> --><-- </section "id="section-create-ratelimit" "> --><-- <section "id="section-update-ratelimit" "> --> ibmcloud cis ratelimit-rule-update Update a rate limiting rule of a given DNS domain. ibmcloud cis ratelimit-rule-update DNS_DOMAIN_ID RATELIMIT_RULE_ID (--json @JSON_FILE | JSON_STRING) -i, --instance INSTANCE] --output FORMAT]
ibmcloud cis edge-functions-action-create 

Create an Edge Functions action for a service instance.

ibmcloud cis edge-functions-action-create [--name ACTION_NAME] (--javascript-str JAVASCRIPT_STR | --javascript-file JAVASCRIPT_FILE) [-i, --instance INSTANCE] [--output FORMAT]



 Command options 

--name
: Action name (Enterprise plan only).

--javascript-str
: Javascript string. For example: addEventListener('fetch', event => { event.respondWith(fetch(event.request))})

--javascript-file
: Javascript file.

-i, --instance
: Instance name or ID. If not set, the context instance specified by ibmcloud cis instance-set INSTANCE is used.

--output
: Specify output format, only JSON is supported.





 Examples 

Create an Edge Functions action for instance action-demo.

ibmcloud cis edge-functions-action-create --javascript-str "addEventListener('fetch', event => { event.respondWith(fetch(event.request)) })" --name "action-demo" -i "cis-demo"







 ibmcloud cis edge-functions-action-update 

Update an Edge Functions action of a service instance.

ibmcloud cis edge-functions-action-update (--javascript-str JAVASCRIPT_STR | --javascript-file JAVASCRIPT_FILE) [--name ACTION_NAME] [-i, --instance INSTANCE] [--output FORMAT]



 Command options 

--name
: Action name (Enterprise plan only).

--javascript-str
: Javascript string. For example: addEventListener('fetch', event => { event.respondWith(fetch(event.request))})

--javascript-file
: Javascript file.

-i, --instance
: Instance name or ID.
24 June 2022 

Algorithm version options available in more languages
: Algorithm version options are now available in Chinese (Traditional), Japanese, and Korean. This allows you to choose which Watson Assistant algorithm to apply to your future trainings. For more information, see [Algorithm version](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-algorithm-version).

Improved enhanced intent detection available in more languages
: Previously, the exact match in enhanced intent detection was improved to better handle small differences between training examples and runtime utterances when the differences do not change the meaning of a sentence. For example, suppose in your training examples, covid-19 is in the covid intent and @doctortype_facilitytype around Palm Beach is in the find_provide_master intent. In this example, the @doctortype_facilitytype direct entity reference contains entity values, including hospital. At run time, covid19 is predicted as 100% confident for the covid intent, and hospital around palm beach is predicted as 100% confident for the find_provide_master intent.

This update now includes the following languages: Chinese (Simplified), Chinese (Traditional), German, Japanese, Korean, and Portuguese. For more information, see [Accessing intents](https://cloud.ibm.com/docs/assistant?topic=assistant-expression-languageexpression-language-intent).





 16 June 2022 

Algorithm version
: Algorithm version allows you to choose which Watson Assistant algorithm to apply to your future trainings. In the Options section of a dialog skill, Algorithm Version replaces Intent Detection. For more information, see [Algorithm version](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-algorithm-version).

Algorithm beta version (2022-06-10)
: Algorithm beta version (2022-06-10) includes a new irrelevance detection algorithm to improve off-topic detection accuracy. Utterances with similar meanings are expected to have more similar confidences in comparison to previous irrelevance detection algorithms. For example, in the Customer Care Sample Skill, the training utterance please suggest route from times square has 100% confidence at runtime.
See also [secret](https://cloud.ibm.com/docs/overview?topic=overview-glossaryx2789492), [secrets engine](https://cloud.ibm.com/docs/overview?topic=overview-glossaryx9968967).







 E 



 endorse 

To validate a chaincode transaction that was made by another member of a blockchain network.





 endorsement 

A collection of digital signatures from endorsing peers that establish that a transaction satisfies an endorsement policy.





 endorsement policy 

A policy that defines the peer nodes on a channel that must execute transactions that are attached to a specific chaincode application, and the required combination of endorsements. For example, a policy could require that a transaction be endorsed by a minimum number of endorsing peers, a minimum percentage of endorsing peers, or by all endorsing peers that are assigned to a specific chaincode application.





 endpoint 

The address of an API or service in an environment. An API exposes an endpoint and at the same time invokes the endpoints of other services. See also [route](https://cloud.ibm.com/docs/overview?topic=overview-glossaryx2037338).





 enterprise 

A hierarchical structure of accounts with centralized account and billing management in a cloud environment. See also [account group](https://cloud.ibm.com/docs/overview?topic=overview-glossaryx8622525), [billing unit](https://cloud.ibm.com/docs/overview?topic=overview-glossaryx9308099).





 enterprise account 

A unique account within an enterprise that manages users and access for account organization and enterprise billing. See also [account](https://cloud.ibm.com/docs/overview?topic=overview-glossaryx2012863).





 entitlement 

In software licensing, the maximum allowed allocation of capacity as determined by a license agreement.





 entity 



* A set of details that are held about a real-world object such as a person, location, or bank account. An entity is a kind of item.
You can then create a model that recognizes the rule patterns, and deploy it for use in other services.

