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Versions: (draft-waltermire-sacm-use-cases) 00 01 02 03 04 05 06 07 08 09 10 RFC 7632

Security Automation and Continuous Monitoring WG           D. Waltermire
Internet-Draft                                                      NIST
Intended status: Informational                             D. Harrington
Expires: May 24, 2014                                 Effective Software
                                                       November 20, 2013


      Endpoint Security Posture Assessment - Enterprise Use Cases
                      draft-ietf-sacm-use-cases-05

Abstract

   This memo documents a sampling of use cases for securely aggregating
   configuration and operational data and evaluating that data to
   determine an organization's security posture.  From these operational
   use cases, we can derive common functional capabilities and
   requirements to guide development of vendor-neutral, interoperable
   standards for aggregating and evaluating data relevant to security
   posture.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at http://datatracker.ietf.org/drafts/current/.

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on May 24, 2014.

Copyright Notice

   Copyright (c) 2013 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (http://trustee.ietf.org/license-info) in effect on the date of
   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must



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   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Endpoint Posture Assessment . . . . . . . . . . . . . . . . .   4
     2.1.  Use Cases . . . . . . . . . . . . . . . . . . . . . . . .   5
       2.1.1.  Define, Publish, Query and Retrieve Content . . . . .   5
       2.1.2.  Endpoint Identification and Assessment Planning . . .   7
       2.1.3.  Endpoint Posture Attribute Value Collection . . . . .   8
       2.1.4.  Posture Evaluation  . . . . . . . . . . . . . . . . .   8
       2.1.5.  Mining the Database . . . . . . . . . . . . . . . . .   9
     2.2.  Usage Scenarios . . . . . . . . . . . . . . . . . . . . .  10
       2.2.1.  Definition and Publication of Automatable
               Configuration Guides  . . . . . . . . . . . . . . . .  10
       2.2.2.  Automated Checklist Verification  . . . . . . . . . .  11
       2.2.3.  Detection of Posture Deviations . . . . . . . . . . .  13
       2.2.4.  Endpoint Information Analysis and Reporting . . . . .  14
       2.2.5.  Asynchronous Compliance/Vulnerability Assessment at
               Ice Station Zebra . . . . . . . . . . . . . . . . . .  15
       2.2.6.  Identification and Retrieval of Repository Content  .  17
       2.2.7.  Content Change Detection  . . . . . . . . . . . . . .  18
       2.2.8.  Others... . . . . . . . . . . . . . . . . . . . . . .  18
   3.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  18
   4.  Security Considerations . . . . . . . . . . . . . . . . . . .  18
   5.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  18
   6.  Change Log  . . . . . . . . . . . . . . . . . . . . . . . . .  19
     6.1.  -04- to -05-  . . . . . . . . . . . . . . . . . . . . . .  19
     6.2.  -03- to -04-  . . . . . . . . . . . . . . . . . . . . . .  20
     6.3.  -02- to -03-  . . . . . . . . . . . . . . . . . . . . . .  20
     6.4.  -01- to -02-  . . . . . . . . . . . . . . . . . . . . . .  21
     6.5.  -00- to -01-  . . . . . . . . . . . . . . . . . . . . . .  21
     6.6.  draft-waltermire-sacm-use-cases-05 to draft-ietf-sacm-
           use-cases-00  . . . . . . . . . . . . . . . . . . . . . .  22
     6.7.  waltermire -04- to -05- . . . . . . . . . . . . . . . . .  23
   7.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  24
     7.1.  Normative References  . . . . . . . . . . . . . . . . . .  24
     7.2.  Informative References  . . . . . . . . . . . . . . . . .  24
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  24

1.  Introduction








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   Our goal with this document is to improve our agreement on which
   problems we're trying to solve.  We need to start with short, simple
   problem statements and discuss those by email and in person.  Once we
   agree on which problems we're trying to solve, we can move on to
   propose various solutions and decide which ones to use.

   This document describes example use cases for endpoint posture
   assessment for enterprises.  It provides a sampling of use cases for
   securely aggregating configuration and operational data and
   evaluating that data to determine the security posture of individual
   endpoints, and, in the aggregate, the security posture of an
   enterprise.

   These use cases cross many IT security information domains.  From
   these operational use cases, we can derive common concepts, common
   information expressions, functional capabilities and requirements to
   guide development of vendor-neutral, interoperable standards for
   aggregating and evaluating data relevant to security posture.

   Using this standard data, tools can analyze the state of endpoints,
   user activities and behaviour, and evaluate the security posture of
   an organization.  Common expression of information should enable
   interoperability between tools (whether customized, commercial, or
   freely available), and the ability to automate portions of security
   processes to gain efficiency, react to new threats in a timely
   manner, and free up security personnel to work on more advanced
   problems.

