Contributing with XCCDFs, OVALs and remediations
There are three main types of content in the project, they are rules, defined using the XCCDF standard, checks, usually written in OVAL format, and remediations, that can be executed on ansible, bash, anaconda installer, puppet, ignition and kubernetes. ComplianceAsCode also has its own templating mechanism, allowing content writers to create models and use it to generate a number of checks and remediations.
Contributing
Contributions can be made for rules, checks, remediations or even utilities. There are different sets of guidelines for each type, for this reason there is a different topic for each of them.
Following lines are rather reference material. If you are completely new and would like to try more guided approach, we recommend you to go through materials prepared for our Content creation workshop. They can be found here. They guide you step by step through the process of creating new rules, profiles, checks and remediations.
Rules
Rules are input described in YAML which mirrors the XCCDF format (an XML
container). Rules are translated to become members of a Group
in an
XML file. All existing rules for Linux products can be found in the
linux_os/guide
directory. For non-Linux products (e.g., jre
), this
content can be found in the <product>/guide
. The exact location
depends on the group (or category) that a rule belongs to.
For an example of rule group, see
linux_os/guide/system/software/disk_partitioning/partition_for_tmp/rule.yml
.
The id of this rule is partition_for_tmp
; this rule belongs to the
disk_partitioning
group, which in turn belongs to the software
group
(which in turn belongs to the system
group). Because this rule is in
linux_os/guide
, it can be shared by all Linux products.
Rules describe the desired state of the system and may contain references if they are parts of higher-level standards. All rules should reflect only a single configuration change for compliance purposes.
Structurally, a rule is a YAML file (which can contain Jinja macros) that represents a dictionary.
A rule YAML file has one implied attribute:
id
: The primary identifier for the rule to be referenced from profiles. This is inferred from the file name and links it to checks and fixes with the same file name.
A rule itself contains these attributes:
title
: Human-readable title of the rule.rationale
: Human-readable HTML description of the reason why the rule exists and why it is important from the technical point of view. For example, rationale of thepartition_for_tmp
rule states that:The <tt>/tmp</tt> partition is used as temporary storage by many programs. Placing <tt>/tmp</tt> in its own partition enables the setting of more restrictive mount options, which can help protect programs which use it.
description
: Human-readable HTML description, which provides broader context for non-experts than the rationale. For example, description of thepartition_for_tmp
rule states that:requires
: Theid
of another rule or group that must be selected and enabled in a profile.conflicts
: Theid
of another rule or group that must not be selected and disabled in a profile.The <tt>/var/tmp</tt> directory is a world-writable directory used for temporary file storage. Ensure it has its own partition or logical volume at installation time, or migrate it using LVM.
severity
: Is used for metrics and tracking. It can have one of the following values:unknown
,info
,low
,medium
, orhigh
.Level Description unknown
Severity not defined (default)
info
Rule is informational only. Failing the rule doesn’t imply failure to conform to the security guidance of the benchmark.
low
Not a serious problem
medium
Fairly serious problem
high
Grave or critical problem
When deciding on severity levels, it is best to follow the following guidelines:
Table Vulnerability Severity Category Code Definitions Severity
DISA Category
Category Code Guidelines
high
CAT I
Any vulnerability, the exploitation of which will directly and immediately result in loss of Confidentiality, Availability, or Integrity.
medium
CAT II
Any vulnerability, the exploitation of which has a potential to result in loss of Confidentiality, Availability, or Integrity.
low
CAT III
Any vulnerability, the existence of which degrades measures to protect againstloss of Confidentiality, Availability, or Integrity.
The severity of the rule can be overridden by a profile with
refine-rule
selector.platform
orplatforms
: Defines applicability of a rule. It is specified either as a single platform or as a list of platforms. For example, if a rule is not applicable to containers, the list should contain the itemmachine
, which means it will be evaluated only if the targeted scan environment is either bare-metal or virtual machine. Also, it can restrict applicability on higher software layers. By setting toshadow-utils
, the rule will have its applicability restricted to only environments which haveshadow-utils
package installed. The available options can be found in the file <product>/cpe/<product>-cpe-dictionary.xml (e.g.: rhel8/cpe/rhel8-cpe-dictionary.xml). In order to support a new value, an OVAL check (ofinventory
class) must be created undershared/checks/oval/
and referenced in the dictionary file. It is possible to specify multiple platforms in the list. In that case, they are implicitly connected with “OR” operand.ocil
: Defines asserting statements to check whether or not the rule is valid.ocil_clause
: This attribute contains the statement which describes how to determine whether the statement is true or false. Check outrule.yml
inlinux_os/guide/system/software/disk_partitioning/encrypt_partitions/
: this contains apartitions do not have a type of crypto_LUKS
value forocil_clause
. This clause is prefixed with the phraseIs it the case that <ocil_clause> ?
.