See [Creating a rule-based model](https://cloud.ibm.com/docs/watson-knowledge-studio-data?topic=watson-knowledge-studio-data-rule-annotator) for more details.







 Analyze text with advanced rules 

The advanced rules feature is Beta. The feature is in a trial stage of development and is not recommended for use in production environments.

The visual advanced rules editor allows you to create text extractors with deeper customization potential than what is available in the entities and relations rules editor. A number of sample extractors are provided such as Finance Actions extractors and Parts of Speech extractors that can be edited and combined to create your own advanced rules model. You can analyze documents directly in the editor, or you can export your model to use with other services such as [Natural Language Understanding](https://cloud.ibm.com/docs/natural-language-understanding).

To get started, see [Creating an advanced rules model](https://cloud.ibm.com/docs/watson-knowledge-studio-data?topic=watson-knowledge-studio-data-create-advanced-rules-model).





 FISMA support 

Federal Information Security Management Act (FISMA) support is available for IBM Watson™ Knowledge Studio for IBM Cloud Pak for Data offerings purchased on or after August 30, 2019. FISMA support is also available to those who purchased the June 28, 2019 version and upgrade to the August 30, 2019 version. IBM Watson™ Knowledge Studio for IBM Cloud Pak for Data is FISMA High Ready.





 Watson services integration 

Share domain artifacts and models between Knowledge Studio and other Watson services available on IBM Cloud Pak for Data.

Use Knowledge Studio to perform the following tasks:



* Upload analyzed documents that are in [UIMA CAS XMI format](https://cloud.ibm.com/docs/watson-knowledge-studio-data?topic=watson-knowledge-studio-data-preannotationwks_uimaweximport).
This lifecycle endorsement policy can in theory be anything (including allowing any organization to commit a definition, or just a single organization), but generally speaking will, in the spirit of collaboration, be something like a “majority of channel admins”.

This separation of the definition (agreed to at the channel level) and the package that’s installed on the peers has powerful implications for how smart contracts can be written and managed, as we will see.



 Taking advantage of the ability for each organization to use a separate package 

The elimination of the need for the smart contracts to exactly match their fingerprints opens up exciting new possibilities when developing smart contracts.

First, to address a natural question: how can results be predictable (or, more to the point, deterministic) if peers in different organizations aren’t running the same code?

An analogy might help to explain. If two people attempt to multiply two numbers together (33 by 7, for example), one might decide to multiply 30 by 7 and also 3 by 7 and then add the two resulting numbers together. While the other person might not use this trick, or choose to use a calculator. It’s not important that both people use the same process, only that they arrive at the same answer.

The same basic principle is true for different smart contract packages running on different peers producing the same read/write set, given a set of inputs. As long as the smart contracts running on every peer on a channel produce the same read/write set, it does not matter if they are running exactly the same code.

But why bother? Why not run the same code?

You certainly can, and it is probably advisable to run the same (or at least similar) code in order to eliminate corner cases that might emerge if substantially different code is being run against the same data.

However, consider a scenario in which the various organizations on a channel are all executing transactions against a set of data but have substantially different roles. In this scenario:



* Org A: an individual who wants to place an advertisement.
* Org B: the owner of the place where advertisements are posted.



Org A should, logically, be allowed to request an ad be placed, and also to query ads.
/myOrg/video/transcode video/transcode /myOrg video transcode 
 /myOrg/filter filter /myOrg filter 



You can use this naming scheme when you use the Cloud Functions CLI, among other places.

More precisely, a name must match the following regular expression (expressed with Java meta character syntax): A([w]|[w][w@.-]+)z.







 Action semantics 

The following sections describe details about Cloud Functions actions.



 Statelessness 

Action implementations are stateless, or idempotent. While the system does not enforce this property, it is not guaranteed that any state maintained by an action is available across invocations.

Moreover, multiple instantiations of an action might exist, with each instantiation with its own state. An action invocation might be dispatched to any of these instantiations.





 Invocation input and output 

The input to and output from an action is a dictionary of key-value pairs. The key is a string, and the value a valid JSON value.





 Invocation ordering of actions 

Invocations of an action are not ordered. If the user invokes an action twice from the command-line or the REST API, the second invocation might run before the first. If the actions have side effects, they might be observed in any order.

Additionally, it is not guaranteed that actions execute automatically. Two actions can run concurrently and their side effects can be interleaved. OpenWhisk does not ensure any particular concurrent consistency model for side effects.





 Action executions 

When an invocation request is received, the system records the request and dispatches an activation.

The system returns an activation ID (with a nonblocking invocation) that confirms that it is received. If a network failure or other failure that intervenes before you receive an HTTP response, it is possible that Cloud Functions received and processed the request.

The system attempts to invoke the action once, resulting in one of the following four outcomes:



Table 5. Outcomes for invoking an action

 Result Description 

 success The action invocation completed successfully.