   The goal is to enable organizations to make informed decisions that
   support organizational objectives, to enforce policies for hardening
   systems, to prevent network misuse, to quantify business risk, and to
   collaborate with partners to identify and mitigate threats.

   It is expected that use cases for enterprises and for service
   providers will largely overlap, but there are additional
   complications for service providers, especially in handling
   information that crosses administrative domains.

   The output of endpoint posture assessment is expected to feed into
   additional processes, such as policy-based enforcement of acceptable
   state, verification and monitoring of security controls, and
   compliance to regulatory requirements.









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2.  Endpoint Posture Assessment

   Endpoint posture assessment involves orchestrating and performing
   data collection and evaluating the posture of a given endpoint.
   Typically, endpoint posture information is gathered and then
   published to appropriate data repositories to make collected
   information available for further analysis supporting organizational
   security processes.

   Endpoint posture assessment typically includes:

   o  Collecting the attributes of a given endpoint;

   o  Making the attributes available for evaluation and action; and

   o  Verifying that the endpoint's posture is in compliance with
      enterprise standards and policy.

   As part of these activities it is often necessary to identify and
   acquire any supporting content that is needed to drive data
   collection and analysis.

   The following is a typical workflow scenario for assessing endpoint
   posture:

   1.  Some type of trigger initiates the workflow.  For example, an
       operator or an application might trigger the process with a
       request, or the endpoint might trigger the process using an
       event-driven notification.

          QUESTION: Since this is about security automation, can we drop
          the User and just use Application?  Is there a better term to
          use here?  Once the policy is selected, the rest seems like
          something we definitely would want to automate, so I dropped
          the User part.

   2.  An operator/application selects one or more target endpoints to
       be assessed.

   3.  A operator/application selects which policies are applicable to
       the targets.

   4.  For each target:

       A.  The application determines which (sets of) posture attributes
           need to be collected for evaluation.





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              QUESTION: It was suggested that mentioning several common
              acquisition methods, such as local API, WMI, Puppet, DCOM,
              SNMP, CMDB query, and NEA, without forcing any specific
              method would be good.  I have concerns this could devolve
              into a "what about my favorite?" contest.  OTOH, the
              charter does specifically call for use of existing
              standards where applicable, so the use cases document
              might be a good neutral location for such information, and
              might force us to consider what types of external
              interfaces we might need to support when we consider the
              requirements.  It appears that the generic workflow
              sequence would be a good place to mention such common
              acquisition methods.

       B.  The application might retrieve previously collected
           information from a cache or data store, such as a data store
           populated by an asset management system.

       C.  The application might establish communication with the
           target, mutually authenticate identities and authorizations,
           and collect posture attributes from the target.

       D.  The application might establish communication with one or
           more intermediary/agents, mutually authenticate their
           identities and determine authorizations, and collect posture
           attributes about the target from the intermediary/agents.
           Such agents might be local or external.

       E.  The application communicates target identity and (sets of)
           collected attributes to an evaluator, possibly an external
           process or external system.

       F.  The evaluator compares the collected posture attributes with
           expected values as expressed in policies.

              QUESTION: Evaluator generates a report or log or
              notification of some type?

2.1.  Use Cases

   The following subsections detail specific use cases for assessment
   planning, data collection, analysis, and related operations
   pertaining to the publication and use of supporting content.

2.1.1.  Define, Publish, Query and Retrieve Content

   This use case describes the need for content to be defined and
   published to a data store, as well as queried and retrieved from the



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   data store for the explicit use of posture collection and evaluation.
   It is expected that multiple information models will be supported to
   address the information needed to support the exchange of endpoint
   metadata, and the collection and evaluation of endpoint posture
   attribute values.  It is likely that multiple data models will be
   used to express these information models requiring specialized or
   extensible content data stores.

   The building blocks of this use case are:

   Content Definition:  Defining the content to drive collection and
         evaluation.  This may include evaluating existing stores of
         content to find content to reuse and the creation of new
         content.  Developed content will be based on available data
         models which may be standardized or proprietary.

   Content Publication:  The capability to publish content to a content
         data store for further use.  Published content may be made
         publicly available or may be based on an authorization decision
         using authenticated credentials.  As a result, the visibility
         of content to an operator or application may be public,
         enterprise-scoped, private, or controlled within any other
         scope.

   Content Query:  An operator or application should be able to query a
         content data store using a set of specified criteria.  The
         result of the query will be a listing matching the query.  The
         query result listing may contain publication metadata (e.g.,
         create date, modified date, publisher, etc.) and/or the full
         content, a summary, snippet, or the location to retrieve the
         content.

   Content Retrieval:  The act of acquiring one or more specific content
         entries.  This capability is useful if the location of the
         content is known a priori, perhaps as the result of request
         based on decisions made using information from a previous
         query.

   Content Change Detection:  An operator or application needs to
         identify content of interest that is new, updated, or deleted
         in a content data store which they have been authorized to
         access.

