wdiff rfc7632.original rfc7632.txt

Security Automation and Continuous Monitoring WG
Internet Engineering Task Force (IETF) D. Waltermire
Internet-Draft
Request for Comments: 7632 NIST
Intended status:
Category: Informational D. Harrington
Expires: January 2, 2016
ISSN: 2070-1721 Effective Software
July 1,
September 2015

Endpoint Security Posture Assessment - Assessment: Enterprise Use Cases
draft-ietf-sacm-use-cases-10

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

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provisions of BCP 78 and BCP 79.

Internet-Drafts are working documents not an Internet Standards Track specification; it is
published for informational purposes.

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This Internet-Draft will expire on January 2, 2016.
http://www.rfc-editor.org/info/rfc7632.

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Table of Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Endpoint Posture Assessment . . . . . . . . . . . . . . . . . 4 3
2.1. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1.1. Define, Publish, Query Query, and Retrieve Security
Automation Data . . . . . . . . . . . . . . . . . . . 5
2.1.2. Endpoint Identification and Assessment Planning . . . 9
2.1.3. Endpoint Posture Attribute Value Collection . . . . . 10
2.1.4. Posture Attribute Evaluation . . . . . . . . . . . . 11
2.2. Usage Scenarios . . . . . . . . . . . . . . . . . . . . . 12
2.2.1. Definition and Publication of Automatable
Configuration Checklists . . . . . . . . . . . . . . 12
2.2.2. Automated Checklist Verification . . . . . . . . . . 13
2.2.3. Detection of Posture Deviations . . . . . . . . . . . 16
2.2.4. Endpoint Information Analysis and Reporting . . . . . 17
2.2.5. Asynchronous Compliance/Vulnerability Assessment at
Ice Station Zebra . . . . . . . . . . . . . . . . . . 18 17
2.2.6. Identification and Retrieval of Guidance . . . . . . 20 19
2.2.7. Guidance Change Detection . . . . . . . . . . . . . . 21 20
3. IANA Security Considerations . . . . . . . . . . . . . . . . . . . . . 21
4. Security Considerations Informative References . . . . . . . . . . . . . . . . . . . 21
5.
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 22
6. Change Log . . . . . . . . . . . . . . . . . . . . . . . . . 22
6.1. -08- to -09- . . . . . . . . . . . . . . . . . . . . .
Authors' Addresses . 22
6.2. -07- to -08- . . . . . . . . . . . . . . . . . . . . . . 22
6.3. -06-

1. Introduction

This document describes the core set of use cases for endpoint
posture assessment for enterprises. It provides a discussion of
these use cases and associated building-block capabilities. The
described use cases support:

o securely collecting and aggregating configuration and operational
data, and

o evaluating that data to -07- . . . . . . . . . . . . . . . . . . . . . . 23
6.4. -05- to -06- . . . . . . . . . . . . . . . . . . . . . . 23
6.5. -04- to -05- . . . . . . . . . . . . . . . . . . . . . . 23
6.6. -03- to -04- . . . . . . . . . . . . . . . . . . . . . . 24
6.7. -02- to -03- . . . . . . . . . . . . . . . . . . . . . . 24
6.8. -01- to -02- . . . . . . . . . . . . . . . . . . . . . . 25
6.9. -00- to -01- . . . . . . . . . . . . . . . . . . . . . . 25
6.10. draft-waltermire-sacm-use-cases-05 to draft-ietf-sacm-
use-cases-00 . . . . . . . . . . . . . . . . . . . . . . 26
6.11. waltermire -04- to -05- . . . . . . . . . . . . . . . . . 27
7. Informative References . . . . . . . . . . . . . . . . . . . 28
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 28

1. Introduction

This document describes the core set of use cases for endpoint
posture assessment for enterprises. It provides a discussion of
these use cases and associated building block capabilities. The
described use cases support:

o securely collecting and aggregating configuration and operational
data, and

o evaluating that data to determine the security posture of
individual endpoints.

Additionally, this document describes a set of usage scenarios that
provide examples for using the use cases and associated building
blocks to address a variety of operational functions.

These operational use cases and related usage scenarios cross many IT
security domains. The use cases enable the derivation of common:

o concepts that are expressed as building blocks in this document,

o characteristics to inform development of a requirements document

o information concepts to inform development of an information model
document, and

o functional capabilities to inform development of an architecture
document.

Together these ideas will be used to guide development of vendor-
neutral, interoperable standards for collecting, 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. When considering this overlap, 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.

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 security automation data that is needed to
drive and feed data collection and evaluation processes.

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.

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

3. An 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. Implementations should
be able to support (possibly mixed) sets of standardized and
proprietary attributes.

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.

G. The evaluator reports the evaluation result for the requested
assessment, in a standardized or proprietary format, such as
a report, a log entry, a database entry, or a notification.

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 data. Each use
case is defined by a short summary containing a simple problem
statement, followed by a discussion of related concepts, and a
listing of associated building blocks which represent the
capabilities needed to support the use case. These use cases and
building blocks identify separate units of functionality that may be
supported by different components of an architectural model.

2.1.1. Define, Publish, Query and Retrieve Security Automation Data

This use case describes the need for security automation data to be
defined and published to one or more data stores, as well as queried
and retrieved from these data stores for the explicit use of posture
collection and evaluation.

Security automation data is a general concept that refers to any data
expression that may be generated and/or used as part of the process
of collecting and evaluating endpoint posture. Different types of
security automation data will generally fall into one of three
categories:

Guidance: Instructions and related metadata that guide the attribute
collection and evaluation processes. The purpose of this data
is to allow implementations to be data-driven enabling their
behavior to be customized without requiring changes to deployed
software.

This type of data tends to change in units of months and days.
In cases where assessments are made more dynamic, it may be
necessary to handle changes in the scope of hours or minutes.
This data will typically be provided by large organizations,
product vendors, and some 3rd-parties. Thus, it will tend to
be shared across large enterprises and customer communities.
In some cases access may be controlled to specific
authenticated users. In other cases, the data may be provided
broadly with little to no access control.

This includes:

* Listings of attribute identifiers for which values may be
collected and evaluated

* Lists of attributes that are to be collected along with
metadata that includes: when to collect a set of attributes
based on a defined interval or event, the duration of
collection, and how to go about collecting a set of
attributes.

* Guidance that specifies how old collected data can be to be
used for evaluation.

* Policies that define how to target and perform the
evaluation of a set of attributes for different kinds or
groups of endpoints and the assets they are composed of. In
some cases it may be desirable to maintain hierarchies of
policies as well.

* References to human-oriented data that provide technical,
organizational, and/or policy context. This might include
references to: best practices documents, legal guidance and
legislation, and instructional materials related to the
automation data in question.

Attribute Data: Data collected through automated and manual
mechanisms describing organizational and posture details
pertaining to specific endpoints and the assets that they are
composed of (e.g., hardware, software, accounts). The purpose
of this type of data is to characterize an endpoint (e.g.,
endpoint type, organizationally expected function/role) and to
provide actual and expected state data pertaining to one or
more endpoints. This data is used to determine what posture
attributes to collect from which endpoints and to feed one or
more evaluations.

