Security Automation and Continuous Monitoring WG D. Waltermire
Internet-Draft NIST
Intended status: Informational D. Harrington
Expires: May 24, 2014 Effective Software
November 20, 2013
Endpoint Security Posture Assessment - Enterprise Use Cases
draft-ietf-sacm-use-cases-05
Abstract
This memo documents a sampling of use cases for securely aggregating
configuration and operational data and evaluating that data to
determine an organization's security posture. From these operational
use cases, we can derive common functional capabilities and
requirements to guide development of vendor-neutral, interoperable
standards for aggregating and evaluating data relevant to security
posture.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
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Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
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This Internet-Draft will expire on May 24, 2014.
Copyright Notice
Copyright (c) 2013 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
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include Simplified BSD License text as described in Section 4.e of
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described in the Simplified BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Endpoint Posture Assessment . . . . . . . . . . . . . . . . . 4
2.1. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1.1. Define, Publish, Query and Retrieve Content . . . . . 5
2.1.2. Endpoint Identification and Assessment Planning . . . 7
2.1.3. Endpoint Posture Attribute Value Collection . . . . . 8
2.1.4. Posture Evaluation . . . . . . . . . . . . . . . . . 8
2.1.5. Mining the Database . . . . . . . . . . . . . . . . . 9
2.2. Usage Scenarios . . . . . . . . . . . . . . . . . . . . . 10
2.2.1. Definition and Publication of Automatable
Configuration Guides . . . . . . . . . . . . . . . . 10
2.2.2. Automated Checklist Verification . . . . . . . . . . 11
2.2.3. Detection of Posture Deviations . . . . . . . . . . . 13
2.2.4. Endpoint Information Analysis and Reporting . . . . . 14
2.2.5. Asynchronous Compliance/Vulnerability Assessment at
Ice Station Zebra . . . . . . . . . . . . . . . . . . 15
2.2.6. Identification and Retrieval of Repository Content . 17
2.2.7. Content Change Detection . . . . . . . . . . . . . . 18
2.2.8. Others... . . . . . . . . . . . . . . . . . . . . . . 18
3. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 18
4. Security Considerations . . . . . . . . . . . . . . . . . . . 18
5. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 18
6. Change Log . . . . . . . . . . . . . . . . . . . . . . . . . 19
6.1. -04- to -05- . . . . . . . . . . . . . . . . . . . . . . 19
6.2. -03- to -04- . . . . . . . . . . . . . . . . . . . . . . 20
6.3. -02- to -03- . . . . . . . . . . . . . . . . . . . . . . 20
6.4. -01- to -02- . . . . . . . . . . . . . . . . . . . . . . 21
6.5. -00- to -01- . . . . . . . . . . . . . . . . . . . . . . 21
6.6. draft-waltermire-sacm-use-cases-05 to draft-ietf-sacm-
use-cases-00 . . . . . . . . . . . . . . . . . . . . . . 22
6.7. waltermire -04- to -05- . . . . . . . . . . . . . . . . . 23
7. References . . . . . . . . . . . . . . . . . . . . . . . . . 24
7.1. Normative References . . . . . . . . . . . . . . . . . . 24
7.2. Informative References . . . . . . . . . . . . . . . . . 24
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 24
1. Introduction
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Our goal with this document is to improve our agreement on which
problems we're trying to solve. We need to start with short, simple
problem statements and discuss those by email and in person. Once we
agree on which problems we're trying to solve, we can move on to
propose various solutions and decide which ones to use.
This document describes example use cases for endpoint posture
assessment for enterprises. It provides a sampling of use cases for
securely aggregating configuration and operational data and
evaluating that data to determine the security posture of individual
endpoints, and, in the aggregate, the security posture of an
enterprise.
These use cases cross many IT security information domains. From
these operational use cases, we can derive common concepts, common
information expressions, functional capabilities and requirements to
guide development of vendor-neutral, interoperable standards for
aggregating and evaluating data relevant to security posture.
Using this standard data, tools can analyze the state of endpoints,
user activities and behaviour, and evaluate the security posture of
an organization. Common expression of information should enable
interoperability between tools (whether customized, commercial, or
freely available), and the ability to automate portions of security
processes to gain efficiency, react to new threats in a timely
manner, and free up security personnel to work on more advanced
problems.
The goal is to enable organizations to make informed decisions that
support organizational objectives, to enforce policies for hardening
systems, to prevent network misuse, to quantify business risk, and to
collaborate with partners to identify and mitigate threats.