   These building blocks are used to enable acquisition of various
   instances of content based on specific data models that are used to
   drive assessment planning (see section 2.1.2), posture attribute
   value collection (see section 2.1.3), and posture evaluation (see
   section 2.1.4).



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2.1.2.  Endpoint Identification and Assessment Planning

   This use case describes the process of discovering endpoints,
   understanding their composition, identifying the desired state to
   assess against, and calculating what posture attributes to collect to
   enable evaluation.  This process may be a set of manual, automated,
   or hybrid steps that are performed for each assessment.

   The building blocks of this use case are:

   Endpoint Discovery:  The purpose of discovery is to determine the
         type of endpoint to be posture assessed.

         QUESTION: Is it just the type?  Or is it to identify what
         endpoint instances to target for assessment using metadata such
         as the endpoint's organizationally expected type (e.g.,
         expected function/role, etc.)

   Identify Endpoint Targets  Determine the candidate endpoint target(s)
         to perform the assessment against.  Depending on the assessment
         trigger, a single endpoint may be targeted or multiple
         endpoints may be targeted based on discovered endpoint
         metadata.  This may be driven by content that describes the
         applicable targets for assessment.  In this case the Content
         Query and/or Content Retrieval building blocks (see section
         2.1.1) may be used to acquire this content.

   Endpoint Component Inventory:  To determine what applicable desired
         states should be assessed, it is first necessary to acquire the
         inventory of software, hardware, and accounts associated with
         the targeted endpoint(s).  If the assessment of the endpoint is
         not dependant on the component inventory, then this capability
         is not required for use in performing the assessment.  This
         process can be treated as a collection use case for specific
         posture attributes.  In this case the building blocks for
         Endpoint Posture Attribute Value Collection (see section 2.1.3)
         can be used.

   Posture Attribute Identification:  Once the endpoint targets and
         component inventory is known, it is then necessary to calculate
         what posture attributes are required to be collected to perform
         the evaluation.  If this is driven by content, then the Content
         Query and/or Content Retrieval building blocks (see section
         2.1.1) may be used to acquire this content.

   QUESTION: Are we missing a building block that determines what
   previously collected data, if any, is suitable for evaluation and
   what data needs to be actually collected?



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   At this point the set of posture attribute values to use for
   evaluation are known and they can be collected if necessary (see
   section 2.1.3).

2.1.3.  Endpoint Posture Attribute Value Collection

   This use case describes the process of collecting a set of posture
   attribute values related to one or more endpoints.  This use case can
   be initiated by a variety of triggers including:

   1.  A posture change or significant event on the endpoint.

   2.  A network event (e.g., endpoint connects to a network/VPN,
       specific netflow is detected).

   3.  Due to a scheduled or ad hoc collection task.

   The building blocks of this use case are:

   Collection Content Acquisition:  If content is required to drive the
         collection of posture attributes values, this capability is
         used to acquire this content from one or more content data
         stores.  Depending on the trigger, the specific content to
         acquire might be known.  If not, it may be necessary to
         determine the content to use based on the component inventory
         or other assessment criteria.  The Content Query and/or Content
         Retrieval building blocks (see section 2.1.1) may be used to
         acquire this content.

   Posture Attribute Value Collection:  The accumulation of posture
         attribute values.  This may be based on collection content that
         is associated with the posture attributes.

   Once the posture attribute values are collected, they may be
   persisted for later use or they may be immediately used for posture
   evaluation.

2.1.4.  Posture Evaluation

   This use case describes the process of evaluating collected posture
   attribute values representing actual endpoint state against the
   expected state selected for the assessment.  This use case can be
   initiated by a variety of triggers including:

   1.  A posture change or significant event on the endpoint.

   2.  A network event (e.g., endpoint connects to a network/VPN,
       specific netflow is detected).



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   3.  Due to a scheduled or ad hoc evaluation task.

   The building blocks of this use case are:

   Posture Attribute Value Query:  If previously collected posture
         attribute values are needed, the appropriate data stores are
         queried to retrieve them.  If all posture attribute values are
         provided directly for evaluation, then this capability may not
         be needed.

   Evaluation Content Acquisition:  If content is required to drive the
         evaluation of posture attributes values, this capability is
         used to acquire this content from one or more content data
         stores.  Depending on the trigger, the specific content to
         acquire might be known.  If not, it may be necessary to
         determine the content to use based on the component inventory
         or other assessment criteria.  The Content Query and/or Content
         Retrieval building blocks (see section 2.1.1) may be used to
         acquire this content.

   Posture Attribute Evaluation:  The comparison of posture attribute
         values against their expected results as expressed in the
         specified content.  The result of this comparison is output as
         a set of posture evaluation results.

   Completion of this process represents a complete assessment cycle as
   defined in section Section 2.