A rule may contain those reference-type attributes:
identifiers
: This is related to products that the rule applies to; this is a dictionary. Currently, only the Common Configuration Enumeration or CCE identifier is supported. Other identifiers can be added as well. Contributions to add these other identifiers are welcomed. The table below shows a list of common identifiers and their current support in a rule:URI Supported Identifier Value Description Yes
Common Configuration Enumeration (CCE) – the identifier value MUST be a CCE version 5 number
No
CPE –the identifier value MUST be a CPE version 2.0 or 2.3 name
No
CVE –the identifier value MUST be a CVE number
No
CERT Coordination Center – the identifier value SHOULD be a CERT advisory identifier (e.g., “CA-2004-02”)
No
US-CERT vulnerability notes database – the identifier value SHOULD be a vulnerability note number (e.g., “709220”)
No
US-CERT technical cyber security alerts –the identifier value SHOULD be a technical cyber security alert ID (e.g., “TA05-189A”)
When the rule is related to RHEL, it should have a CCE. A CEE (e.g. cce@rhel7: CCE-80328-8) is used as a global identifier that maps the rule to the product over the lifetime of a rule. There should only be one CCE mapped to a rule as a global identifier. Any other usage of CCE is no longer considered a best practice. CCEs are also product dependent which means that a different CCE must be used for each different product and product version. For example if
cce@rhel7: 80328-8
exists in a rule, that CCE cannot be used for another product or version (e.g. rhel9), and the CCE MUST be retired with the rule. Available CCEs that can be assigned to new rules are listed in theshared/references/cce-rhel-avail.txt
file.references
: This is related to the compliance document line items that the rule applies to. These can be attributes such asstigid
,srg
,nist
, etc., whose keys may be modified with a product (e.g.,stigid@rhel7
) to restrict what products a reference identifier applies to. Depending on the type of reference (e.g. catalog, ruleid, etc.) will depend on how many can be added to a single rule. In addition, certain references in a rule such asstigid
orcis
only apply to a certain product and product version; they cannot be used for multiple products and versions.Key Reference Type Mapping to Rule Example Format cis@<product><product_version>
Center for Internet Security (catalog identifier)
0-to-many, 0-to-1 is preferred
5.2.5
cjis
Criminal Justice Information System (catalog identifier)
0-to-1
5.4.1.1
cui
Controlled Unclassified Information (catalog identifier)
0-to-many, 0-to-1 is preferred
3.1.7
disa
DISA Control Correlation Identifiers (catalog identifier)
0-to-many
CCI-000018,CCI-000172,CCI-001403
srg, vmmsrg, etc.
DISA Security Requirements Guide (catalog identifier)
0-to-many
SRG-OS-000003-GPOS-00004
stigid@<product><product_version>
DISA STIG identifier (rule identifier)
0-to-1
RHEL-07-030874
hipaa
Health Insurance Portability and Accountability Act of 1996 (HIPAA) (catalog identifier)
0-to-many
164.308(a)(1)(ii)(D),164.308(a)(3)(ii)(A)
nist
National Institute for Standards and Technology 800-53 (catalog identifier)
0-to-many
AC-2(4),AC-17(7),AU-1(b)
nist-csf
National Institute for Standards and Technology Cybersecurity Framework (catalog identifier)
0-to-many
DE.AE-3,DE.AE-5,DE.CM-1
ospp
National Information Assurance Partnership (selected control identifier)
0-to-many
FMT_MOF_EXT.1
pcidss
Payment Card Industry Data Security Standard
0-to-many, 0-to-1 is preferred
Req-8.7.c
See
linux_os/guide/system/software/disk_partitioning/encrypt_partitions/rule.yml
for an example of reference-type attributes as there are others that are not referenced above.
Some of existing rule definitions contain attributes that use macros. There are two implementations of macros:
Jinja macros, that are defined in
shared/macros.jinja
, andshared/macros-highlevel.jinja
.Legacy XSLT macros, which are defined in
shared/transforms/*.xslt
.
For example, the ocil
attribute of service_ntpd_enabled
uses the
ocil_service_enabled
jinja macro. Due to the need of supporting
Ansible output, which also uses jinja, we had to modify control
sequences, so macro operations require one more curly brace. For
example, invocation of the partition macro looks like
{{{ complete_ocil_entry_separate_partition(part="/tmp") }}}
- there
are three opening and closing curly braces instead of the two that are
documented in the Jinja guide.
shared/macros.jinja
contains specific low-level macros s.a.
systemd_ocil_service_enabled
, whereas shared/macros-highlevel.jinja
contains general macros s.a. ocil_service_enabled
, that decide which
one of the specialized macros to call based on the actual product being
used.
You can see references of high level macros here.
The macros that are likely to be used in descriptions begin by
describe_
, whereas macros likely to be used in OCIL entries begin with
ocil_
. Sometimes, a rule requires ocil
and ocil_clause
to be
specified, and they depend on each other. Macros that begin with
complete_ocil_entry_
were designed for exactly this purpose, as they
make sure that OCIL and OCIL clauses are defined and consistent. Macros
that begin with underscores are not meant to be used in descriptions.
To parametrize rules and remediations as well as Jinja macros, you can
use product-specific variables defined in product.yml
in product root
directory. Moreover, you can define implied properties which are
variables inferred from them. For example, you can define a condition
that checks if the system uses yum
or dnf
as a package manager and
based on that populate a variable containing correct path to the
configuration file. The inferring logic is implemented in
_get_implied_properties
in ssg/yaml.py
. Constants and mappings used
in implied properties should be defined in ssg/constants.py
.
Rules are unselected by default - even if the scanner reads rule
definitions, they are effectively ignored during the scan or
remediation. A rule may be selected by any number of profiles, so when
the scanner is scanning using a profile the rule is included in, the
rule is taken into account. For example, the rule identified by
partition_for_tmp
defined in
shared/xccdf/system/software/disk_partitioning.xml
is included in the
RHEL7 C2S
profile in rhel7/profiles/C2S.xml
.
Checks are connected to rules by the oval
element and the filename in
which it is found. Remediations (i.e. fixes) are assigned to rules based
on their basename. Therefore, the rule sshd_print_last_log
has a
bash
fix associated as there is a bash
script
shared/fixes/bash/sshd_print_last_log.sh
. As there is an Ansible
playbook shared/fixes/ansible/sshd_print_last_log.yml
, the rule has
also an Ansible fix associated.