This type of data tends to change in units of days, minutes, a
seconds with posture attribute values typically changing more
frequently than endpoint characterizations. This data tends to
be organizationally and endpoint specific, with specific
operational groups of endpoints tending to exhibit similar
attribute profiles. This data will generally not be shared
outside an organizational boundary and will generally require
authentication with specific access controls.

This includes:

* Endpoint characterization data that describes the endpoint
type, organizationally expected function/role, etc.

* Collected endpoint posture attribute values and related
context including: time of collection, tools used for
collection, etc.

* Organizationally defined expected posture attribute values
targeted to specific evaluation guidance and endpoint
characteristics. This allows a common set of guidance to be
parameterized for use with different groups of endpoints.

Processing Artifacts: Data that is generated by, and is specific to,
an individual assessment process. This data may be used as
part of the interactions between architectural components to
drive and coordinate collection and evaluation activities. Its
lifespan will be bounded by the lifespan of the assessment. It
may also be exchanged and stored to provide historic context
around an assessment activity so that individual assessments
can be grouped, evaluated, and reported in an enterprise
context.

This includes:

* The identified set of endpoints for which an assessment
should be performed.

* The identified set of posture attributes that need to be
collected from specific endpoints to perform an evaluation.

* The resulting data generated by an evaluation process
including the context of what was assessed, what it was
assessed against, what collected data was used, when it was
collected, and when the evaluation was performed.

The information model for security automation data must support a
variety of different data types as described above, along with the
associated metadata that is needed to support publication, query, and
retrieval operations. It is expected that multiple data models will
be used to express specific data types requiring specialized or
extensible determine the security automation data repositories. The different
temporal characteristics, access patterns, and access control
dimensions posture of each data type may also require different protocols and
data models to be supported furthering the potential requirement for
specialized data repositories. See [RFC3444] for
individual endpoints.

Additionally, this document describes a description and
discussion set of distinctions between an information and data model. It
is likely usage scenarios that additional kinds of data will be identified through
the process of defining requirements and an architectural model.
Implementations supporting this building block will need to be
extensible to accommodate the addition of new types of data, both
proprietary or (preferably)
provide examples for using a standard format.

The building blocks of this the use case are:

Data Definition: Security automation data will guide and inform
collection and evaluation processes. This data may be designed
by a variety of roles - application implementers may build
security automation data into their applications;
administrators may define guidance based on organizational
policies; operators may define guidance and attribute data as
needed for evaluation at runtime, cases and so on. Data producers
may choose to reuse data from existing stores of security
automation data and/or may create new data. Data producers may
develop data based on available standardized or proprietary
data models, such as those used for network management and/or
host management.

Data Publication: The capability to enable data producers to publish
data to a security automation data store for further use.
Published data may be made publicly available or access may be
based on an authorization decision using authenticated
credentials. As associated building
blocks to address a result, the visibility variety of specific operational functions.

These operational use cases and related usage scenarios cross many IT
security
automation data to an operator or application may be public,
enterprise-scoped, private, or controlled within any other
scope.

Data Query: An operator or application should be able domains. The use cases enable the derivation of common:

o concepts that are expressed as building blocks in this document,

o characteristics to query a
security automation data store using inform development of a set requirements document,

o information concepts to inform development of specified
criteria. The result an information model
document, and

o functional capabilities to inform development of the query an architecture
document.

Together, these ideas 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 used to guide development of vendor-
neutral, interoperable standards for collecting, aggregating, and
evaluating data relevant to security posture.

Using this standard data, a summary, snippet, or tools can analyze the location to
retrieve state of endpoints as
well as user activities and behaviour, and evaluate the data.

Data Retrieval: A user, operator, or application acquires one or
more specific security automation data entries. The location
posture of an organization. Common expression of the data may be known a priori, or may be determined based
on decisions made using information from a previous query.

Data Change Detection: An operator should
enable interoperability between tools (whether customized,
commercial, or application needs freely available), and the ability to know when automate
portions of security automation data they interested processes to gain efficiency, react to new
threats in has been published
to, updated in, or deleted from a timely manner, and free up security automation data
store which they have been authorized personnel to access.

These building blocks are used work on
more advanced problems.

The goal is to enable acquisition 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.

The output of various
instances endpoint posture assessment is expected to feed into
additional processes, such as policy-based enforcement of acceptable
state, verification and monitoring of security automation data based on specific data models
that are used controls, and
compliance to drive assessment planning (see section 2.1.2), regulatory requirements.

2. Endpoint Posture Assessment

Endpoint posture attribute value collection (see section 2.1.3), assessment involves orchestrating and posture
evaluation (see section 2.1.4).

2.1.2. Endpoint Identification performing
data collection and Assessment Planning

This use case describes evaluating the process posture of discovering endpoints,
understanding their composition, identifying the desired state to
assess against, and calculating what a given endpoint.
Typically, endpoint posture attributes information is gathered and then
published to collect appropriate data repositories to
enable evaluation. This process may be a set of manual, automated,
or hybrid steps that are performed make collected
information available for each assessment.

The building blocks of this use case are: further analysis supporting organizational
security processes.

Endpoint Discovery: To determine posture assessment typically includes:

o collecting the current or historic presence attributes of
endpoints in a given endpoint;

o making the environment that are attributes available for evaluation and action; and

o verifying that the endpoint's posture
assessment. Endpoints are identified is in support compliance with
enterprise standards and policy.

As part of discovery
using information previously obtained or by using other
collection mechanisms these activities, it is often necessary to gather identification identify and
characterization data. Previously obtained
acquire any supporting security automation data that is needed to
drive and feed data may originate
from sources such as network authentication exchanges.

Endpoint Characterization: The act of acquiring, through automated collection or manual input, and organizing attributes
associated with an endpoint (e.g., type, organizationally
expected function/role, hardware/software versions).

Identify Endpoint Targets: Determine the candidate evaluation processes.

The following is a typical workflow scenario for assessing endpoint
target(s) against which to perform
posture:

1. Some type of trigger initiates the assessment. Depending
on workflow. For example, an
operator or an application might trigger the assessment trigger, process with a single endpoint
request, or multiple
endpoints may be targeted based on characterized the endpoint
attributes. Guidance describing might trigger the assessment process using an
event-driven notification.

2. An operator/application selects one or more target endpoints to
be performed
may contain instructions or references used assessed.

3. An operator/application selects which policies are applicable to determine
the
applicable assessment targets. In this case the Data Query
and/or Data Retrieval building blocks (see section 2.1.1) may
be used

4. For each target:

A. The application determines which (sets of) posture attributes
need to acquire this data.

Endpoint Component Inventory: To determine what applicable desired
states be collected for evaluation. Implementations should
be assessed, it is first necessary able to acquire the
inventory support (possibly mixed) sets of software, hardware, standardized and accounts associated with
the targeted endpoint(s). If the assessment of the endpoint is
not dependent on the these details, then this capability is not
required for use in performing the assessment. This process
can be treated
proprietary attributes.

B. The application might retrieve previously collected
information from a cache or data store, such as a collection use case for specific 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. In this case attributes from the building blocks for
Endpoint Posture Attribute Value Collection (see section 2.1.3)
can target.