It is expected that use cases for enterprises and for service
providers will largely overlap, but there are additional
complications for service providers, especially in handling
information that crosses administrative domains.
The output of endpoint posture assessment is expected to feed into
additional processes, such as policy-based enforcement of acceptable
state, verification and monitoring of security controls, and
compliance to regulatory requirements.
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2. Endpoint Posture Assessment
Endpoint posture assessment involves orchestrating and performing
data collection and evaluating the posture of a given endpoint.
Typically, endpoint posture information is gathered and then
published to appropriate data repositories to make collected
information available for further analysis supporting organizational
security processes.
Endpoint posture assessment typically includes:
o Collecting the attributes of a given endpoint;
o Making the attributes available for evaluation and action; and
o Verifying that the endpoint's posture is in compliance with
enterprise standards and policy.
As part of these activities it is often necessary to identify and
acquire any supporting content that is needed to drive data
collection and analysis.
The following is a typical workflow scenario for assessing endpoint
posture:
1. Some type of trigger initiates the workflow. For example, an
operator or an application might trigger the process with a
request, or the endpoint might trigger the process using an
event-driven notification.
QUESTION: Since this is about security automation, can we drop
the User and just use Application? Is there a better term to
use here? Once the policy is selected, the rest seems like
something we definitely would want to automate, so I dropped
the User part.
2. An operator/application selects one or more target endpoints to
be assessed.
3. A operator/application selects which policies are applicable to
the targets.
4. For each target:
A. The application determines which (sets of) posture attributes
need to be collected for evaluation.
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QUESTION: It was suggested that mentioning several common
acquisition methods, such as local API, WMI, Puppet, DCOM,
SNMP, CMDB query, and NEA, without forcing any specific
method would be good. I have concerns this could devolve
into a "what about my favorite?" contest. OTOH, the
charter does specifically call for use of existing
standards where applicable, so the use cases document
might be a good neutral location for such information, and
might force us to consider what types of external
interfaces we might need to support when we consider the
requirements. It appears that the generic workflow
sequence would be a good place to mention such common
acquisition methods.
B. The application might retrieve previously collected
information from a cache or data store, such as a data store
populated by an asset management system.
C. The application might establish communication with the
target, mutually authenticate identities and authorizations,
and collect posture attributes from the target.
D. The application might establish communication with one or
more intermediary/agents, mutually authenticate their
identities and determine authorizations, and collect posture
attributes about the target from the intermediary/agents.
Such agents might be local or external.
E. The application communicates target identity and (sets of)
collected attributes to an evaluator, possibly an external
process or external system.
F. The evaluator compares the collected posture attributes with
expected values as expressed in policies.
QUESTION: Evaluator generates a report or log or
notification of some type?
2.1. Use Cases
The following subsections detail specific use cases for assessment
planning, data collection, analysis, and related operations
pertaining to the publication and use of supporting content.
2.1.1. Define, Publish, Query and Retrieve Content
This use case describes the need for content to be defined and
published to a data store, as well as queried and retrieved from the
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data store for the explicit use of posture collection and evaluation.
It is expected that multiple information models will be supported to
address the information needed to support the exchange of endpoint
metadata, and the collection and evaluation of endpoint posture
attribute values. It is likely that multiple data models will be
used to express these information models requiring specialized or
extensible content data stores.
The building blocks of this use case are:
Content Definition: Defining the content to drive collection and
evaluation. This may include evaluating existing stores of
content to find content to reuse and the creation of new
content. Developed content will be based on available data
models which may be standardized or proprietary.
Content Publication: The capability to publish content to a content
data store for further use. Published content may be made
publicly available or may be based on an authorization decision
using authenticated credentials. As a result, the visibility
of content to an operator or application may be public,
enterprise-scoped, private, or controlled within any other
scope.
Content Query: An operator or application should be able to query a
content data store using a set of specified criteria. The
result of the query will be a listing matching the query. The
query result listing may contain publication metadata (e.g.,
create date, modified date, publisher, etc.) and/or the full
content, a summary, snippet, or the location to retrieve the
content.
Content Retrieval: The act of acquiring one or more specific content
entries. This capability is useful if the location of the
content is known a priori, perhaps as the result of request
based on decisions made using information from a previous
query.
Content Change Detection: An operator or application needs to
identify content of interest that is new, updated, or deleted
in a content data store which they have been authorized to
access.