2.1.5.  Mining the Database

   This use case describes the need to analyze previously collected
   posture attribute values from one or more endpoints.  This is an
   alternate use case to Posture Evaluation (see section 2.1.4 that uses
   collected posture attributes values for analysis processes that may
   do more than evaluating expected vs.  actual state(s).

   The building blocks of this use case are:

   Query:  Query a data store for specific posture attribute values.

   Change Detection:  An operator should have a mechanism to detect the
         availability of new or changes to existing posture attribute
         values.  The timeliness of detection may vary from immediate to
         on demand.  Having the ability to filter what changes are
         detected will allow the operator to focus on the changes that
         are relevant to their use.





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   QUESTION: Does this warrant a separate use case, or should this be
   incorporated into the previous use case?

2.2.  Usage Scenarios

   In this section, we describe a number of usage scenarios that utilize
   aspects of endpoint posture assessment.  These are examples of common
   problems that can be solved with the building blocks defined above.

2.2.1.  Definition and Publication of Automatable Configuration Guides

   A vendor manufactures a number of specialized endpoint devices.  They
   also develop and maintain an operating system for these devices that
   enables end-user organizations to configure a number of security and
   operational settings.  As part of their customer support activities,
   they publish a number of secure configuration guides that provide
   minimum security guidelines for configuring their devices.

   Each guide they produce applies to a specific model of device and
   version of the operating system and provides a number of specialized
   configurations depending on the devices intended function and what
   add-on hardware modules and software licenses are installed on the
   device.  To enable their customers to evaluate the security posture
   of their devices to ensure that all appropriate minimal security
   settings are enabled, they publish an automatable configuration
   checklist using a popular data format that defines what settings to
   collect using a network management protocol and appropriate values
   for each setting.  They publish these checklist to a public content
   repository that customers can query to retrieve applicable checklist
   for their deployed specialized endpoint devices.

   Automatable configuration checklist could also come from sources
   other than a device vendor, such as industry groups or regulatory
   authorities, or enterprises could develop their own checklists.

   This usage scenario employs the following building blocks defined in
   Section 2.1.1 above:

   Content Definition:  To allow content to be defined using
         standardized or proprietary data models that will drive
         Collection and Evaluation.

   Content Publication:  Providing a mechanism to publish created
         content to a content data store.

   Content Query:  To locate and select existing content that may be
         reused.




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   Content Retrieval  To retrieve specific content from a content data
         store for editing.

   While each building block can be used in a manual fashion by a human
   operator, it is also likely that these capabilities will be
   implemented together in some form of a content editor or generator
   application.

2.2.2.  Automated Checklist Verification

   A financial services company operates a heterogeneous IT environment.
   In support of their risk management program, they utilize vendor
   provided automatable security configuration checklists for each
   operating system and application used within their IT environment.
   Multiple checklists are used from different vendors to insure
   adequate coverage of all IT assets.

   To identify what checklists are needed, they use automation to gather
   an inventory of the software versions utilized by all IT assets in
   the enterprise.  This data gathering will involve querying existing
   data stores of previously collected endpoint software inventory
   posture data and actively collecting data from reachable endpoints as
   needed utilizing network and systems management protocols.
   Previously collected data may be provided by periodic data
   collection, network connection-driven data collection, or ongoing
   event-driven monitoring of endpoint posture changes.

   Using the gathered hardware and software inventory data and
   associated asset management data that may indicate the organizational
   defined functions of each endpoint, checklist content is queried,
   located and downloaded from the appropriate vendor and 3rd-party
   content repositories for the appropriate checklists.  This content is
   cached locally to reduce the need to download the checklist content
   multiple times.

   Driven by the setting data provided in the checklist, a combination
   of existing configuration data stores and data collection methods are
   used to gather the appropriate posture attributes from each endpoint.
   Specific data is gathered based on the defined enterprise function
   and software inventory of each endpoint.  The data collection paths
   used to collect software inventory posture will be used again for
   this purpose.  Once the data is gathered, the actual state is
   evaluated against the expected state criteria in each applicable
   checklist.  The results of this evaluation are provided to
   appropriate operators and applications to drive additional business
   logic.





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   Checklists could include searching for indicators of compromise on
   the endpoint (e.g., file hashes); identifying malicious activity
   (e.g. command and control traffic); detecting presence of
   unauthorized/malicious software, hardware, and configuration items;
   and other indicators.

   A checklist can be assessed as a whole, or a specific subset of the
   checklist can be assessed resulting in partial data collection and
   evaluation.

   Checklists could also come from sources other than the application or
   OS vendor, such as industry groups or regulatory authorities, or
   enterprises could develop their own checklists.