D. The application might establish communication with one or
more intermediaries or agents, which may be used.

Posture Attribute Identification: Once local or
external. When establishing connections with an intermediary
or agent, the endpoint targets and application can mutually authenticate their associated asset inventory is known, it is then necessary
to calculate what
identities and determine authorizations, and collect posture
attributes are required to be about the target from the intermediaries or
agents.

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

F. The evaluator compares the desired evaluation. When available,
existing collected posture data is queried attributes with
expected values as expressed in policies.

G. The evaluator reports the evaluation result for the requested
assessment, in a standardized or proprietary format, such as
a report, a log entry, a database entry, or a notification.

2.1. Use Cases

The following subsections detail specific use cases for suitability using the Data
Query building block (see section 2.1.1). Such posture assessment
planning, data is
suitable if it is complete collection, analysis, and current enough for use in related operations
pertaining to the
evaluation. Any unsuitable posture data is identified for
collection.

If this publication and use of supporting data. Each use
case is driven defined by guidance, then the Data Query and/or Data
Retrieval a short summary containing a simple problem
statement, followed by a discussion of related concepts, and a
listing of associated building blocks (see section 2.1.1) may be used to
acquire this data.

At this point that represent the set of posture attribute values capabilities
needed to support the use for
evaluation are known case. These use cases and they can building blocks
identify separate units of functionality that may be collected if necessary (see
section 2.1.3).

2.1.3. Endpoint Posture Attribute Value Collection supported by
different components of an architectural model.

2.1.1. Define, Publish, Query, and Retrieve Security Automation Data

This use case describes the process of collecting a set of posture
attribute values related need for security automation data 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
defined and published to a network/VPN,
specific netflow is detected).

3. A scheduled one or ad hoc collection task.

The building blocks of this use case are:

Collection Guidance Acquisition: If guidance is required to drive more data stores, as well as queried
and retrieved from these data stores for the collection explicit use of posture attributes values, this capability
collection and evaluation.

Security automation data is
used a general concept that refers to acquire this any data from one or more
expression that may be generated and/or used as part of the process
of collecting and evaluating endpoint posture. Different types of
security automation data stores. Depending on the trigger, will generally fall into one of three
categories:

Guidance: Instructions and related metadata that guide the specific guidance attribute
collection and evaluation processes. The purpose of this data
is to allow implementations to acquire might be known. If not, data-driven, thus enabling
their behavior to be customized without requiring changes to
deployed software.

This type of data tends to change in units of months and days.
In cases where assessments are made more dynamic, it may be
necessary to
determine the guidance to use based on handle changes in the component inventory scope of hours or other assessment criteria. The Data Query and/or Data
Retrieval building blocks (see section 2.1.1) may minutes.
This data will typically be used provided by large organizations,
product vendors, and some third parties. Thus, it will tend to
acquire this guidance.

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

Once the posture attribute values are collected, they shared across large enterprises and customer communities.

In some cases, access may be
persisted for later use or they controlled to specific
authenticated users. In other cases, the data may be immediately used for posture
evaluation.

2.1.4. Posture Attribute Evaluation provided
broadly with little to no access control.

This use case represents the action includes:

* Listings of analyzing collected posture attribute identifiers for which values as part of an assessment. The primary focus may be
collected and evaluated.

* Lists of this
use case is attributes that are to support evaluation of actual endpoint state against
the expected state selected for the assessment.

This use case can be initiated by collected along with
metadata that includes: when to collect a variety set of triggers including:

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

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

3. A scheduled defined interval or ad hoc evaluation task.

The building blocks event, the duration of this use case are:

Collected Posture Change Detection: An operator or application has
collection, and how to go about collecting a
mechanism set of
attributes.

* Guidance that specifies how old collected data can be when
used for evaluation.

* Policies that define how to detect target and perform the availability
evaluation of new, a set of attributes for different kinds or changes to
existing, posture attribute values. The timeliness
groups 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 endpoints and the changes that assets they are relevant composed of. In
some cases, it may be desirable to their use
and will enable evaluation maintain hierarchies of
policies as well.

* References to occur dynamically based on
detected changes.

Posture Attribute Value Query: If previously collected posture
attribute values are needed, the appropriate human-oriented data stores are
queried that provide technical,
organizational, and/or policy context. This might include
references to: best practices documents, legal guidance and
legislation, and instructional materials related to retrieve them using the
automation data in question.

Attribute Data: Data Query building block
(see section 2.1.1). If all collected through automated and manual
mechanisms describing organizational and posture attribute values are
provided directly for evaluation, then this capability may not
be needed.

Evaluation Guidance Acquisition: If guidance is required details
pertaining to drive specific endpoints and the evaluation assets that they are
composed of (e.g., hardware, software, accounts). The purpose
of posture attributes values, this capability type of data is
used to acquire this characterize an endpoint (e.g.,
endpoint type, organizationally expected function/role) and to
provide actual and expected state data from pertaining to one or
more security automation endpoints. This data stores. Depending on the trigger, the specific guidance
to acquire might be known. If not, it may be necessary is used to determine the guidance what posture
attributes to use based on the component inventory collect from which endpoints and to feed one or other assessment criteria. The Data Query and/or Data
Retrieval building blocks (see section 2.1.1) may be used
more evaluations.

This type of data tends to
acquire this guidance.

Posture Attribute Evaluation: The comparison change in units of days, minutes,
and seconds, with posture attribute values against their expected values as expressed in the
specified guidance. The result of this comparison is output as
a set of posture evaluation results. Such results include
metadata required typically changing
more frequently than endpoint characterizations. This data
tends to provide a level be organizationally and endpoint specific, with
specific operational groups of assurance endpoints tending to exhibit
similar attribute profiles. Generally, this data will not be
shared outside an organizational boundary and will require
authentication with respect
to specific access controls.

This includes:

* Endpoint characterization data that describes the endpoint
type, organizationally expected function/role, etc.

* Collected endpoint posture attribute data and, therefore, evaluation
results. Examples of such metadata include provenance values and or
availability data.

While the primary focus of this use case is around enabling the
comparison related
context including: time of collection, tools used for
collection, etc.

* Organizationally defined expected vs. actual state, the same building blocks can
support other analysis techniques that are applied to collected posture attribute data (e.g., trending, historic analysis).

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

2.2. Usage Scenarios

In this section, we describe values
targeted to specific evaluation guidance and endpoint
characteristics. This allows a number of usage scenarios that utilize
aspects common set of endpoint posture assessment. These are examples guidance to be
parameterized for use with different groups of common
problems endpoints.

Processing Artifacts: Data that can is generated by, and is specific to,
an individual assessment process. This data may be solved with used as
part of the building blocks defined above.

2.2.1. Definition interactions between architectural components to
drive and Publication of Automatable Configuration
Checklists

A vendor manufactures a number coordinate collection and evaluation activities. Its
lifespan will be bounded by the lifespan of specialized endpoint devices. They the assessment. It
may also develop be exchanged and maintain stored to provide historic context
around an operating system for these devices assessment activity so that
enables end-user organizations to configure a number of security individual assessments
can be grouped, evaluated, and
operational settings. As part reported in an enterprise
context.