These building blocks are used to enable acquisition of various
instances of content based on specific data models that are used to
drive assessment planning (see section 2.1.2), posture attribute
value collection (see section 2.1.3), and posture evaluation (see
section 2.1.4).
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2.1.2. Endpoint Identification and Assessment Planning
This use case describes the process of discovering endpoints,
understanding their composition, identifying the desired state to
assess against, and calculating what posture attributes to collect to
enable evaluation. This process may be a set of manual, automated,
or hybrid steps that are performed for each assessment.
The building blocks of this use case are:
Endpoint Discovery: The purpose of discovery is to determine the
type of endpoint to be posture assessed.
QUESTION: Is it just the type? Or is it to identify what
endpoint instances to target for assessment using metadata such
as the endpoint's organizationally expected type (e.g.,
expected function/role, etc.)
Identify Endpoint Targets Determine the candidate endpoint target(s)
to perform the assessment against. Depending on the assessment
trigger, a single endpoint may be targeted or multiple
endpoints may be targeted based on discovered endpoint
metadata. This may be driven by content that describes the
applicable targets for assessment. In this case the Content
Query and/or Content Retrieval building blocks (see section
2.1.1) may be used to acquire this content.
Endpoint Component Inventory: To determine what applicable desired
states should be assessed, it is first necessary to acquire the
inventory of software, hardware, and accounts associated with
the targeted endpoint(s). If the assessment of the endpoint is
not dependant on the component inventory, then this capability
is not required for use in performing the assessment. This
process can be treated as a collection use case for specific
posture attributes. In this case the building blocks for
Endpoint Posture Attribute Value Collection (see section 2.1.3)
can be used.
Posture Attribute Identification: Once the endpoint targets and
component inventory is known, it is then necessary to calculate
what posture attributes are required to be collected to perform
the evaluation. If this is driven by content, then the Content
Query and/or Content Retrieval building blocks (see section
2.1.1) may be used to acquire this content.
QUESTION: Are we missing a building block that determines what
previously collected data, if any, is suitable for evaluation and
what data needs to be actually collected?
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At this point the set of posture attribute values to use for
evaluation are known and they can be collected if necessary (see
section 2.1.3).
2.1.3. Endpoint Posture Attribute Value Collection
This use case describes the process of collecting a set of posture
attribute values related to one or more endpoints. This use case can
be initiated by a variety of triggers including:
1. A posture change or significant event on the endpoint.
2. A network event (e.g., endpoint connects to a network/VPN,
specific netflow is detected).
3. Due to a scheduled or ad hoc collection task.
The building blocks of this use case are:
Collection Content Acquisition: If content is required to drive the
collection of posture attributes values, this capability is
used to acquire this content from one or more content data
stores. Depending on the trigger, the specific content to
acquire might be known. If not, it may be necessary to
determine the content to use based on the component inventory
or other assessment criteria. The Content Query and/or Content
Retrieval building blocks (see section 2.1.1) may be used to
acquire this content.
Posture Attribute Value Collection: The accumulation of posture
attribute values. This may be based on collection content that
is associated with the posture attributes.
Once the posture attribute values are collected, they may be
persisted for later use or they may be immediately used for posture
evaluation.
2.1.4. Posture Evaluation
This use case describes the process of evaluating collected posture
attribute values representing actual endpoint state against the
expected state selected for the assessment. This use case can be
initiated by a variety of triggers including:
1. A posture change or significant event on the endpoint.
2. A network event (e.g., endpoint connects to a network/VPN,
specific netflow is detected).
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3. Due to a scheduled or ad hoc evaluation task.
The building blocks of this use case are:
Posture Attribute Value Query: If previously collected posture
attribute values are needed, the appropriate data stores are
queried to retrieve them. If all posture attribute values are
provided directly for evaluation, then this capability may not
be needed.
Evaluation Content Acquisition: If content is required to drive the
evaluation of posture attributes values, this capability is
used to acquire this content from one or more content data
stores. Depending on the trigger, the specific content to
acquire might be known. If not, it may be necessary to
determine the content to use based on the component inventory
or other assessment criteria. The Content Query and/or Content
Retrieval building blocks (see section 2.1.1) may be used to
acquire this content.
Posture Attribute Evaluation: The comparison of posture attribute
values against their expected results as expressed in the
specified content. The result of this comparison is output as
a set of posture evaluation results.
Completion of this process represents a complete assessment cycle as
defined in section Section 2.