Rule Directories
The rule directory simplifies the structure of a rule and all of its associated content by placing it all under a common directory. The structure of a rule directory looks like the following example:
linux_os/guide/system/group/rule_id/rule.yml
linux_os/guide/system/group/rule_id/bash/ol7.sh
linux_os/guide/system/group/rule_id/bash/shared.sh
linux_os/guide/system/group/rule_id/oval/rhel7.xml
linux_os/guide/system/group/rule_id/oval/shared.xml
To be considered a rule directory, it must be a directory contained in a
benchmark pointed to by some product. The directory must have a name
that is the id of the rule, and must contain a file called rule.yml
which is a YAML Rule description as described above. This directory can
then contain the following subdirectories:
anaconda
- for Anaconda remediation content, ending in.anaconda
ansible
- for Ansible remediation content, ending in.yml
bash
- for Bash remediation content, ending in.sh
oval
- for OVAL check content, ending in.xml
puppet
- for Puppet remediation content, ending in.pp
ignition
- for Ignition remediation content, ending in.yml
kubernetes
- for Kubernetes remediation content, ending in.yml
sce
- for Script Check Engine content, with any file extensionblueprint
- for OSBuild blueprint content, ending in.toml
In each of these subdirectories, a file named shared.ext
will apply to
all products and be included in all builds, but {{{ product }}}.ext
will only get included in the build for {{{ product }}}
(e.g.,
rhel7.xml
above will only be included in the build of the rhel7
guide content and not in the ol7
content). Additionally, we support
the use of unversioned products here (e.g., rhel
applies to rhel7
,
rhel8
, and rhel9
). Note that .ext
must be substituted for the
correct extension for content of that type (e.g., .sh
for bash
content). Further, all of these directories are optional and will only
be searched for content if present. Lastly, the product naming of
content will not override the contents of platform
or prodtype
fields in the content itself (e.g., if rhel7
is not present in the
rhel7.xml
OVAL check platform specifier, it will be included in the
build artifacts but later removed because it doesn’t match the platform).
This means that any shared (or templated) checks won’t be searched if
a product-specific file is present but has the wrong applicability;
this includes shared checks being preferred above templated checks.
Currently the build system supports both rule files (discussed above)
and rule directories. For example content in this format, please see
rules in linux_os/guide
.
To interact with build directories, the ssg.rules
and
ssg.rule_dir_stats
modules have been created, as well as three
utilities:
utils/rule_dir_json.py
- to generate a JSON tree describing the current content of all guidesutils/rule_dir_stats.py
- for analyzing the JSON tree and finding information about specific rules, products, or summary statisticsutils/rule_dir_diff.py
- for diffing two JSON trees (e.g., before and after a major change), using the same interface asrule_dir_stats.py
.
For more information about these utilities, please see their help text.
To interact with rule.yml
files and the OVALs inside a rule directory,
the following utilities are provided:
utils/mod_prodtype.py
This utility modifies the prodtype field of rules. It supports several commands:
mod_prodtype.py <rule_id> list
- list the computed and actual prodtype of the rule specified byrule_id
.mod_prodtype.py <rule_id> add <product> [<product> ...]
- add additional products to the prodtype of the rule specified byrule_id
.mod_prodtype.py <rule_id> remove <product> [<product> ...]
- remove products to the prodtype of the rule specified byrule_id
.mod_prodtype.py <rule_id> replace <replacement> [<replacement> ...]
- do the specified replacement transformations. A replacement transformation is of the formmatch~replace
wherematch
andreplace
are a comma separated list of products. If all of the products inmatch
exist in the originalprodtype
of the rule, they are removed and the products inreplace
are added.
This utility requires an up to date JSON tree created by
rule_dir_json.py
.
utils/mod_checks.py
This utility modifies the <affected>
element of an OVAL check. It
supports several commands on a given rule:
mod_checks.py <rule_id> list
- list all OVALs, their computed products, and their actual platforms.mod_checks.py <rule_id> delete <product>
- delete the OVAL for the the specified product.mod_checks.py <rule_id> make_shared <product>
- moves the product OVAL to the shared OVAL (e.g.,rhel7.xml
toshared.xml
).mod_checks.py <rule_id> diff <product> <product>
- Performs a diff between two OVALs (product can beshared
to diff against the shared OVAL).
In addition, the mod_checks.py
utility supports modifying the shared
OVAL with the following commands:
mod_checks.py <rule_id> add <platform> [<platform> ...]
- adds the specified platforms to the shared OVAL for the rule specified byrule_id
.mod_checks.py <rule_id> remove <platform> [<platform> ...]
- removes the specified platforms from the shared OVAL.mod_checks.py <rule_id> replace <replacement> [<replacement ...]
- do the specified replacement against the platforms in the shared OVAL. See the description ofreplace
undermod_prodtype.py
for more information about the format of a replacement.
This utility requires an up to date JSON tree created by
rule_dir_json.py
.
utils/mod_fixes.py
This utility modifies the <affected>
element of a remediation. It
supports several commands on a given rule and for the specified
remediation language:
mod_fixes.py <rule_id> <lang> list
- list all fixes, their computed products, and their actual platforms.mod_fixes.py <rule_id> <lang> delete <product>
- delete the fix for the specified product.mod_fixes.py <rule_id> <lang> make_shared <product>
- moves the product fix to the shared fix (e.g.,rhel7.sh
toshared.sh
).mod_fixes.py <rule_id> <lang> diff <product> <product>
- Performs a diff between two fixes (product can beshared
to diff against the shared fix).
In addition, the mod_fixes.py
utility supports modifying the shared
fixes with the following commands:
mod_fixes.py <rule_id> <lang> add <platform> [<platform> ...]
- adds the specified platforms to the shared fix for the rule specified byrule_id
.mod_fixes.py <rule_id> <lang> remove <platform> [<platform> ...]
- removes the specified platforms from the shared fix.mod_fixes.py <rule_id> <lang> replace <replacement> [<replacement ...]
- do the specified replacement against the platforms in the shared fix. See the description ofreplace
undermod_prodtype.py
for more information about the format of a replacement.