This includes:

* The identified set of their customer support activities,
they publish a number endpoints for which an assessment
should be performed.

* The identified set of secure configuration guides posture attributes that provide
minimum security guidelines for configuring their devices.

Each guide they produce applies need to a be
collected from specific model endpoints to perform an evaluation.

* The resulting data generated by an evaluation process
including the context of device what was assessed, what it was
assessed against, what collected data was used, when it was
collected, and
version of when the operating system and provides evaluation was performed.

The information model for security automation data must support a number
variety of specialized
configurations depending on different data types as described above, along with the device's intended function and what
add-on hardware modules
associated metadata that is needed to support publication, query, and software licenses are installed on the
device. To enable their customers
retrieval operations. It is expected that multiple data models will
be used to evaluate the express specific data types requiring specialized or
extensible security posture automation data repositories. The different
temporal characteristics, access patterns, and access control
dimensions of their devices each data type may also require different protocols and
data models to ensure that all appropriate minimal security
settings are enabled, they publish an automatable configuration
checklists using be supported furthering the potential requirement for
specialized data repositories. See [RFC3444] for a popular description and
discussion of distinctions between an information and data format model. It
is likely that defines what settings additional kinds of data will be identified through
the process of defining requirements and an architectural model.
Implementations supporting this building block will need to
collect be
extensible to accommodate the addition of new types of data, whether
proprietary or (preferably) using a network management protocol standard format.

The building blocks of this use case are:

Data Definition: Security automation data will guide and appropriate values
for each setting. They publish these checklists to inform
collection and evaluation processes. This data may be designed
by a public variety of roles -- application implementers may build
security automation data store that customers can query to retrieve applicable
checklist(s) for into their deployed specialized endpoint devices.

Automatable configuration checklist could also come from sources
other than a device vendor, such applications;
administrators may define guidance based on organizational
policies; operators may define guidance and attribute data 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:
needed for evaluation at runtime; and so on. Data Definition: To allow guidance producers
may choose to be defined using reuse data from existing stores of security
automation data and/or may create new data. Data producers may
develop data based on available standardized or proprietary
data models that will drive collection and
evaluation. models, such as those used for network management and/or
host management.

Data Publication: Providing a mechanism The capability to enable data producers to publish created guidance
data to a security automation data store.

Data Query: To locate and select existing guidance that store for further use.
Published data may be made publicly available or access may be
based on an authorization decision using authenticated
credentials. As a result, the visibility of specific security
automation data to an operator or application may be
reused. public,
enterprise-scoped, private, or controlled within any other
scope.

Data Retrieval To retrieve specific guidance from Query: An operator or application should be able to query a
security automation data store for editing.

While each building block can be used in a manual fashion by using a human
operator, it is also likely that these capabilities set of specified
criteria. The result of the query will be
implemented together in some form of a guidance editor listing matching
the query. The query result listing may contain publication
metadata (e.g., create date, modified date, publisher, etc.)
and/or the full data, a summary, snippet, or generator
application.

2.2.2. Automated Checklist Verification the location to
retrieve the data.

Data Retrieval: 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 user, operator, or 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 acquires one or
more specific security 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 entries. The location
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 the data may be provided by periodic data
collection, network connection-driven data collection, known a priori, or may be determined based
on decisions made using information from a previous query.

Data Change Detection: An operator or ongoing
event-driven monitoring of endpoint posture changes.

Appropriate checklists application needs to know when
security automation data they are queried, located and downloaded interested in has been
published to, updated in, or deleted from the
relevant guidance data stores. The specific a security automation
data stores queried and
the specifics store that they have been authorized to access.

These building blocks are used to enable acquisition of each query may be driven by various
instances of security automation data including:

o collected hardware and software inventory data, and

o associated asset characterization based on specific data models
that may indicate 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).

2.1.2. Endpoint Identification and Assessment Planning

This use case describes the
organizational defined functions process of each endpoint.

Checklists 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 sourced from guidance data stores maintained by an
application or OS vendor, an industry group, a regulatory authority, set of manual, automated,
or directly by the enterprise. hybrid steps that are performed for each assessment.

The retrieved guidance is cached locally to reduce the need to
retrieve the data multiple times.

Driven by building blocks of this use case are:

Endpoint Discovery: To determine the setting data provided current or historic presence of
endpoints in the checklist, a combination environment that are available for posture
assessment. Endpoints are identified in support of existing configuration data stores discovery
by using information previously obtained or using other
collection mechanisms to gather identification and
characterization data. Previously obtained data may originate
from sources such as network authentication exchanges.

Endpoint Characterization: The act of acquiring, through automated
collection methods are
used or manual input, and organizing attributes
associated with an endpoint (e.g., type, organizationally
expected function/role, hardware/software versions).

Endpoint Target Identification: Determine the candidate endpoint
target(s) against which to gather perform the appropriate posture attributes from (or pertaining
to) each endpoint. Specific posture attribute values are gathered assessment. Depending
on the assessment trigger, a single endpoint or multiple
endpoints may be targeted based on characterized endpoint
attributes. Guidance describing the defined enterprise function and software inventory of
each endpoint. The collection mechanisms used assessment to collect software
inventory posture will be performed
may contain instructions or references used again for to determine the
applicable assessment targets. In this purpose. Once case, the data Data Query
and/or Data Retrieval building blocks (see Section 2.1.1) may
be used to acquire this data.

Endpoint Component Inventory: To determine what applicable desired
states should be assessed, it is gathered, first necessary to acquire the actual state
inventory of software, hardware, and accounts associated with
the targeted endpoint(s). If the assessment of the endpoint is evaluated against
not dependent on the expected state
criteria defined these details, then this capability is not
required for use in each applicable checklist.

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

The results of checklist evaluation are provided to appropriate
operators and applications to drive additional business logic.
Specific applications for checklist evaluation results are out-of-
scope treated as a collection use case for current SACM efforts. Irrespective of specific
applications, posture
attributes. In this case, the availability, timeliness, and liveness of results
is often of general concern. Network latency and available bandwidth
often create operational constraints that require trade-offs between
these concerns and need to building blocks for
Endpoint Posture Attribute Value Collection (see Section 2.1.3)
can be considered.

Uses of checklists used.

Posture Attribute Identification: Once the endpoint targets and
their associated evaluation results may include, but
are not limited to:

o Detecting endpoint asset inventory is known, it is then necessary
to calculate what posture deviations as part of a change
management program to:

* identify missing attributes are required patches,

* unauthorized changes to hardware and software inventory, and

* unauthorized changes be
collected to configuration items.

o Determining compliance with organizational policies governing
endpoint posture.

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

o Searching perform the desired evaluation. When available,
existing posture data is queried for current suitability using the Data
Query building block (see Section 2.1.1). Such posture data is
suitable if it is complete and historic indicators of compromise.

o Detecting current and historic infection by malware and
determining enough for use in the scope of infection within an enterprise.

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

o Informing network access control decision making
evaluation. Any unsuitable posture data is identified for wired,
wireless, or VPN connections.

This usage scenario employs
collection.

If this is driven by guidance, then the following Data Query and/or Data
Retrieval building blocks defined in blocks (see Section 2.1.1 above:

Endpoint Discovery: The purpose of discovery is 2.1.1) may be used to determine
acquire this data.