2.1.5. Mining the Database
This use case describes the need to analyze previously collected
posture attribute values from one or more endpoints. This is an
alternate use case to Posture Evaluation (see section 2.1.4 that uses
collected posture attributes values for analysis processes that may
do more than evaluating expected vs. actual state(s).
The building blocks of this use case are:
Query: Query a data store for specific posture attribute values.
Change Detection: An operator should have a mechanism to detect the
availability of new or changes to existing posture attribute
values. The timeliness of detection may vary from immediate to
on demand. Having the ability to filter what changes are
detected will allow the operator to focus on the changes that
are relevant to their use.
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QUESTION: Does this warrant a separate use case, or should this be
incorporated into the previous use case?
2.2. Usage Scenarios
In this section, we describe a number of usage scenarios that utilize
aspects of endpoint posture assessment. These are examples of common
problems that can be solved with the building blocks defined above.
2.2.1. Definition and Publication of Automatable Configuration Guides
A vendor manufactures a number of specialized endpoint devices. They
also develop and maintain an operating system for these devices that
enables end-user organizations to configure a number of security and
operational settings. As part of their customer support activities,
they publish a number of secure configuration guides that provide
minimum security guidelines for configuring their devices.
Each guide they produce applies to a specific model of device and
version of the operating system and provides a number of specialized
configurations depending on the devices intended function and what
add-on hardware modules and software licenses are installed on the
device. To enable their customers to evaluate the security posture
of their devices to ensure that all appropriate minimal security
settings are enabled, they publish an automatable configuration
checklist using a popular data format that defines what settings to
collect using a network management protocol and appropriate values
for each setting. They publish these checklist to a public content
repository that customers can query to retrieve applicable checklist
for their deployed specialized endpoint devices.
Automatable configuration checklist could also come from sources
other than a device vendor, such as industry groups or regulatory
authorities, or enterprises could develop their own checklists.
This usage scenario employs the following building blocks defined in
Section 2.1.1 above:
Content Definition: To allow content to be defined using
standardized or proprietary data models that will drive
Collection and Evaluation.
Content Publication: Providing a mechanism to publish created
content to a content data store.
Content Query: To locate and select existing content that may be
reused.
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Content Retrieval To retrieve specific content from a content data
store for editing.
While each building block can be used in a manual fashion by a human
operator, it is also likely that these capabilities will be
implemented together in some form of a content editor or generator
application.
2.2.2. Automated Checklist Verification
A financial services company operates a heterogeneous IT environment.
In support of their risk management program, they utilize vendor
provided automatable security configuration checklists for each
operating system and application used within their IT environment.
Multiple checklists are used from different vendors to insure
adequate coverage of all IT assets.
To identify what checklists are needed, they use automation to gather
an inventory of the software versions utilized by all IT assets in
the enterprise. This data gathering will involve querying existing
data stores of previously collected endpoint software inventory
posture data and actively collecting data from reachable endpoints as
needed utilizing network and systems management protocols.
Previously collected data may be provided by periodic data
collection, network connection-driven data collection, or ongoing
event-driven monitoring of endpoint posture changes.
Using the gathered hardware and software inventory data and
associated asset management data that may indicate the organizational
defined functions of each endpoint, checklist content is queried,
located and downloaded from the appropriate vendor and 3rd-party
content repositories for the appropriate checklists. This content is
cached locally to reduce the need to download the checklist content
multiple times.
Driven by the setting data provided in the checklist, a combination
of existing configuration data stores and data collection methods are
used to gather the appropriate posture attributes from each endpoint.
Specific data is gathered based on the defined enterprise function
and software inventory of each endpoint. The data collection paths
used to collect software inventory posture will be used again for
this purpose. Once the data is gathered, the actual state is
evaluated against the expected state criteria in each applicable
checklist. The results of this evaluation are provided to
appropriate operators and applications to drive additional business
logic.
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Checklists could include searching for indicators of compromise on
the endpoint (e.g., file hashes); identifying malicious activity
(e.g. command and control traffic); detecting presence of
unauthorized/malicious software, hardware, and configuration items;
and other indicators.
A checklist can be assessed as a whole, or a specific subset of the
checklist can be assessed resulting in partial data collection and
evaluation.
Checklists could also come from sources other than the application or
OS vendor, such as industry groups or regulatory authorities, or
enterprises could develop their own checklists.