This utility requires an up to date JSON tree created by
rule_dir_json.py
.
utils/add_platform_rule.py
This utility can be used to bootstrap and test Kubernetes/OpenShift application checks. See the help output for more detailed usage examples of each of the supported subcommands:
utils/add_platform_rule.py create --rule=<rule_name> <options>
- creates files for a new rule.utils/add_platform_rule.py test --rule=<rule_name> <options>
- tests a rule against local files using an oscap container.utils/add_platform_rule.py cluster-test --rule=<rule_name> <options>
tests a rule against a running OCP4 cluster using compliance-operator.
This utility requires the following:
KUBECONFIG env set to a kubeconfig file for a running OCP4 cluster.
oc
andpodman
in PATH.
Tips:
The –yamlpath option requires a specialized format to specify the resource element to check. See https://github.com/OpenSCAP/yaml-filter/wiki/YAML-Path-Definition for documentation.
To use the local
test
subcommand, first create a yaml file under a directory structure under /tmp that mirrors the API path. For example, if the resource’s full path is /api/v1/foo, save the yaml to /tmp/api/v1/foo. Runningtest
will then check the rule against the local file by launching an openscap-1.3.3 container using podman.
Checks
Checks are used to evaluate a Rule. There are two types of check content supported by ComplianceAsCode: OVAL and SCE. Note that OVAL is standardized by NIST and has better cross-scanner support than SCE does. However, because SCE can use any language on the target system (Bash, Python, …) it is much more flexible and general-purpose than OVAL. This project generally encourages OVAL unless it lacks support for certain features.
OVAL Check Content
They are written using a custom OVAL syntax and are transformed by the system during the building process into OVAL compliant checks.
The OVAL checks are stored as XML files and the build system can source them from:
the
oval
directory of a rulethe shared pool of checks
shared/checks/oval
a template
In order to create a new check you must create a file in the appropriate directory. The id attribute of the check needs to match the id of its rule. The content of the file should follow the OVAL specification with these exceptions:
The root tag must be
<def-group>
If the OVAL check has to be a certain OVAL version, you can add
oval_version="oval_version_number"
as an attribute to the root tag. Otherwise ifoval_version
does not exist in<def-group>
, it is assumed that the OVAL file applies to any OVAL version.Don’t use the tags
<definitions>
<tests>
<objects>
<states>
, instead, put the tags<definition>
<*_test>
<*_object>
<*_state>
directly inside the<def-group>
tag.TODO Namespaces
This is an example of a check, written using the custom OVAL syntax, that checks if the group that owns the file /etc/cron.allow is the root:
<def-group oval_version="5.11">
<definition class="compliance" id="file_groupowner_cron_allow" version="1">
<metadata>
<title>Verify group who owns 'cron.allow' file</title>
<affected family="unix">
<platform>Red Hat Enterprise Linux 7</platform>
</affected>
<description>The /etc/cron.allow file should be owned by the appropriate
group.</description>
</metadata>
<criteria>
<criterion test_ref="test_groupowner_etc_cron_allow" />
</criteria>
</definition>
<unix:file_test check="all" check_existence="any_exist"
comment="Testing group ownership /etc/cron.allow" id="test_groupowner_etc_cron_allow"
version="1">
<unix:object object_ref="object_groupowner_cron_allow_file" />
<unix:state state_ref="state_groupowner_cron_allow_file" />
</unix:file_test>
<unix:file_state id="state_groupowner_cron_allow_file" version="1">
<unix:group_id datatype="int">0</unix:group_id>
</unix:file_state>
<unix:file_object comment="/etc/cron.allow"
id="object_groupowner_cron_allow_file" version="1">
<unix:filepath>/etc/cron.allow</unix:filepath>
</unix:file_object>
Before you start creating an OVAL check, please consult our list of JINJA macros specific for OVAL. It might save time for you as an author as well as for reviewers.
Limitations and pitfalls
This section aims to list known OVAL limitations and situations that OVAL can’t handle well or at all.
Checking that all objects exist based on a variable
A test with check_existence=”all_exist” attribute will not ensure that all objects defined based on a variable exist.
This happens because in the test context all_exist defaults to at_least_one_exists. Reference: OVAL ExistenceEnumeration
This means that an object defined based on a variable with multiple values will result in pass if just one of the expected objects exist. Example, lets say there is a variable containing multiple paths, and you’d like to check that all of them are present in the file system. The following snippet would work if all_exist didn’t default to at_least_one_exists.
<unix:file_test id="" check="all" check_existence="all_exist" comment="This test fails to ensure that all paths from variable exist" version="1">
<unix:object object_ref="collect_objects_based_on_variable" />
</unix:file_test>
<unix:file_object id="collect_objects_based_on_variable" version="1">
<unix:path datatype="string" var_ref="variable_containing_a_list_of_paths" var_check="at least one"/>
</unix:file_object>
A workaround is to add a second test to count the number of objects collected and compare the sum against the number of values in the variable. This works well, except when none of the files exist, which leads to a result of unknown. Counting the number of collected items of an object definition that doesn’t exist is unknown (not 0, for example).
Platform applicability
Whenever possible, please reuse the macros and form high-level simplifications.
SCE Check Content
SCE is a mechanism for running arbitrary scripts while delivering them via the same data stream as OVAL content. These checks (being written in a general-purpose programming language) can be more flexible than OVAL checks but at the downside of not being compliant with the relevant NIST standards (and thus losing interoperability with other scanners). This project prefers Bash SCE content.
Within a rule directory, SCE content is stored under the sce/
subfolder;
it doesn’t have a single extension (taking the preferred extension of the
language the check is written in, .sh
for Bash content).
To build SCE content, specify the -DSSG_SCE_ENABLED=ON
option to CMake;
note that we default to not building SCE content.