At this point, the
type set of endpoint to be posture assessed.

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

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

Posture Attribute Identification: To determine what data needs to
evaluation are known, and they can be collected to support evaluation, the checklist is evaluated
against the component inventory and other endpoint metadata to
determine 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 that are needed. 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 [RFC3954] is detected).

3. a scheduled or ad hoc collection task.

The building blocks of this use case are:

Collection Guidance Acquisition: Based on If guidance is required to drive
the identified collection of posture
attributes, the application will query appropriate attributes values, this capability is
used to acquire this data from one or more security automation
data stores stores. Depending on the trigger, the specific guidance
to find acquire might be known. If not, it may be necessary to
determine the "applicable" collection guidance for each endpoint in question. to use based on the component inventory
or other assessment criteria. The Data Query and/or Data
Retrieval building blocks (see Section 2.1.1) may be used to
acquire this guidance.

Posture Attribute Value Collection: For each endpoint, the values
for The accumulation of posture
attribute values. This may be based on collection guidance
that is associated with the required posture attributes are collected.

Posture Attribute Value Query: If previously collected attributes.

Once the posture attribute values are used, collected, they are queried from the
appropriate data stores may be
persisted for the target endpoint(s).

Evaluation Guidance Acquisition: Any guidance that is needed to
support evaluation is queried and retrieved. later use or they may be immediately used for posture
evaluation.

2.1.4. Posture Attribute Evaluation: The resulting posture attribute values
from previous collection processes are evaluated using Evaluation

This use case represents the
evaluation guidance to provide a set action of analyzing collected posture results.

2.2.3. Detection of Posture Deviations

Example corporation has established secure configuration baselines
for each different type
attribute values as part of endpoint within their enterprise
including: network infrastructure, mobile, client, and server
computing platforms. These baselines define an approved list assessment. The primary focus 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 this
use case is
communicated to the support evaluation of actual endpoint based on its location in the network, state against
the expected function of the device, and other asset management data.
It is checked state selected for compliance with the baseline indicating any
deviations to the device's operators. Once the baseline has been
established, 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 is monitored for any change events
pertaining connects to the baseline on an ongoing basis. When a change occurs network/VPN,
specific netflow [RFC3954] is detected).

3. a scheduled or ad hoc evaluation task.

The building blocks of this use case are:

Collected Posture Change Detection: An operator or application has a
mechanism to posture defined in detect the baseline, updated availability of new posture information is
exchanged, allowing operators attribute
values or changes to be notified and/or automated action existing ones. The timeliness of
detection may vary from immediate to be taken.

Like on-demand. Having the Automated Checklist Verification usage scenario (see section
2.2.2), this usage scenario supports assessment based on automatable
checklists. It differs from that scenario by monitoring for specific
endpoint posture
ability to filter what changes on an ongoing basis. When are detected will allow the endpoint
detects a posture change, an alert is generated identifying
operator to focus on the
specific changes in that are relevant to their use
and will enable evaluation to occur dynamically based on
detected changes.

Posture Attribute Value Query: If previously collected posture allowing assessment of
attribute values are needed, the delta appropriate data stores are
queried to be
performed instead of a full assessment in the previous case. This
usage scenario employs retrieve them using the same Data Query building blocks as
Automated Checklist Verification block
(see section 2.2.2). It differs
slightly in how Section 2.1.1). If all posture attribute values are
provided directly for evaluation, then this capability may not
be needed.

Evaluation Guidance Acquisition: If guidance is required to drive
the evaluation of posture attributes values, this capability is
used to acquire this data from one or more security automation
data stores. Depending on the trigger, the specific guidance
to acquire might be known. If not, it uses may be necessary to
determine the following building blocks:

Endpoint Component Inventory: Additionally, changes guidance to use based on the hardware
and software component inventory are monitored, with changes causing
alerts to
or other assessment criteria. The Data Query and/or Data
Retrieval building blocks (see Section 2.1.1) may be issued. used to
acquire this guidance.

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

Posture Attribute Value Query: against their expected values as expressed in the
specified guidance. The previous state result of this comparison is output as
a set of posture
attributes are tracked, allowing changes evaluation results. Such results include
metadata required to be detected.

Posture Attribute Evaluation: After the initial assessment, provide a
partial evaluation is performed based on changes level of assurance with respect
to specific the posture attributes.

This usage scenario highlights attribute data and, therefore, evaluation
results. Examples of such metadata include provenance and or
availability data.

While the need primary focus of this use case is around enabling the
comparison of expected vs. actual state, the same building blocks can
support other analysis techniques that are applied to query a collected
posture attribute data store to
prepare (e.g., trending, historic analysis).

Completion of this process represents a compliance report for complete assessment cycle as
defined in Section 2.

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
Checklists

A vendor manufactures a specific number of specialized endpoint and devices. They
also the need develop and maintain an operating system for a change in endpoint state these devices that
enables end-user organizations to trigger Collection and Evaluation.

2.2.4. Endpoint Information Analysis configure a number of security and Reporting

Freed from the drudgery
operational settings. As part of manual endpoint compliance monitoring, one their customer support activities,
they publish a number of the security administrators at Example Corporation notices (not
using SACM standards) secure configuration guides that five endpoints have been uploading lots of
data provide
minimum security guidelines for configuring their devices.

Each guide they produce applies to a suspicious server specific model of device and
version of the operating system and provides a number of specialized
configurations depending on the Internet. The administrator
queries data stores for specific endpoint posture to see device's intended function and what
add-on hardware modules and software is licenses are installed on those endpoints and finds that they all have
a particular program installed. She then queries the appropriate
data stores
device. To enable their customers to see which other endpoints have that program installed.
All these endpoints are monitored carefully (not using SACM
standards), which allows evaluate the administrator security posture
of their devices to detect ensure that the other
endpoints all appropriate minimal security
settings are also infected.

This is just one example of the useful analysis enabled, they publish automatable configuration
checklists 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 checklists to a skilled
analyst can do using public security
automation data stores of store that customers can query to retrieve applicable
checklist(s) for their deployed specialized endpoint posture. devices.

Automatable configuration checklists 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:

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

Data Definition: To allow guidance to be defined using a standardized method.

This usage scenario highlights the need to query
or proprietary data models that will drive collection and
evaluation.

Data Publication: Providing a repository for
attributes mechanism 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 publish created guidance
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 automation data store.

Data Query: To locate and track assessments.

On a periodic basis -- either after select existing guidance that may be
reused.

Data Retrieval To retrieve specific guidance from a maximum time delta or when the security
automation data store has received a threshold level of new
vulnerability definitions -- the university uses the information for editing.

While each building block can be used in
the asset management system to put together a collection request for
all of the deployed assets manual fashion by a human
operator, it is also likely that encompasses the minimal set these capabilities will be
implemented together in some form of
artifacts necessary to evaluate all three security policies as well
as vulnerability testing. a guidance editor or generator
application.