   While specific applications for checklists results are out-of-scope
   for current SACM efforts, how the data is used may illuminate
   specific latency and bandwidth requirements.  For this purpose use of
   checklist assessment results may include, but are not limited to:

   o  Detecting endpoint posture deviations as part of a change
      management program to include changes to hardware and software
      inventory including patches, changes to configuration items, and
      other posture aspects.

   o  Determining compliance with organizational policies governing
      endpoint posture.

   o  Searching for current and historic signs of infection by malware
      and determining the scope of infection within an enterprise.

   o  Informing configuration management, patch management, and
      vulnerability mitigation and remediation decisions.

   o  Detecting performance, attack and vulnerable conditions that
      warrant additional network diagnostics, monitoring, and analysis.

   o  Informing network access control decision making for wired,
      wireless, or VPN connections.

   This usage scenario employs the following building blocks defined in
   Section 2.1.1 above:

   Endpoint Discovery:  The purpose of discovery is to determine the
         type of endpoint to be posture assessed.

   Identify Endpoint Targets:  To identify what potential endpoint
         targets the checklist should apply to based on organizational
         policies.



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   Endpoint Component Inventory:  Collecting and consuming the software
         and hardware inventory for the target endpoints.

   Posture Attribute Identification:  To determine what data needs to be
         collected to support evaluation, the checklist is evaluated
         against the component inventory and other endpoint metadata to
         determine the set of posture attribute values that are needed.

   Collection Content Acquisition:  Based on the identified posture
         attributes, the application will query appropriate content data
         stores to find the "applicable" data collection content for
         each endpoint in question.

   Posture Attribute Value Collection:  For each endpoint, the values
         for the required posture attributes are collected.

   Posture Attribute Value Query:  If previously collected posture
         attribute values are used, they are queried from the
         appropriate data stores for the target endpoint(s).

   Evaluation Content Acquisition:  Any content that is needed to
         support evaluation is queried and retrieved.

   Posture Attribute Evaluation:  The resulting posture attribute values
         from previous Collection processes are evaluated using the
         evaluation content to provide a set of posture results.

2.2.3.  Detection of Posture Deviations

   Example corporation has established secure configuration baselines
   for each different type of endpoint within their enterprise
   including: network infrastructure, mobile, client, and server
   computing platforms.  These baselines define an approved list of
   hardware, software (i.e., operating system, applications, and
   patches), and associated required configurations.  When an endpoint
   connects to the network, the appropriate baseline configuration is
   communicated to the endpoint based on its location in the network,
   the expected function of the device, and other asset management data.
   It is checked for compliance with the baseline indicating any
   deviations to the device's operators.  Once the baseline has been
   established, the endpoint is monitored for any change events
   pertaining to the baseline on an ongoing basis.  When a change occurs
   to posture defined in the baseline, updated posture information is
   exchanged allowing operators to be notified and/or automated action
   to be taken.

   Like the Automated Checklist Verification usage scenario (see section
   2.2.2), this usage scenario supports assessment of checklists.  It



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   differs from that scenario by monitoring for specific endpoint
   posture changes on an ongoing basis.  When the endpoint detects a
   posture change, an alert is generated identifying the specific
   changes in posture allowing a delta assessment to be performed
   instead of a full assessment in the previous case.  This usage
   scenario employs the same building blocks as Automated Checklist
   Verification (see section 2.2.2).  It differs slightly in how it uses
   the following building blocks:

   Endpoint Component Inventory:  Additionally, changes to the hardware
         and software inventory are monitored, with changes causing
         alerts to be issued.

   Posture Attribute Value Collection:  After the initial assessment,
         posture attributes are monitored for changes.  If any of the
         selected posture attribute values change, an alert is issued.

   Posture Attribute Value Query:  The previous state of posture
         attributes are tracked, allowing changes to be detected.

   Posture Attribute Evaluation:  After the initial assessment, a
         partial evaluation is performed based on changes to specific
         posture attributes.

   This usage scenario highlights the need to query a data store to
   prepare a compliance report for a specific endpoint and also the need
   for a change in endpoint state to trigger Collection and Evaluation.

2.2.4.  Endpoint Information Analysis and Reporting

   Freed from the drudgery of manual endpoint compliance monitoring, one
   of the security administrators at Example Corporation notices (not
   using SACM standards) that five endpoints have been uploading lots of
   data to a suspicious server on the Internet.  The administrator
   queries data stores for specific endpoint posture to see what
   software is installed on those endpoints and finds that they all have
   a particular program installed.  She then queries the appropriate
   data stores to see which other endpoints have that program installed.
   All these endpoints are monitored carefully (not using SACM
   standards), which allows the administrator to detect that the other
   endpoints are also infected.

   This is just one example of the useful analysis that a skilled
   analyst can do using data stores of endpoint posture.

   This usage scenario employs the following building blocks defined in
   Section 2.1.1 above:




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   Posture Attribute Value Query:  Previously collected posture
         attribute values are queried from the appropriate data stores
         for the target endpoint(s).