We support the same comment-based mechanism for controlling script parameters as the test suite and rest of the content system. The following parameters are unique to SCE:
check-import
: can bestdout
orstderr
and corresponds to the XCCDF’s<check-import />
element’simport-name
attribute.check-export
: a comma-separated list ofvariable_name=xccdf_variable
pairs to export via XCCDF<check-export />
elements. oscap will generate 3 env_variables before calling the SCE script:XCCDF_VALUE_<variable_name>=<value> XCCDF_TYPE_<variable_name>=<type> XCCDF_OPERATOR_<variable_name>=<operator>
The
<value>
,<type>
and<operator>
come from the corresponding xccdf variable.complex-check
: an XCCDF operator (AND
orOR
) to be passed as theoperator
attribute on the XCCDF element’s<complex-check />
element. Note that this gets provisioned into the<Rule />
element to handle whether both the OVAL and SCE checks must pass (AND) or whether only one is necessary (OR). If a rule only has one or the other check language, it is not necessary. Additionally, OCIL checks, if any is present in therule.yml
, are added as a top-level OR-operator<complex-check />
with the results of this<complex-check />
.
For an example of SCE content, consider the check:
$ cat ./linux_os/guide/system/accounts/accounts-session/accounts_users_own_home_directories/sce/ubuntu2004.sh
#!/bin/bash
#
# Contributed by Canonical.
#
# Disable job control and run the last command of a pipeline in the current shell environment
# Require Bash 4.2 and later
#
# platform = multi_platform_ubuntu
# check-import = stdout
set +m
shopt -s lastpipe
result=$XCCDF_RESULT_PASS
cat /etc/passwd | egrep -v '^(root|halt|sync|shutdown)' | awk -F: '($7 != "/usr/sbin/nologin" && $7 != "/bin/false") { print $1 " " $6 }'| while read user dir; do
if [ ! -d "$dir" ]; then
echo "The home directory ($dir) of user $user does not exist."
result=$XCCDF_RESULT_FAIL
break
else
owner=$(stat -L -c "%U" "$dir")
if [ "$owner" != "$user" ]; then
echo "The home directory ($dir) of user $user is owned by $owner."
result=$XCCDF_RESULT_FAIL
break
fi
fi
done
exit $result
Since this rule lacks an OVAL, this rule does not need a complex-check
attribute. Additionally, this rule doesn’t use any XCCDF variables and
thus doesn’t need a check-export
element.
Remediations
Remediations, also called fixes, are used to change the state of the machine, so that previously non-passing rules can pass. There can be multiple versions of the same remediation meant to be executed by different applications, more specifically Ansible, Bash, Anaconda, Puppet, Ignition and Kubernetes. By default all remediation languages are built and included in the DataStream.
But each product can specify its own set of remediation to include in
the DataStream via a CMake Variable in the product’s CMakeLists.txt
.
See example below, from OCP4 product, ocp4/CMakeLists.txt
:
set(PRODUCT_REMEDIATION_LANGUAGES "ignition;kubernetes")
They also have to be idempotent, meaning that they must be able to be executed multiple times without causing the fixes to accumulate. The Ansible’s language works in such a way that this behavior is built-in, however, for the other versions, the remediations must have it implemented explicitly. Remediations also carry metadata that should be present at the beginning of the files. This meta data will be converted in XCCDF tags during the building process. That is how it looks like and what it means:
# platform = multi_platform_all
# reboot = false
# strategy = restrict
# complexity = low
# disruption = low
Field | Description | Accepted values |
---|---|---|
platform |
CPE name, CPE applicability language expression or even wildcards declaring which platforms the fix can be applied |
Default CPE dictionary is packaged along with openscap. Custom CPE dictionaries can be used. Wildcards are multi_platform_[all, oval, fedora, debian, ubuntu, linux, rhel, openstack, opensuse, rhev, sle]. |
reboot |
Whether or not a reboot is necessary after the fix |
true, false |
strategy |
The method or approach for making the described fix. Only informative for now |
unknown, configure, disable, enable, patch, policy, restrict, update |
complexity |
The estimated complexity or difficulty of applying the fix to the target. Only informative for now |
unknown, low, medium, high |
disruption |
An estimate of the potential for disruption or operational degradation that the application of this fix will impose on the target. Only informative for now |
unknown, low, medium, high |
Ansible
Important
The minimum version of Ansible must be at the latest supported version. See https://access.redhat.com/support/policy/updates/ansible-engine for information on the supported Ansible versions.
Ansible remediations are either:
Stored as
.yml
files in directoryansible
in the rule directory.Generated from templates.
Generated using jinja2 macros.
They are meant to be executed by Ansible itself when requested by openscap, so they are written using Ansible’s own language with the following exceptions:
The remediation content must be only the tasks section of what would be a playbook.
Tasks can include blocks for grouping related tasks.
The
when
clause will get augmented in certain scenarios.
Notifications and handlers are not supported.
Tags are not necessary, because they are automatically generated during build of content.
Here is an example of an Ansible remediation that ensures the SELinux is enabled in grub:
# platform = multi_platform_rhel,multi_platform_fedora
# reboot = false
# strategy = restrict
# complexity = low
# disruption = low
- name: Ensure SELinux Not Disabled in /etc/default/grub
replace:
dest: /etc/default/grub
regexp: selinux=0
The Ansible remediation will get included by our build system to the
SCAP datastream in the fix
element of respective rule.
The build system generates an Ansible Playbook from the remediation for
all profiles. The generated Playbook is located in
/build/<product>/playbooks/<profile_id>/<rule_id>.yml
.
For each rule in the given product we also generate an Ansible Playbook
regardless presence of the rule in any profile. The generated Playbook
is located in /build/<product>/playbooks/all/<rule_id>.yml
. The
/build/<product>/playbooks/all/
directory represents the virtual
(all)
profile which consists of all rules in the product. Due to
undefined XCCDF Value selectors in this pseudo-profile, these Playbooks
use defaults of XCCDF Values when applicable.
We also build profile Playbook that contains tasks for all rules in the
profile. The Playbook is generated in
/build/ansible/<product>-playbook-<profile_id>.yml
.