2.2.2. Automated Checklist Verification

A financial services company operates a heterogeneous IT environment.
In the case of new critical vulnerabilities, this collection request
consists only support of the artifacts necessary their risk management program, they utilize vendor-
provided automatable security configuration checklists for those vulnerabilities each
operating system 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 application used within their IT environment.
Multiple checklists are reported to the security automation data store, a
request used from different vendors 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 ensure
adequate coverage of connectivity.
The deployed assets eventually receive the request, fulfill it, and
queue the results for the next return opportunity.

The collected artifacts eventually make it back all IT assets.

To identify what checklists are needed, they use automation to gather
an inventory of the university
where software versions utilized by all IT assets in
the level enterprise. This data gathering will involve querying existing
data stores of compliance previously collected endpoint software inventory
posture data and vulnerability exposed is calculated actively collecting data from reachable endpoints as
needed, utilizing network and asset characteristics are compared to what is in the asset systems management system for accuracy and completeness.

Like the Automated Checklist Verification usage scenario (see section
2.2.2), this usage scenario supports assessment based on checklists.
It differs from that scenario in how guidance, protocols.
Previously collected data may be provided by periodic data
collection, network connection-driven data collection, or ongoing
event-driven monitoring of endpoint posture
attribute values, and evaluation results changes.

Appropriate checklists are exchanged due to
bandwidth limitations queried, located, 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 downloaded from the following
building blocks:

Endpoint Component Inventory: It is likely that
relevant guidance data stores. The specific data stores queried and
the component
inventory will not change. If it does, this information will
need to specifics of each query may be batched driven by data including:

o collected hardware and transmitted during the next
communication window.

Collection Guidance Acquisition: Due to intermittent communication
windows software inventory data, and bandwidth constraints, changes to collection

o associated asset characterization data that may indicate the
organizationally defined functions of each endpoint.

Checklists may be sourced from guidance data stores maintained by an
application or OS vendor, an industry group, a regulatory authority,
or directly by the enterprise.

The retrieved guidance will need is cached locally to batched and transmitted during reduce the next
communication window. Guidance will need to be cached locally
retrieve the data 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 avoid gather the need for remote communications.

Posture Attribute Value Collection: The specific appropriate posture attributes from (or pertaining
to) each endpoint. Specific posture attribute values to be collected are identified remotely and batched for
collection during gathered
based on the next communication window. If a delay is
introduced for defined enterprise function and software inventory of
each endpoint. The collection mechanisms used to complete, results will need to be
batched and transmitted.

Posture Attribute Value Query: Previously collected collect software
inventory posture
attribute values will be stored used again for this purpose. Once the data
is gathered, the actual state is evaluated against the expected state
criteria defined in each applicable checklist.

A checklist can be assessed as a remote data store for use
at whole, or a specific subset of the university

Evaluation Guidance Acquisition: Due
checklist can be assessed resulting in partial data collection and
evaluation.

The results of checklist evaluation are provided to intermittent communication
windows appropriate
operators and bandwidth constraints, changes applications to drive additional business logic.
Specific applications for checklist evaluation
guidance will need to batched results are out of
scope for current SACM (Security Automation and Continuous
Monitoring) efforts. Irrespective of specific applications, the
availability, timeliness, and liveness of results are often of
general concern. Network latency and available bandwidth often
create operational constraints that require trade-offs between these
concerns and transmitted during the next
communication window. Guidance will need to be cached locally
to avoid the need for remote communications.

Posture Attribute Evaluation: Due to the caching considered.

Uses of posture
attribute values checklists and associated evaluation guidance, evaluation results may be
performed at both the university campus as well include, but
are not limited to:

o Detecting endpoint posture deviations as part of a change
management program to identify:

* missing required patches,
* unauthorized changes to hardware and software inventory, and

* unauthorized changes to configuration items.

o Determining compliance with organizational policies governing
endpoint posture.

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

o Searching for current and historic indicators of compromise.

o Detecting current and historic infection by malware and
determining the
satellite site. scope of infection within an enterprise.

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 highlights employs the need following building blocks defined in
Section 2.1.1 above:

Endpoint Discovery: The purpose of discovery is to support low-bandwidth,
intermittent, or high-latency links.

2.2.6. Identification and Retrieval determine the
type of Guidance

In preparation for performing an assessment, an operator or
application will need endpoint to be posture assessed.

Endpoint Target Identification: To identify one or more security automation
data stores that contain what potential endpoint
targets the guidance entries necessary checklist should apply to perform
data collection based on organizational
policies.

Endpoint Component Inventory: Collecting and evaluation tasks. The location of a given
guidance entry will either be known a priori or known security
automation consuming the software
and hardware inventory for the target endpoints.

Posture Attribute Identification: To determine what data stores will need needs to be queried
collected to retrieve applicable
guidance.

To query guidance it will be necessary support evaluation, the checklist is evaluated
against the component inventory and other endpoint metadata to define a
determine the set of search
criteria. This criteria will often utilize a logical combination of
publication metadata (e.g. publishing identity, create time,
modification time) and guidance data-specific criteria elements.
Once posture attribute values that are needed.

Collection Guidance Acquisition: Based on the criteria is defined, one or more identified posture
attributes, the application will query appropriate security
automation data stores will need to be queried generating a result set. Depending on
how find the results "applicable" collection
guidance 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, it may be desirable to return they are queried from the matching
guidance directly, a snippet of
appropriate data stores for the target endpoint(s).

Evaluation Guidance Acquisition: Any guidance matching 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 query, or
evaluation guidance to provide a
resolvable location 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 retrieve the data at a later time. The
guidance matching the query will be restricted based network, the authorized
level of access allowed appropriate baseline configuration is
communicated to the requester.

If the endpoint based on its location of guidance is identified in the query result set, network,
the guidance will be retrieved when needed using one or more data
retrieval requests. A variation on this approach would be to
maintain a local cache expected function of previously retrieved the device, and other asset management data. In this case,
only guidance that
It is determined to be stale by some measure will be
retrieved from the remote data store.

Alternately, guidance can be discovered by iterating over data
published checked for compliance with a given context within a security automation data
store. Specific guidance can be selected and retrieved as needed.

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

Data Query: Enables an operator or application baseline, and any deviations
are indicated to query one or more
security automation data stores the device's operators. Once the baseline has been
established, the endpoint is monitored for guidance using a set of
specified criteria.

Data Retrieval: If data locations are returned in any change events
pertaining to the query result
set, then specific guidance entries can be retrieved and
possibly cached locally.

2.2.7. Guidance Change Detection

An operator or application may need baseline on an ongoing basis. When a change occurs
to identify new, updated, or
deleted guidance posture defined in a security automation data store for which they
have been authorized the baseline, updated posture information is
exchanged, allowing operators to access. This may be achieved by querying or
iterating over guidance in a security automation data store, or
through a notification mechanism that alerts 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 based on
automatable checklists. It differs from that scenario by monitoring
for specific endpoint posture changes made to on an ongoing basis. When the
endpoint detects a
security automation data store.

Once guidance posture change, an alert is generated identifying
the specific changes have been determined, data collection and
evaluation activities may in posture, thus allowing assessment of the
delta to be triggered. performed instead of a full assessment as in the previous
case. This usage scenario employs the following same building blocks defined as
Automated Checklist Verification (see section 2.2.2). It differs
slightly in
Section 2.1.1 above:

Data Change Detection: Allows an operator or application how it uses the following building blocks:

Endpoint Component Inventory: Additionally, changes to identify
guidance the hardware
and software inventory are monitored, with changes in a security automation data store which they
have been authorized causing
alerts to access.