         QUESTION: Should we include other building blocks here?

   This usage scenario highlights the need to query a repository for
   attributes to see which attributes certain endpoints have in common.

2.2.5.  Asynchronous Compliance/Vulnerability Assessment at Ice Station
        Zebra

   A university team receives a grant to do research at a government
   facility in the arctic.  The only network communications will be via
   an intermittent low-speed high-latency high-cost satellite link.
   During their extended expedition they will need to show continue
   compliance with the security policies of the university, the
   government, and the provider of the satellite network as well as keep
   current on vulnerability testing.  Interactive assessments are
   therefore not reliable, and since the researchers have very limited
   funding they need to minimize how much money they spend on network
   data.

   Prior to departure they register all equipment with an asset
   management system owned by the university, which will also initiate
   and track assessments.

   On a periodic basis -- either after a maximum time delta or when the
   content repository has received a threshold level of new
   vulnerability definitions -- the university uses the information in
   the asset management system to put together a collection request for
   all of the deployed assets that encompasses the minimal set of
   artifacts necessary to evaluate all three security policies as well
   as vulnerability testing.

   In the case of new critical vulnerabilities this collection request
   consists only of the artifacts necessary for those vulnerabilities
   and collection is only initiated for those assets that could
   potentially have a new vulnerability.

   [Optional] Asset artifacts are cached in a local CMDB.  When new
   vulnerabilities are reported to the content repository, a request to
   the live asset is only done if the artifacts in the CMDB are
   incomplete and/or not current enough.

   The collection request is queued for the next window of connectivity.
   The deployed assets eventually receive the request, fulfill it, and
   queue the results for the next return opportunity.



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   The collected artifacts eventually make it back to the university
   where the level of compliance and vulnerability expose is calculated
   and asset characteristics are compared to what is in the asset
   management system for accuracy and completeness.

   Like the Automated Checklist Verification usage scenario (see section
   2.2.2), this usage scenario supports assessment of checklists.  It
   differs from that scenario in how content, collected posture values,
   and evaluation results are exchanged due to bandwidth limitations and
   availability.  This usage scenario employs the same building blocks
   as Automated Checklist Verification (see section 2.2.2).  It differs
   slightly in how it uses the following building blocks:

   Endpoint Component Inventory:  It is likely that the component
         inventory will not change.  If it does, this information will
         need to be batched and transmitted during the next
         communication window.

   Collection Content Acquisition:  Due to intermittent communication
         windows and bandwidth constraints, changes to collection
         content will need to batched and transmitted during the next
         communication window.  Content will need to be cached locally
         to avoid the need for remote communications.

   Posture Attribute Value Collection:  The specific posture attribute
         values to be collected are identified remotely and batched for
         collection during the next communication window.  If a delay is
         introduced for collection to complete, results will need to be
         batched and transmitted in the same way.

   Posture Attribute Value Query:  Previously collected posture
         attribute values will be stored in a remote data store for use
         at the university

   Evaluation Content Acquisition:  Due to intermittent communication
         windows and bandwidth constraints, changes to evaluation
         content will need to batched and transmitted during the next
         communication window.  Content will need to be cached locally
         to avoid the need for remote communications.

   Posture Attribute Evaluation:  Due to the caching of posture
         attribute values and evaluation content, evaluation may be
         performed at both the university campus as well as the
         satellite site.

   This usage scenario highlights the need to support low-bandwidth,
   intermittent, or high-latency links.




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2.2.6.  Identification and Retrieval of Repository Content

   In preparation for performing an assessment, an operator or
   application will need to identify one or more content data stores
   that contain the content entries necessary to perform data collection
   and evaluation tasks.  The location of a given content entry will
   either be known a priori or known content repositories will need to
   be queried to retrieve applicable content.

   To query content it will be necessary to define a set of search
   criteria.  This criteria will often utilize a logical combination of
   publication metadata (e.g. publishing identity, create time,
   modification time) and content-specific criteria elements.  Once the
   criteria is defined, one or more content data stores will need to be
   queried generating a result set.  Depending on how the results are
   used, it may be desirable to return the matching content directly, a
   snippet of the content matching the query, or a resolvable location
   to retrieve the content at a later time.  The content matching the
   query will be restricted based the authorized level of access allowed
   to the requester.

   If the location of content is identified in the query result set, the
   content will be retrieved when needed using one or more content
   retrieval requests.  A variation on this approach would be to
   maintain a local cache of previously retrieved content.  In this
   case, only content that is determined to be stale by some measure
   will be retrieved from the remote content store.

   Alternately, content can be discovered by iterating over content
   published with a given context within a content repository.  Specific
   content can be selected and retrieved as needed.

   This usage scenario employs the following building blocks defined in
   Section 2.1.1 above:

   Content Query:  Enables an operator or application to query one or
         more content data stores for content using a set of specified
         criteria.