While specific applications for checklists results are out-of-scope
for current SACM efforts, how the data is used may illuminate
specific latency and bandwidth requirements. For this purpose use of
checklist assessment results may include, but are not limited to:
o Detecting endpoint posture deviations as part of a change
management program to include changes to hardware and software
inventory including patches, changes to configuration items, and
other posture aspects.
o Determining compliance with organizational policies governing
endpoint posture.
o Searching for current and historic signs of infection by malware
and determining the scope of infection within an enterprise.
o Informing configuration management, patch management, and
vulnerability mitigation and remediation decisions.
o Detecting performance, attack and vulnerable conditions that
warrant additional network diagnostics, monitoring, and analysis.
o Informing network access control decision making for wired,
wireless, or VPN connections.
This usage scenario employs the following building blocks defined in
Section 2.1.1 above:
Endpoint Discovery: The purpose of discovery is to determine the
type of endpoint to be posture assessed.
Identify Endpoint Targets: To identify what potential endpoint
targets the checklist should apply to based on organizational
policies.
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Endpoint Component Inventory: Collecting and consuming the software
and hardware inventory for the target endpoints.
Posture Attribute Identification: To determine what data needs to be
collected to support evaluation, the checklist is evaluated
against the component inventory and other endpoint metadata to
determine the set of posture attribute values that are needed.
Collection Content Acquisition: Based on the identified posture
attributes, the application will query appropriate content data
stores to find the "applicable" data collection content for
each endpoint in question.
Posture Attribute Value Collection: For each endpoint, the values
for the required posture attributes are collected.
Posture Attribute Value Query: If previously collected posture
attribute values are used, they are queried from the
appropriate data stores for the target endpoint(s).
Evaluation Content Acquisition: Any content that is needed to
support evaluation is queried and retrieved.
Posture Attribute Evaluation: The resulting posture attribute values
from previous Collection processes are evaluated using the
evaluation content to provide a set of posture results.
2.2.3. Detection of Posture Deviations
Example corporation has established secure configuration baselines
for each different type of endpoint within their enterprise
including: network infrastructure, mobile, client, and server
computing platforms. These baselines define an approved list of
hardware, software (i.e., operating system, applications, and
patches), and associated required configurations. When an endpoint
connects to the network, the appropriate baseline configuration is
communicated to the endpoint based on its location in the network,
the expected function of the device, and other asset management data.
It is checked for compliance with the baseline indicating any
deviations to the device's operators. Once the baseline has been
established, the endpoint is monitored for any change events
pertaining to the baseline on an ongoing basis. When a change occurs
to posture defined in the baseline, updated posture information is
exchanged allowing operators to be notified and/or automated action
to be taken.
Like the Automated Checklist Verification usage scenario (see section
2.2.2), this usage scenario supports assessment of checklists. It
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differs from that scenario by monitoring for specific endpoint
posture changes on an ongoing basis. When the endpoint detects a
posture change, an alert is generated identifying the specific
changes in posture allowing a delta assessment to be performed
instead of a full assessment in the previous case. This usage
scenario employs the same building blocks as Automated Checklist
Verification (see section 2.2.2). It differs slightly in how it uses
the following building blocks:
Endpoint Component Inventory: Additionally, changes to the hardware
and software inventory are monitored, with changes causing
alerts to be issued.
Posture Attribute Value Collection: After the initial assessment,
posture attributes are monitored for changes. If any of the
selected posture attribute values change, an alert is issued.
Posture Attribute Value Query: The previous state of posture
attributes are tracked, allowing changes to be detected.
Posture Attribute Evaluation: After the initial assessment, a
partial evaluation is performed based on changes to specific
posture attributes.
This usage scenario highlights the need to query a data store to
prepare a compliance report for a specific endpoint and also the need
for a change in endpoint state to trigger Collection and Evaluation.
2.2.4. Endpoint Information Analysis and Reporting
Freed from the drudgery of manual endpoint compliance monitoring, one
of the security administrators at Example Corporation notices (not
using SACM standards) that five endpoints have been uploading lots of
data to a suspicious server on the Internet. The administrator
queries data stores for specific endpoint posture to see what
software is installed on those endpoints and finds that they all have
a particular program installed. She then queries the appropriate
data stores to see which other endpoints have that program installed.
All these endpoints are monitored carefully (not using SACM
standards), which allows the administrator to detect that the other
endpoints are also infected.
This is just one example of the useful analysis that a skilled
analyst can do using data stores of endpoint posture.
This usage scenario employs the following building blocks defined in
Section 2.1.1 above:
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Posture Attribute Value Query: Previously collected posture
attribute values are queried from the appropriate data stores
for the target endpoint(s).
QUESTION: Should we include other building blocks here?