Data Retrieval: If data locations be issued.

Posture Attribute Value Collection: After the initial assessment,
posture attributes are provided by monitored for changes. If any of the change
detection mechanism, then specific guidance entries can
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
retrieved and possibly cached locally.

3. IANA Considerations

This memo includes no request detected.

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

4. Security Considerations specific
posture attributes.

This memo documents, for informational purposes, use cases usage scenario highlights the need to query a data store to
prepare a compliance report for
security automation. Specific security a specific endpoint and privacy considerations
will be provided also the need
for a change in related documents (e.g., requirements,
architecture, information model, data model, protocol) as appropriate 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 function described in each related document.

One consideration for security automation is administrators at Example Corporation notices (not
using SACM standards) that five endpoints have been uploading lots of
data to a malicious actor
could use suspicious server on the security automation infrastructure and related
collected Internet. The administrator
queries data stores for specific endpoint posture to gain access to an item of interest. This may
include personal data, private keys, see what
software is installed on those endpoints and configuration state finds that can be used to inform an attack against they all have
a particular program installed. She then queries the network and
endpoints, and appropriate
data stores to see which other sensitive information. It is important endpoints have that
security and privacy considerations in program installed.
All these endpoints are monitored carefully (not using SACM
standards), which allows the related documents identify
methods administrator to both identify and prevent such activity.

For consideration detect that the other
endpoints are means for protecting 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 communications as well
as following building blocks defined in
Section 2.1.1 above:

Posture Attribute Value Query: Previously collected posture
attribute values for the systems that store target endpoint(s) are queried from
the information. For communications
between appropriate data stores using a standardized method.

This usage scenario highlights the varying SACM components there should be considerations need to query a repository for protecting
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 confidentiality, data integrity and peer entity
authentication. For exchanged information, there should Arctic. The only network communications will be a means via
an intermittent, low-speed, high-latency, high-cost satellite link.
During their extended expedition, they will need to authenticate show continue
compliance with the origin security policies of the information. This is important
where tracking university, the provenance of data is needed. Also, for any
systems that store information that could be used for unauthorized or
malicious purposes, methods to identify and protect against
unauthorized usage, inappropriate usage,
government, and denial the provider of service 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 be considered.

5. Acknowledgements

Adam Montville edited early versions of this draft.

Kathleen Moriarty, 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 Stephen Hanna contributed text describing track assessments.

On a periodic basis -- either after a maximum time delta or when the
scope
security automation data store has received a threshold level of new
vulnerability definitions -- the document.

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. -08- university uses the information in
the asset management system to -09-

Fixed put together a number collection request for
all of gramatical nits throughout the draft identified by deployed assets that encompasses the SECDIR review.

Added additional text minimal set of
artifacts necessary to the evaluate all three security considerations about malicious
actors.

6.2. -07- to -08-

Reworked long sentences throughout policies as well
as vulnerability testing.

In the document by shortening or
using bulleted lists.

Re-ordered case of new critical vulnerabilities, this collection request
consists only of the artifacts necessary for those vulnerabilities,
and condensed text collection is only initiated for those assets that could
potentially have a new vulnerability.

(Optional) Asset artifacts are cached in the "Automated Checklist
Verification" sub-section a local configuration
management database (CMDB). When new vulnerabilities are reported to improve
the conceptual presentation and security automation data store, a request to clarify longer sentences.

Clarified that the "Posture Attribute Value Query" building block
represents a standardized interface live asset is
only done if the artifacts in the context CMDB are incomplete and/or not
current enough.

The collection request is queued for the next window of SACM.

Removed connectivity.
The deployed assets eventually receive the "others" sub-section within request, fulfill it, and
queue the "usage scenarios"
section.

Updated results for the "Security Considerations" section next return opportunity.

The collected artifacts eventually make it back to identify that actual
SACM security considerations will be discussed in the appropriate
related documents.

6.3. -06- to -07-

A number of edits were made to section 2 to resolve open questions in university
where the draft based on meeting level of compliance and mailing list discussions.

Section 2.1.5 was merged into section 2.1.4.

6.4. -05- to -06-

Updated the "Introduction" section vulnerability exposed is calculated
and asset characteristics are compared to better reflect what is in the use case,
building block, asset
management system for accuracy and completeness.

Like the Automated Checklist Verification usage scenario structure changes (see section
2.2.2), this usage scenario supports assessment based on checklists.
It differs from previous
revisions.

Updated most uses of the terms "content" that scenario in how guidance, collected posture
attribute values, and "content repository" evaluation results are exchanged due to
use "guidance" and "security automation data store" respectively.

In section 2.1.1, added a discussion of different data types
bandwidth limitations and
renamed "content" to "data" in availability. This usage scenario employs
the same building block names.

In blocks as Automated Checklist Verification (see
section 2.1.2, separated out 2.2.2). It differs slightly in how it uses the following
building block concepts of
"Endpoint Discovery" and "Endpoint Characterization" based on mailing
list discussions.

Addressed some open questions throughout blocks:

Endpoint Component Inventory: It is likely that the draft based on consensus
from mailing list discussions component
inventory will not change. If it does, this information will
need to be batched and transmitted during the two virtual interim meetings.

Changed many section/sub-section names to better reflect their
content.

6.5. -04- next
communication window.

Collection Guidance Acquisition: Due to -05-

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

o Moved existing use cases bandwidth constraints, changes to a subsection titled "Usage Scenarios".

o Added a new subsection titled "Use Cases" collection
guidance will need to describe the common
use cases batched and building blocks used transmitted during the next
communication window. Guidance will need to address be cached locally
to avoid the "Usage
Scenarios". The new use cases are:

* Define, Publish, Query and Retrieve Content

* Endpoint Identification and Assessment Planning

* Endpoint need for remote communications.

Posture Attribute Value Collection

* Posture Evaluation
* Mining the Database

o Added a listing of building blocks used Collection: The specific posture attribute
values to be collected are identified remotely and batched for all usage scenarios.

o Combined
collection during the following usage scenarios into "Automated Checklist
Verification": "Organizational Software Policy Compliance",
"Search next communication window. If a delay is
introduced 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 collection to complete, results
using an endpoint evaluator", will need to be
batched and "NAC/NAP connection with no transmitted.

Posture Attribute Value Query: Previously collected posture
attribute values will be stored results using in a third-party evaluator".

o Created new usage scenario "Identification and Retrieval of
Repository Content" by combining remote data store for use
at the following usage scenarios:
"Repository Interaction - A Full Assessment" university.

Evaluation Guidance Acquisition: Due to intermittent communication
windows and "Repository
Interaction - Filtered Delta Assessment"

o Renamed "Register with repository for immediate notification of
new security vulnerability content that match a selection filter" bandwidth constraints, changes to "Content Change Detection" evaluation
guidance will need to batched and generalized transmitted during the description next
communication window. Guidance will need to be neutral cached locally
to implementation approaches.

o Removed out-of-scope usage scenarios: "Remediation avoid the need for remote communications.