   Content Retrieval:  If content locations are returned in the query
         result set, then specific content entries can be retrieved and
         possibly cached locally.









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2.2.7.  Content Change Detection

   An operator or application may need to identify new, updated, or
   deleted content in a content repository for which they have been
   authorized to access.  This may be achieved by querying or iterating
   over content in a content repository, or through a notification
   mechanism that alerts to changes made to a content repository.

   Once content changes have been determined, data collection and
   evaluation activities may be triggered.

   This usage scenario employs the following building blocks defined in
   Section 2.1.1 above:

   Content Change Detection:  Allows an operator or application to
         identify content changes in a content data store which they
         have been authorized to access.

   Content Retrieval:  If content locations are provided by the change
         detection mechanism, then specific content entries can be
         retrieved and possibly cached locally.

2.2.8.  Others...

   Additional use cases will be identified as we work through other
   domains.

3.  IANA Considerations

   This memo includes no request to IANA.

4.  Security Considerations

   This memo documents, for Informational purposes, use cases for
   security automation.  While it is about security, it does not affect
   security.

5.  Acknowledgements

   The National Institute of Standards and Technology (NIST) and/or the
   MITRE Corporation have developed specifications under the general
   term "Security Automation" including languages, protocols,
   enumerations, and metrics.

   Adam Montville edited early versions of this draft.

   Kathleen Moriarty, and Stephen Hanna contributed text describing the
   scope of the document.



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   Gunnar Engelbach, Steve Hanna, Chris Inacio, Kent Landfield, Lisa
   Lorenzin, Adam Montville, Kathleen Moriarty, Nancy Cam-Winget, and
   Aron Woland provided use cases text for various revisions of this
   draft.

6.  Change Log

6.1.  -04- to -05-

   Changes in this revision are focused on section 2 and the subsequent
   subsections:

   o  Moved existing use cases to a subsection titled "Usage Scenarios".

   o  Added a new subsection titled "Use Cases" to describe the common
      use cases and building blocks used to address the "Usage
      Scenarios".  The new use cases are:

      *  Define, Publish, Query and Retrieve Content

      *  Endpoint Identification and Assessment Planning

      *  Endpoint Posture Attribute Value Collection

      *  Posture Evaluation

      *  Mining the Database

   o  Added a listing of building blocks used for all usage scenarios.

   o  Combined the following usage scenarios into "Automated Checklist
      Verification": "Organizational Software Policy Compliance",
      "Search for Signs of Infection", "Vulnerable Endpoint
      Identification", "Compromised Endpoint Identification",
      "Suspicious Endpoint Behavior", "Traditional endpoint assessment
      with stored results", "NAC/NAP connection with no stored results
      using an endpoint evaluator", and "NAC/NAP connection with no
      stored results using a third-party evaluator".

   o  Created new usage scenario "Identification and Retrieval of
      Repository Content" by combining the following usage scenarios:
      "Repository Interaction - A Full Assessment" and "Repository
      Interaction - Filtered Delta Assessment"

   o  Renamed "Register with repository for immediate notification of
      new security vulnerability content that match a selection filter"
      to "Content Change Detection" and generalized the description to
      be neutral to implementation approaches.



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   o  Removed out-of-scope usage scenarios: "Remediation and Mitigation"
      and "Direct Human Retrieval of Ancillary Materials"

   Updated acknowledgements to recognize those that helped with editing
   the use case text.

6.2.  -03- to -04-

   Added four new use cases regarding content repository.

6.3.  -02- to -03-

   Expanded the workflow description based on ML input.

   Changed the ambiguous "assess" to better separate data collection
   from evaluation.

   Added use case for Search for Signs of Infection.

   Added use case for Remediation and Mitigation.

   Added use case for Endpoint Information Analysis and Reporting.

   Added use case for Asynchronous Compliance/Vulnerability Assessment
   at Ice Station Zebra.

   Added use case for Traditional endpoint assessment with stored
   results.

   Added use case for NAC/NAP connection with no stored results using an
   endpoint evaluator.

   Added use case for NAC/NAP connection with no stored results using a
   third-party evaluator.

   Added use case for Compromised Endpoint Identification.

   Added use case for Suspicious Endpoint Behavior.

   Added use case for Vulnerable Endpoint Identification.

   Updated Acknowledgements









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6.4.  -01- to -02-

   Changed title

   removed section 4, expecting it will be moved into the requirements
   document.

   removed the list of proposed capabilities from section 3.1

   Added empty sections for Search for Signs of Infection, Remediation
   and Mitigation, and Endpoint Information Analysis and Reporting.

   Removed Requirements Language section and rfc2119 reference.

   Removed unused references (which ended up being all references).

6.5.  -00- to -01-

   o  Work on this revision has been focused on document content
      relating primarily to use of asset management data and functions.

   o  Made significant updates to section 3 including:

      *  Reworked introductory text.