Jinja macros for Ansible content are located in
/shared/macros-ansible.jinja
. You can see their reference
[here]( jinja_macros/ansible:ansible).
Whenever possible, please reuse the macros and form high-level simplifications. This ensures consistent, high quality remediations that we can edit in one place and reuse in many places.
Bash
Bash remediations are stored as shell script files in the bash directory in a rule’s directory. You can make use of any available command, but beware of too specific or complex solutions, as it may lead to a narrow range of supported platforms.
Following, you can see an example of a bash remediation that sets the maximum number of days a password may be used:
# platform = Red Hat Enterprise Linux 7
{{{ bash_instantiate_variables("var_accounts_maximum_age_login_defs) }}}
grep -q ^PASS_MAX_DAYS /etc/login.defs && \
sed -i "s/PASS_MAX_DAYS.*/PASS_MAX_DAYS $var_accounts_maximum_age_login_defs/g" /etc/login.defs
if [ $? -ne 0 ]; then
echo "PASS_MAX_DAYS $var_accounts_maximum_age_login_defs" >> /etc/login.defs
fi
When writing new bash remediations content, please follow the following guidelines:
Use four spaces for indentation rather than tabs.
You can use macros from
shared/macros-bash.jinja
in the remediation content. If the macro is used from a nested block, use theindent
jinja2 filter assuming the 4-space indentation. Typically, you want to call the macro with the intended indentation, and asindent
doesn’t indent the first line by default, you just pass the number of spaces as the only argument. See the remediation for ruleensure_fedora_gpgkey_installed
for reference.Prefer to use
sed
rather thanawk
.Try to keep expressions simple, avoid double negations. Use compound lists with moderation and only if you understand them.
Test your script in the “strict mode” with
set -e -o pipefail
specified at the top of it. Make sure that the script doesn’t end prematurely in the strict mode.Beware of constructs such as
[ $x = 1 ] && echo "$x is one"
as they violate the previous point.[ $x != 1 ] || echo "$x is one"
is OK.Use the
die
macro defined inshared/macros-bash.jinja
to handle exceptions and terminate the remediation, such as{{{ die("An error was encountered during the remediation of rule.") }}}
.Run
shellcheck
over your remediation script. Make sure that you fix all warnings that are applicable. If you are not sure, mention those warnings in the pull request description.Use POSIX syntax in regular expressions, so prefer
grep '^[[:space:]]*something'
overgrep '^\s*something'
.
Jinja macros that generate Bash remediations can be found in
shared/macros-bash.jinja
. You can see their reference
here.
Kubernetes
Jinja macros for Kubernetes content are located in
/shared/macros-kubernetes.jinja
. You can see their reference
here
Templating
Writing OVAL checks, Bash, or any other content can be tedious work. For
certain types of rules we provide templates. If there is a template that
can be used for the new rule you only need to specify the template name
and its parameters in rule.yml
and the content will be generated
during the build.
The templating system currently supports generating OVAL checks and
Ansible, Bash, Anaconda, Puppet, Ignition and Kubernetes remediations.
All templates can be found in
shared/templates directory. The files
are named template_<TYPE>_<NAME>
, where <TYPE>
should be OVAL,
ANSIBLE, BASH, ANACONDA, PUPPET, IGNITION and KUBERNETES and <NAME>
is
the template name.
Using Templates
To use a template in rule.yml
add template:
key there and fill it
accordingly. The general form is the following:
template:
name: template_name
vars:
param_name: value # these parameters are individual for each template
param_name@rhel7: value1
param_name@rhel8: value2
backends: # optional
ansible: "off"
bash: "on" # on is implicit value
The vars:
key contains template parameters and their values which will
be substituted into the template. Each template has specific parameters.
To use different values of parameters based on product, append @
followed by product ID to the parameter name.
The backends:
key is optional. By default, all languages supported by
a given template will be generated. with given name exist will be
generated. This key can be used to explicitly opt out from generating a
certain type of content for the rule.
For example, to generate templated content except Bash remediation for
rule “Package GCC is Installed” using package_installed
template, add
the following to rule.yml
:
template:
name: package_installed
vars:
pkgname: gcc
backends:
bash: "off"
Important
The build system does not support implicit conversion of bool strings when Python 2 is used, so
bash: True
argument in the example above would cause a build error. One should always use quoted strings as arguments until Python 2 is completely removed from the list of supported interpreters.
you can see reference of all available templates here.
Applicability of content
All profiles and rules included in a products’ DataStream are applicable
by default. For example, all profiles and rules included in a rhel8
DS
will apply and evaluate in a RHEL 8 host.
But a content’s applicability can be fine tuned to a specific environment in the product. The SCAP standard specifies two mechanisms to define applicability: - CPE: Allows a specific hardware or platform to be identified. - Applicability Language: Allows the construction of logical expressions involving CPEs.
At the moment, only the CPE mechanism is supported.
Applicability by CPE
The CPEs defined by the project are declared in
shared/applicability/cpes.yml
.
Syntax is as follows (using examples of existing CPEs):
cpes:
- machine: ## The id of the CPE
name: "cpe:/a:machine" ## The CPE Name as defined by the CPE standard
title: "Bare-metal or Virtual Machine" ## Human readable title for the CPE
check_id: installed_env_is_a_machine ## ID of OVAL implementing the applicability check
- gdm:
name: "cpe:/a:gdm"
title: "Package gdm is installed"
check_id: installed_env_has_gdm_package
The first entry above defines a CPE whose id
is machine
, this CPE
is used for rules not applicable to containers.
A rule or profile with platform: machine
will be evaluated only if the
targeted scan environment is either bare-metal or virtual machine.
The second entry defines a CPE for GDM.
By setting the platform
to gdm
, the rule will have its applicability
restricted to only environments which have gdm
package installed.