This usage scenario highlights the need to query a repository for
attributes to see which attributes certain endpoints have in common.
2.2.5. Asynchronous Compliance/Vulnerability Assessment at Ice Station
Zebra
A university team receives a grant to do research at a government
facility in the arctic. The only network communications will be via
an intermittent low-speed high-latency high-cost satellite link.
During their extended expedition they will need to show continue
compliance with the security policies of the university, the
government, and the provider of the satellite network as well as keep
current on vulnerability testing. Interactive assessments are
therefore not reliable, and since the researchers have very limited
funding they need to minimize how much money they spend on network
data.
Prior to departure they register all equipment with an asset
management system owned by the university, which will also initiate
and track assessments.
On a periodic basis -- either after a maximum time delta or when the
content repository has received a threshold level of new
vulnerability definitions -- the university uses the information in
the asset management system to put together a collection request for
all of the deployed assets that encompasses the minimal set of
artifacts necessary to evaluate all three security policies as well
as vulnerability testing.
In the case of new critical vulnerabilities this collection request
consists only of the artifacts necessary for those vulnerabilities
and collection is only initiated for those assets that could
potentially have a new vulnerability.
[Optional] Asset artifacts are cached in a local CMDB. When new
vulnerabilities are reported to the content repository, a request to
the live asset is only done if the artifacts in the CMDB are
incomplete and/or not current enough.
The collection request is queued for the next window of connectivity.
The deployed assets eventually receive the request, fulfill it, and
queue the results for the next return opportunity.
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The collected artifacts eventually make it back to the university
where the level of compliance and vulnerability expose is calculated
and asset characteristics are compared to what is in the asset
management system for accuracy and completeness.
Like the Automated Checklist Verification usage scenario (see section
2.2.2), this usage scenario supports assessment of checklists. It
differs from that scenario in how content, collected posture values,
and evaluation results are exchanged due to bandwidth limitations and
availability. This usage scenario employs the same building blocks
as Automated Checklist Verification (see section 2.2.2). It differs
slightly in how it uses the following building blocks:
Endpoint Component Inventory: It is likely that the component
inventory will not change. If it does, this information will
need to be batched and transmitted during the next
communication window.
Collection Content Acquisition: Due to intermittent communication
windows and bandwidth constraints, changes to collection
content will need to batched and transmitted during the next
communication window. Content will need to be cached locally
to avoid the need for remote communications.
Posture Attribute Value Collection: The specific posture attribute
values to be collected are identified remotely and batched for
collection during the next communication window. If a delay is
introduced for collection to complete, results will need to be
batched and transmitted in the same way.
Posture Attribute Value Query: Previously collected posture
attribute values will be stored in a remote data store for use
at the university
Evaluation Content Acquisition: Due to intermittent communication
windows and bandwidth constraints, changes to evaluation
content will need to batched and transmitted during the next
communication window. Content will need to be cached locally
to avoid the need for remote communications.
Posture Attribute Evaluation: Due to the caching of posture
attribute values and evaluation content, evaluation may be
performed at both the university campus as well as the
satellite site.
This usage scenario highlights the need to support low-bandwidth,
intermittent, or high-latency links.
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2.2.6. Identification and Retrieval of Repository Content
In preparation for performing an assessment, an operator or
application will need to identify one or more content data stores
that contain the content entries necessary to perform data collection
and evaluation tasks. The location of a given content entry will
either be known a priori or known content repositories will need to
be queried to retrieve applicable content.
To query content it will be necessary to define a set of search
criteria. This criteria will often utilize a logical combination of
publication metadata (e.g. publishing identity, create time,
modification time) and content-specific criteria elements. Once the
criteria is defined, one or more content data stores will need to be
queried generating a result set. Depending on how the results are
used, it may be desirable to return the matching content directly, a
snippet of the content matching the query, or a resolvable location
to retrieve the content at a later time. The content matching the
query will be restricted based the authorized level of access allowed
to the requester.
If the location of content is identified in the query result set, the
content will be retrieved when needed using one or more content
retrieval requests. A variation on this approach would be to
maintain a local cache of previously retrieved content. In this
case, only content that is determined to be stale by some measure
will be retrieved from the remote content store.
Alternately, content can be discovered by iterating over content
published with a given context within a content repository. Specific
content can be selected and retrieved as needed.
This usage scenario employs the following building blocks defined in
Section 2.1.1 above:
Content Query: Enables an operator or application to query one or
more content data stores for content using a set of specified
criteria.