      *  Replaced the single example with multiple use cases that focus
         on more discrete uses of asset management data to support
         hardware and software inventory, and configuration management
         use cases.

      *  For one of the use cases, added mapping to functional
         capabilities used.  If popular, this will be added to the other
         use cases as well.

      *  Additional use cases will be added in the next revision
         capturing additional discussion from the list.

   o  Made significant updates to section 4 including:

      *  Renamed the section heading from "Use Cases" to "Functional
         Capabilities" since use cases are covered in section 3.  This
         section now extrapolates specific functions that are needed to
         support the use cases.

      *  Started work to flatten the section, moving select subsections
         up from under asset management.





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      *  Removed the subsections for: Asset Discovery, Endpoint
         Components and Asset Composition, Asset Resources, and Asset
         Life Cycle.

      *  Renamed the subsection "Asset Representation Reconciliation" to
         "Deconfliction of Asset Identities".

      *  Expanded the subsections for: Asset Identification, Asset
         Characterization, and Deconfliction of Asset Identities.

      *  Added a new subsection for Asset Targeting.

      *  Moved remaining sections to "Other Unedited Content" for future
         updating.

6.6.  draft-waltermire-sacm-use-cases-05 to draft-ietf-sacm-use-cases-00

   o  Transitioned from individual I/D to WG I/D based on WG consensus
      call.

   o  Fixed a number of spelling errors.  Thank you Erik!

   o  Added keywords to the front matter.

   o  Removed the terminology section from the draft.  Terms have been
      moved to: draft-dbh-sacm-terminology-00

   o  Removed requirements to be moved into a new I/D.

   o  Extracted the functionality from the examples and made the
      examples less prominent.

   o  Renamed "Functional Capabilities and Requirements" section to "Use
      Cases".

      *  Reorganized the "Asset Management" sub-section.  Added new text
         throughout.

         +  Renamed a few sub-section headings.

         +  Added text to the "Asset Characterization" sub-section.

   o  Renamed "Security Configuration Management" to "Endpoint
      Configuration Management".  Not sure if the "security" distinction
      is important.

      *  Added new sections, partially integrated existing content.




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      *  Additional text is needed in all of the sub-sections.

   o  Changed "Security Change Management" to "Endpoint Posture Change
      Management".  Added new skeletal outline sections for future
      updates.

6.7.  waltermire -04- to -05-

   o  Are we including user activities and behavior in the scope of this
      work?  That seems to be layer 8 stuff, appropriate to an IDS/IPS
      application, not Internet stuff.

   o  I removed the references to what the WG will do because this
      belongs in the charter, not the (potentially long-lived) use cases
      document.  I removed mention of charter objectives because the
      charter may go through multiple iterations over time; there is a
      website for hosting the charter; this document is not the correct
      place for that discussion.

   o  I moved the discussion of NIST specifications to the
      acknowledgements section.

   o  Removed the portion of the introduction that describes the
      chapters; we have a table of concepts, and the existing text
      seemed redundant.

   o  Removed marketing claims, to focus on technical concepts and
      technical analysis, that would enable subsequent engineering
      effort.

   o  Removed (commented out in XML) UC2 and UC3, and eliminated some
      text that referred to these use cases.

   o  Modified IANA and Security Consideration sections.

   o  Moved Terms to the front, so we can use them in the subsequent
      text.

   o  Removed the "Key Concepts" section, since the concepts of ORM and
      IRM were not otherwise mentioned in the document.  This would seem
      more appropriate to the arch doc rather than use cases.

   o  Removed role=editor from David Waltermire's info, since there are
      three editors on the document.  The editor is most important when
      one person writes the document that represents the work of
      multiple people.  When there are three editors, this role marking
      isn't necessary.




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   o  Modified text to describe that this was specific to enterprises,
      and that it was expected to overlap with service provider use
      cases, and described the context of this scoped work within a
      larger context of policy enforcement, and verification.

   o  The document had asset management, but the charter mentioned
      asset, change, configuration, and vulnerability management, so I
      added sections for each of those categories.

   o  Added text to Introduction explaining goal of the document.

   o  Added sections on various example use cases for asset management,
      config management, change management, and vulnerability
      management.

7.  References

7.1.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119, March 1997.

7.2.  Informative References

   [RFC2865]  Rigney, C., Willens, S., Rubens, A., and W. Simpson,
              "Remote Authentication Dial In User Service (RADIUS)", RFC
              2865, June 2000.

Authors' Addresses

   David Waltermire
   National Institute of Standards and Technology
   100 Bureau Drive
   Gaithersburg, Maryland  20877
   USA

   Email: david.waltermire@nist.gov


   David Harrington
   Effective Software
   50 Harding Rd
   Portsmouth, NH  03801
   USA

   Email: ietfdbh@comcast.net





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