The OVAL checks for the CPE need to be of inventory
class, and must be
under shared/checks/oval/
.
Setting a product’s default CPE
The product’s default applicability is set in its product.yml
file,
under the cpes
key. For example:
cpes:
- example:
name: "cpe:/o:example"
title: "Example"
check_id: installed_OS_is_part_of_Unix_family
Multiple CPEs can be set as default platforms for a product.
Setting the product’s CPE source directory
The key cpes_root
in product.yml
file specifies the directory to
source the CPEs from.
By default, all products source their CPEs from shared/applicability/
.
Any file with extension .yml
will be sourced for CPE definitions.
Note: Only CPEs that are referenced by a rule or profile will be included in the product’s CPE Dictionary. If no content requires the CPE, it is deemed unnecessary and won’t be included in the dictionary.
Tests (ctest)
ComplianceAsCode uses ctest to orchestrate testing upstream. To run the
test suite go to the build folder and execute ctest
:
cd build/
ctest -j 4
Check out the various ctest
options to perform specific testing, you
can rerun just one test or skip all tests that match a regex. (See -R,
-E and other options in the ctest man page)
Tests are added using the add_test cmake call. Each test should finish with a 0 exit-code in case everything went well and a non-zero if something failed. Output (both stdout and stderr) are collected by ctest and stored in logs or displayed. Make sure you never hard-code a path to any tool when doing testing (or anything really) in the cmake code. Always use configuration to find all the paths and then use the respective variable.
See some of the existing testing code in cmake/SSGCommon.cmake
.
Tests (OCP4)
Unit tests
Running unit tests is very useful way to verify the content being written without requiring a full-blown OpenShift cluster.
The unit testing approach for content requires a container where the scanning will be executed. This container will be a small replication of the environment where the content is intended to run.
To build the container, from the project’s root directory, execute the following command:
podman build --build-arg CLIENT_PUBLIC_KEY=$(cat ~/.ssh/id_rsa.pub) -t ssg_test_suite -f Dockerfiles/test_suite-fedora
Unit tests reside en each rule’s tests/
directory. Tests are
simply bash scripts that set up the required environment
and set expectations on what the scan is suposed to output.
The naming convention is as follows:
<test name>.<expected result>.sh
e.g. when testing if encryption is disabled in a specific cloud provider, and that this should fail a compliance scan, you’d have a file named as follows:
encryption_disabled.fail.sh
Note that this file has to be executable. So don’t forget to change the mode appropriately.
Test files shall always begin with the following lines:
#!/bin/bash
# remediation = none
Bash is used to evaluate the scripts. And we don’t expect remediations
executed by OpenSCAP itself (this is done elsewhere), so we set
remediation = none
.
OpenShift content (as well as other Kubernetes content) is usually meant
to run through the Compliance Operator. The aforementioned component will
read the API paths specified as warnings
and persist them on a temporary
volume. The Compliance Operator is also the one that handles remediating
rules, this is why we turned remediations off in our scripts as mentioned
earlier.
For unit tests, we’ll do something similar when setting up the testing container in our test scripts: We’ll create a directory for the API resource object and persist it there.
Note that the content uses the path /kubernetes-api-resources
by
default as a base for any API path for Kubernetes. So, be mindful of
always using that.
An example looks as follows:
kube_apipath="/kubernetes-api-resources"
machinev1beta1="/apis/machine.openshift.io/v1beta1"
machineset_apipath="$machinev1beta1/machinesets?limit=500"
# Create kubernetes resource directory path
mkdir -p "$kube_apipath/$machinev1beta1"
# Persist kubernetes resource
cat <<EOF > "$kube_apipath/$machineset_apipath"
{
"apiVersion": "v1",
...
EOF
When the scanner tests the content for this rule, it’ll read the Kubernetes resource (both YAML or JSON are fine for this) and evaluate it accordingly.
Note that some rules require a specific CPE to be set. e.g. there are some rules that are meant to run on a specific cloud platform.
You’ll see them from the platforms
key of the rule:
platforms:
- ocp4-on-azure
For rules like these, you’ll also need to persist the appropriate CPE information (normally another Kubernetes object).
The information needed varies on each CPE. These are defined
in /shared/checks/oval
.
For the ocp4-on-azure
example, the CPE requires that the
infrastructures/cluster
resource specifies the platform
as Azure
. That would look as follows:
kube_apipath="/kubernetes-api-resources"
# Create infra file for CPE to pass
mkdir -p "$kube_apipath/apis/config.openshift.io/v1/infrastructures/"
cat <<EOF > "$kube_apipath/apis/config.openshift.io/v1/infrastructures/cluster"
{
"apiVersion": "config.openshift.io/v1",
"kind": "Infrastructure",
"metadata": {
"name": "cluster"
},
"spec": {
"platformSpec": {
"type": "Azure"
}
},
"status": {
"platform": "Azure",
"platformStatus": {
"azure": {
"cloudName": "AzurePublicCloud"
},
"type": "Azure"
}
}
}
EOF
For rules that use jq filters, they are using a unique file path instead of the one you see above, therefore we also need to install the jq package, run the jq test, and save the filtered jq result into that unique file path.
The format for the file path for a jq filter rule is:
"$kube_apipath$rule_apipath#$(echo -n "$rule_apipath$jq_filter" | sha256sum | awk '{print $1}')"
Noted it is important to know that the $rule_apipath
does not
have /
at the end, or it will cause a different hash with /
at the end, and jq result will be saved into a location that is
different from where the rule is checking, hence will fail the test.
We have a test file for rule ‘routes_rate_limit’ as an example that uses jq filter:
#!/bin/bash
# remediation = none
yum install -y jq
kube_apipath="/kubernetes-api-resources"
mkdir -p "$kube_apipath/apis/route.openshift.io/v1"
routes_apipath="/apis/route.openshift.io/v1/routes?limit=500"
cat <<EOF > "$kube_apipath$routes_apipath"
{
...