Posture Attribute Evaluation: Due to the caching of posture
attribute values and Mitigation" evaluation guidance, 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.

2.2.6. Identification and "Direct Human Retrieval of Ancillary Materials"

Updated acknowledgements Guidance

In preparation for performing an assessment, an operator or
application will need to recognize those identify one or more security automation
data stores that helped with editing
the use case text.

6.6. -03- to -04-

Added four new use cases regarding content repository.

6.7. -02- to -03-

Expanded the workflow description based on ML input.

Changed contain the ambiguous "assess" guidance entries necessary to better separate perform
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 evaluation tasks. The location of a given
guidance entry will either be known 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

6.8. -01- priori or known security
automation data stores will need to -02-

Changed title

removed section 4, expecting be queried to retrieve applicable
guidance.

To query guidance 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).

6.9. -00- to -01-

o Work on this revision has been focused on document content
relating primarily necessary to use define a set of asset management data search
criteria. This criteria will often utilize a logical combination of
publication metadata (e.g., publishing identity, create time,
modification time) and functions.

o Made significant updates criteria elements specific to section 3 including:

* Reworked introductory text.

* Replaced the single example with multiple use cases that focus
on guidance
data. Once the criteria are defined, one or more discrete uses of asset management security automation
data stores will need to support
hardware and software inventory, and configuration management
use cases.

* For one be queried, thus generating a result set.
Depending on how the results are used, it may be desirable to return
the matching guidance directly, a snippet of the use cases, added mapping guidance matching
the query, or a resolvable location to functional
capabilities used. If popular, this retrieve the data at a later
time. The guidance matching the query will be added restricted based on
the authorized level of access allowed to the other
use cases as well.

* Additional use cases will be added in requester.

If the next revision
capturing additional discussion from location of guidance is identified in the list.

o Made significant updates to section 4 including:

* Renamed query result set,
the section heading from "Use Cases" guidance will be retrieved when needed using one or more data
retrieval requests. A variation on this approach would be to "Functional
Capabilities" since use cases are covered in section 3. This
section now extrapolates specific functions
maintain a local cache of previously retrieved data. In this case,
only guidance that are needed to
support the use cases.

* Started work is determined to flatten the section, moving select subsections
up be stale by some measure will be
retrieved from under asset management.

* Removed the subsections for: Asset Discovery, Endpoint
Components and Asset Composition, Asset Resources, remote data store.

Alternately, guidance can be discovered by iterating over data
published with a given context within a security automation data
store. Specific guidance can be selected and Asset
Life Cycle.

* Renamed retrieved as needed.

This usage scenario employs the subsection "Asset Representation Reconciliation" following building blocks defined in
Section 2.1.1 above:

Data Query: Enables an operator or application to
"Deconfliction query one or more
security automation data stores for guidance using a set of Asset Identities".

* Expanded
specified criteria.

Data Retrieval: If data locations are returned in the subsections for: Asset Identification, Asset
Characterization, query result
set, then specific guidance entries can be retrieved and Deconfliction of Asset Identities.

* Added a new subsection for Asset Targeting.

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

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

o Transitioned from individual I/D
possibly cached locally.

2.2.7. Guidance Change Detection

An operator or application may need to WG I/D based on WG consensus
call.

o Fixed identify new, updated, or
deleted guidance in a number of spelling errors. Thank you Erik!

o Added keywords to the front matter.

o Removed the terminology section from the draft. Terms security automation data store for which they
have been
moved to: draft-dbh-sacm-terminology-00

o Removed requirements authorized to access. This may be moved into achieved by querying or
iterating over guidance in a new I/D.

o Extracted the functionality from the examples and security automation data store, or
through a notification mechanism that generates alerts when changes
are 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 a security automation data store.

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

This usage scenario employs the "security" distinction
is important.

* Added new sections, partially integrated existing content.

* Additional text is needed following building blocks defined in all of the sub-sections.

o Changed "Security Change Management" to "Endpoint Posture
Section 2.1.1 above:

Data Change
Management". Added new skeletal outline sections for future
updates.

6.11. waltermire -04- Detection: Allows an operator or application to -05-

o Are we including user activities and behavior identify
guidance changes in the scope of this
work? That seems a security automation data store for which
they have been authorized to access.

Data Retrieval: If data locations are provided by the change
detection mechanism, then specific guidance entries can be layer 8 stuff,
retrieved and possibly cached locally.

3. Security Considerations

This memo documents, for informational purposes, use cases for
security automation. Specific security and privacy considerations
will be provided in related documents (e.g., requirements,
architecture, information model, data model, protocol) as appropriate
to an IDS/IPS
application, not Internet stuff.

o Removed the references to what the WG will do because this belongs function described in the charter, not the (potentially long-lived) use cases each related document. I removed mention of charter objectives because the
charter may go through multiple iterations over time; there is a
website

One consideration for hosting the charter; this document security automation is not the correct
place for that discussion.

o Moved a malicious actor
could use the discussion of NIST specifications security automation infrastructure and related
collected data to the
acknowledgements section.

o Removed the portion gain access to an item of the introduction interest. This may
include personal data, private keys, software and configuration state
that describes can be used to inform an attack against the
chapters; we have a table of concepts, network and the existing text
seemed redundant.

o Removed marketing claims, to focus on technical concepts
endpoints, and
technical analysis, other sensitive information. It is important that would enable subsequent engineering
effort.

o Removed (commented out in XML) UC2 and UC3,
security and eliminated some
text that referred privacy considerations in the related documents indicate
methods to these use cases.

o Modified IANA both identify and Security Consideration sections.

o Moved Terms to prevent such activity.

For consideration are means for protecting the front, so we can use them in communications as well
as the subsequent
text.

o Removed systems that store the "Key Concepts" section, since information. For communications
between the concepts of ORM and
IRM were not otherwise mentioned in varying SACM components, there should be considerations
for protecting the document. This would seem
more appropriate confidentiality, data integrity, and peer entity
authentication. For exchanged information, there should be a means
to authenticate the arch doc rather than use cases.

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

o Modified text to describe data is needed. Also, for any
systems that this was specific to enterprises,
and store information that it was expected could be used for unauthorized or
malicious purposes, methods to overlap with service provider use
cases, and described the context of this scoped work within a
larger context of policy enforcement, identify and verification.

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

o Added text service need
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. be considered.

4. Informative References

[RFC3444] Pras, A. and J. Schoenwaelder, "On the Difference between
Information Models and Data Models", RFC 3444, DOI
10.17487/RFC3444, January
2003. 2003,
<http://www.rfc-editor.org/info/rfc3444>.

[RFC3954] Claise, B., Ed., "Cisco Systems NetFlow Services Export
Version 9", RFC 3954, DOI 10.17487/RFC3954, October 2004,
<http://www.rfc-editor.org/info/rfc3954>.

Acknowledgements

Adam Montville edited early versions of this document.

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

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

Authors' Addresses

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

Email: david.waltermire@nist.gov

David Harrington
Effective Software
50 Harding Rd
Portsmouth, NH New Hampshire 03801
USA
United States

Email: ietfdbh@comcast.net