Content Retrieval: If content locations are returned in the query
result set, then specific content entries can be retrieved and
possibly cached locally.
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2.2.7. Content Change Detection
An operator or application may need to identify new, updated, or
deleted content in a content repository for which they have been
authorized to access. This may be achieved by querying or iterating
over content in a content repository, or through a notification
mechanism that alerts to changes made to a content repository.
Once content changes have been determined, data collection and
evaluation activities may be triggered.
This usage scenario employs the following building blocks defined in
Section 2.1.1 above:
Content Change Detection: Allows an operator or application to
identify content changes in a content data store which they
have been authorized to access.
Content Retrieval: If content locations are provided by the change
detection mechanism, then specific content entries can be
retrieved and possibly cached locally.
2.2.8. Others...
Additional use cases will be identified as we work through other
domains.
3. IANA Considerations
This memo includes no request to IANA.
4. Security Considerations
This memo documents, for Informational purposes, use cases for
security automation. While it is about security, it does not affect
security.
5. Acknowledgements
The National Institute of Standards and Technology (NIST) and/or the
MITRE Corporation have developed specifications under the general
term "Security Automation" including languages, protocols,
enumerations, and metrics.
Adam Montville edited early versions of this draft.
Kathleen Moriarty, and Stephen Hanna contributed text describing the
scope of the document.
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Gunnar Engelbach, Steve Hanna, Chris Inacio, Kent Landfield, Lisa
Lorenzin, Adam Montville, Kathleen Moriarty, Nancy Cam-Winget, and
Aron Woland provided use cases text for various revisions of this
draft.
6. Change Log
6.1. -04- to -05-
Changes in this revision are focused on section 2 and the subsequent
subsections:
o Moved existing use cases to a subsection titled "Usage Scenarios".
o Added a new subsection titled "Use Cases" to describe the common
use cases and building blocks used to address the "Usage
Scenarios". The new use cases are:
* Define, Publish, Query and Retrieve Content
* Endpoint Identification and Assessment Planning
* Endpoint Posture Attribute Value Collection
* Posture Evaluation
* Mining the Database
o Added a listing of building blocks used for all usage scenarios.
o Combined the following usage scenarios into "Automated Checklist
Verification": "Organizational Software Policy Compliance",
"Search for Signs of Infection", "Vulnerable Endpoint
Identification", "Compromised Endpoint Identification",
"Suspicious Endpoint Behavior", "Traditional endpoint assessment
with stored results", "NAC/NAP connection with no stored results
using an endpoint evaluator", and "NAC/NAP connection with no
stored results using a third-party evaluator".
o Created new usage scenario "Identification and Retrieval of
Repository Content" by combining the following usage scenarios:
"Repository Interaction - A Full Assessment" and "Repository
Interaction - Filtered Delta Assessment"
o Renamed "Register with repository for immediate notification of
new security vulnerability content that match a selection filter"
to "Content Change Detection" and generalized the description to
be neutral to implementation approaches.
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o Removed out-of-scope usage scenarios: "Remediation and Mitigation"
and "Direct Human Retrieval of Ancillary Materials"
Updated acknowledgements to recognize those that helped with editing
the use case text.
6.2. -03- to -04-
Added four new use cases regarding content repository.
6.3. -02- to -03-
Expanded the workflow description based on ML input.
Changed the ambiguous "assess" to better separate data collection
from evaluation.
Added use case for Search for Signs of Infection.
Added use case for Remediation and Mitigation.
Added use case for Endpoint Information Analysis and Reporting.
Added use case for Asynchronous Compliance/Vulnerability Assessment
at Ice Station Zebra.
Added use case for Traditional endpoint assessment with stored
results.
Added use case for NAC/NAP connection with no stored results using an
endpoint evaluator.
Added use case for NAC/NAP connection with no stored results using a
third-party evaluator.
Added use case for Compromised Endpoint Identification.
Added use case for Suspicious Endpoint Behavior.
Added use case for Vulnerable Endpoint Identification.
Updated Acknowledgements
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6.4. -01- to -02-
Changed title
removed section 4, expecting it will be moved into the requirements
document.
removed the list of proposed capabilities from section 3.1
Added empty sections for Search for Signs of Infection, Remediation
and Mitigation, and Endpoint Information Analysis and Reporting.
Removed Requirements Language section and rfc2119 reference.
Removed unused references (which ended up being all references).