}
EOF
jq_filter='[.items[] | select(.metadata.namespace | startswith("kube-") or startswith("openshift-") | not) | select(.metadata.annotations["haproxy.router.openshift.io/rate-limit-connections"] == "true" | not) | .metadata.name]'
filteredpath="$kube_apipath$routes_apipath#$(echo -n "$routes_apipath$jq_filter" | sha256sum | awk '{print $1}')"
jq "$jq_filter" "$kube_apipath$routes_apipath" > "$filteredpath"
Before running the unit tests, the content needs to be built to ensure that the latest changes are taken into account:
./build_product ocp4
Remember this needs to be done every time before running the unit tests.
Now, with all of this set, we’ll run the unit test!
tests/test_rule_in_container.sh \
--dontclean --logdir logs_bash \
--remediate-using bash \
--name ssg_test_suite \
--datastream build/ssg-ocp4-ds.xml \
<rule name>
This command will run the unit tests on dedicated containers.
The logs will be located in the logs_bash
directory.
End-to-end tests
The ComplianceAsCode/content repo runs some end-to-end tests for the ocp4 content. These tests run over the OpenShift infrastructure, spawn an ephemeral cluster and run tests targetted at a specific profile.
The current workflow is as follows:
Install needed prerequisites (e.g. the compliance-operator and other resources it might need)
Run a scan using the specific profile (for the specific product)
Run manual remediations
Run automated remediations
Wait for remediations to converge
Run second scan
The test will pass if:
There are no errors in the scan runs
We have less rule failures after the remediations have been applied
The cluster status is not inconsistent
Rules may have extra verifications on them. For instance, one is able to verify if:
The rule’s expected result is gotten on a clean run.
The rule’s result changes after a remediation has been applied.
If an automated remediation is not possible, one is also able to created a “manual” remediation that will be run as a bash script. The end-to-end tests have a 15 minute timeout for the manual remediation scripts to be executed.
Writing e2e tests for specific rules
In order to test that a rule is yielding expected results in the e2e
tests, one must create a file called e2e.yml
in a tests/ocp4/
directory which will exist in the rule’s directory itself.
The format may look as follows:
---
default_result: [PASS|FAIL|SKIP]
result_after_remediation: [PASS|FAIL|SKIP]
Where:
default_result
will look at the result when the first scan is run.result_after_remediation
will look at the result when the second scan is run. The second scan takes place after remediations are applied.
Note that this format applies if the result of a rule will be the same accross roles in the cluster.
It is also possible to differentiate results between roles. For such a thing, the format would look as follows:
Let’s look at an example:
---
default_result:
worker: [PASS|FAIL|SKIP]
master: [PASS|FAIL|SKIP]
result_after_remediation:
worker: [PASS|FAIL|SKIP]
master: [PASS|FAIL|SKIP]
Where “worker” and “master” are node roles.
For the controller_use_service_account
rule, which exists in the
applications/openshift/controller/
directory, the directory tree will
contain the rule definition and the test file:
.
├── rule.yml
└── tests
└── ocp4
└── e2e.yml
In this case, we just want to verify that the default value returns a
passing result. So e2e.yml
has the following content:
---
default_result: PASS
Let’s look at another example:
For the api_server_encryption_provider_config
we want to apply a
remediation which cannot be applied via the compliance-operator
. So
we’ll need a manual remediation for this.
The directory structure looks as follows:
.
├── rule.yml
└── tests
└── ocp4
├── e2e-remediation.sh
└── e2e.yml
Where our test contains information for both the first default result and the expected result after the remediation has been applied:
---
default_result: FAIL
result_after_remediation: PASS
The remediation expects the name of the remediation script to be
e2e-remediation.sh
. The script should:
Apply the remediation.
Verify that the status has converged.
In the aforementioned case, the remediation script is as follows:
#!/bin/bash
oc patch apiservers cluster -p '{"spec":{"encryption":{"type":"aescbc"}}}' --type=merge
while true; do
status=$(oc get openshiftapiserver -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}')
echo "Current Encryption Status:"
oc get openshiftapiserver -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'
if [ "$status" == "EncryptionCompleted" ]; then
exit 0
fi
sleep 5
done
Here, we apply the remediation (through the patch
command) and probe
the cluster for status. Once the cluster converges, we exit the script
with 0
, which is a successful status.
The e2e test run will time out at 15 minuntes if a script doesn’t converge.
Note that the scripts will be run in parallel, but the test run will wait for all of them to be done.
Running the e2e tests on a local cluster
Note that it’s possible to run the e2e tests on a cluster of your choice.
To do so, ensure that you have a KUBECONFIG
with appropriate
credentials that points to the cluster where you’ll run the tests.
From the root of the ComplianceAsCode/content
repository, run:
$ make -f tests/ocp4e2e/Makefile e2e PROFILE=<profile> PRODUCT=<product>
Where profile is the name of the profile you want to test, and product
is a product relevant to OCP4
, such as ocp4
or rhcos4
.
For instance, to run the tests for the cis
benchmark for ocp4
do:
$ make -f tests/ocp4e2e/Makefile e2e PROFILE=cis PRODUCT=ocp4
For more information on the available options, do:
$ make -f tests/ocp4e2e/Makefile help
It is important to note that the tests will do changes to your cluster and there currently isn’t an option to clean them up. So take that into account before running these tests.
Contribution to infrastructure code
The ComplianceAsCode build and templating system is mostly written in Python.
Python
The common pattern is to dynamically add
ssg
to the import path. There are many useful modules with several functions and predefined constants. See scripts at./build-scripts
as an example of this practice.Follow the PEP8 standard.
Try to keep most of your lines length under 80 characters. Although the 99 character limit is within PEP8 requirements, there is no reason for most lines to be that long.