6.5. -00- to -01-
o Work on this revision has been focused on document content
relating primarily to use of asset management data and functions.
o Made significant updates to section 3 including:
* Reworked introductory text.
* Replaced the single example with multiple use cases that focus
on more discrete uses of asset management data to support
hardware and software inventory, and configuration management
use cases.
* For one of the use cases, added mapping to functional
capabilities used. If popular, this will be added to the other
use cases as well.
* Additional use cases will be added in the next revision
capturing additional discussion from the list.
o Made significant updates to section 4 including:
* Renamed the section heading from "Use Cases" to "Functional
Capabilities" since use cases are covered in section 3. This
section now extrapolates specific functions that are needed to
support the use cases.
* Started work to flatten the section, moving select subsections
up from under asset management.
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* Removed the subsections for: Asset Discovery, Endpoint
Components and Asset Composition, Asset Resources, and Asset
Life Cycle.
* Renamed the subsection "Asset Representation Reconciliation" to
"Deconfliction of Asset Identities".
* Expanded the subsections for: Asset Identification, Asset
Characterization, and Deconfliction of Asset Identities.
* Added a new subsection for Asset Targeting.
* Moved remaining sections to "Other Unedited Content" for future
updating.
6.6. draft-waltermire-sacm-use-cases-05 to draft-ietf-sacm-use-cases-00
o Transitioned from individual I/D to WG I/D based on WG consensus
call.
o Fixed a number of spelling errors. Thank you Erik!
o Added keywords to the front matter.
o Removed the terminology section from the draft. Terms have been
moved to: draft-dbh-sacm-terminology-00
o Removed requirements to be moved into a new I/D.
o Extracted the functionality from the examples and made the
examples less prominent.
o Renamed "Functional Capabilities and Requirements" section to "Use
Cases".
* Reorganized the "Asset Management" sub-section. Added new text
throughout.
+ Renamed a few sub-section headings.
+ Added text to the "Asset Characterization" sub-section.
o Renamed "Security Configuration Management" to "Endpoint
Configuration Management". Not sure if the "security" distinction
is important.
* Added new sections, partially integrated existing content.
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* Additional text is needed in all of the sub-sections.
o Changed "Security Change Management" to "Endpoint Posture Change
Management". Added new skeletal outline sections for future
updates.
6.7. waltermire -04- to -05-
o Are we including user activities and behavior in the scope of this
work? That seems to be layer 8 stuff, appropriate to an IDS/IPS
application, not Internet stuff.
o I removed the references to what the WG will do because this
belongs in the charter, not the (potentially long-lived) use cases
document. I removed mention of charter objectives because the
charter may go through multiple iterations over time; there is a
website for hosting the charter; this document is not the correct
place for that discussion.
o I moved the discussion of NIST specifications to the
acknowledgements section.
o Removed the portion of the introduction that describes the
chapters; we have a table of concepts, and the existing text
seemed redundant.
o Removed marketing claims, to focus on technical concepts and
technical analysis, that would enable subsequent engineering
effort.
o Removed (commented out in XML) UC2 and UC3, and eliminated some
text that referred to these use cases.
o Modified IANA and Security Consideration sections.
o Moved Terms to the front, so we can use them in the subsequent
text.
o Removed the "Key Concepts" section, since the concepts of ORM and
IRM were not otherwise mentioned in the document. This would seem
more appropriate to the arch doc rather than use cases.
o Removed role=editor from David Waltermire's info, since there are
three editors on the document. The editor is most important when
one person writes the document that represents the work of
multiple people. When there are three editors, this role marking
isn't necessary.
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o Modified text to describe that this was specific to enterprises,
and that it was expected to overlap with service provider use
cases, and described the context of this scoped work within a
larger context of policy enforcement, and verification.
o The document had asset management, but the charter mentioned
asset, change, configuration, and vulnerability management, so I
added sections for each of those categories.
o Added text to Introduction explaining goal of the document.
o Added sections on various example use cases for asset management,
config management, change management, and vulnerability
management.
7. References
7.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
7.2. Informative References
[RFC2865] Rigney, C., Willens, S., Rubens, A., and W. Simpson,
"Remote Authentication Dial In User Service (RADIUS)", RFC
2865, June 2000.
Authors' Addresses
David Waltermire
National Institute of Standards and Technology
100 Bureau Drive
Gaithersburg, Maryland 20877
USA
Email: david.waltermire@nist.gov
David Harrington
Effective Software
50 Harding Rd
Portsmouth, NH 03801
USA
Email: ietfdbh@comcast.net
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