CVE-2017-18342
Description
From CVE.org
In PyYAML before 5.1, the yaml.load() API could execute arbitrary code if used with untrusted data. The load() function has been deprecated in version 5.1 and the 'UnsafeLoader' has been introduced for backward compatibility with the function.
Statement
The default loading mechanism in PyYAML contains fundamental and long-standing functionality that allows for arbitrary code execution.
The yaml.load() function (when called without a specified loader), has been documented as inherently unsafe since its first release. When processing YAML input, this function can call any Python function, including those that execute system commands (i.e., os.system()).
In response, the PyYAML maintainers have deprecated the plain use of yaml.load() to encourage developers to explicitly choose a safer option. The yaml.safe_load() function is the intended replacement. It handles a safe subset of the YAML language and disables the dangerous features that permit arbitrary code execution, effectively neutralizing the RCE threat from untrusted input.
However, to maintain backwards compatibility the yaml.load() function remains available. Its default behavior (as of PyYAML 5.1) was to use FullLoader and issue a warning. FullLoader was deemed not safe for untrusted data, and as of PyYAML 6.0 yaml.load() requires an explicit Loader argument. The original vulnerable loader is also retained (again, in the interest of backwards compatibility) which provides the attack vector.
The code executed via PyYAML runs as the user invoking the python binary calling the pyyaml module– there is no inherent privilege escalation. Therefore any exploit affecting any substantial impact requires privilege escalation via a separate vulnerability or poor application design and/or poor coding practices.
Given that the vulnerability in PyYAML’s load function provides a mechanism for threat actors to potentially impact a system via a wide range of Python functions, Red Hat must err on the side of caution and view the possible impact to Confidentiality, Integrity, and Availability as High.
Mitigation
Any codebases written in Python and employing the PyYAML library should be audited. Developers should replace every instance of the deprecated yaml.load() function with the secure alternative, yaml.safe_load(), especially when handling configuration or data from untrusted sources. Any applications invoking python where PyYAML is available should run as a non-privileged user.
Common Vulnerability Scoring System (CVSS) Score Details
Info alert:Important note
CVSS scores for open source components depend on vendor-specific factors (e.g. version or build chain). Therefore, Red Hat's score and impact rating can be different from NVD and other vendors. Red Hat remains the authoritative CVE Naming Authority (CNA) source for its products and services (see Red Hat classifications).
The following CVSS metrics and score provided are preliminary and subject to review.
CVSS v3 Score Breakdown
| Red Hat | NVD | cve.org | |
|---|---|---|---|
| Base Score | 9.8 | 9.8 | N/A |
| Attack Vector | Network | Network | N/A |
| Attack Complexity | Low | Low | N/A |
| Privileges Required | None | None | N/A |
| User Interaction | None | None | N/A |
| Scope | Unchanged | Unchanged | N/A |
| Confidentiality | High | High | N/A |
| Integrity Impact | High | High | N/A |
| Availability Impact | High | High | N/A |
Vector
Red Hat: CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
NVD: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
Understanding the Weakness (CWE)
Availability
Technical Impact: DoS: Crash, Exit, or Restart; DoS: Resource Consumption (CPU); DoS: Resource Consumption (Memory)
An attacker could provide unexpected values and cause a program crash or arbitrary control of resource allocation, leading to excessive consumption of resources such as memory and CPU.
Confidentiality
Technical Impact: Read Memory; Read Files or Directories
An attacker could read confidential data if they are able to control resource references.
Integrity,Confidentiality,Availability
Technical Impact: Modify Memory; Execute Unauthorized Code or Commands
An attacker could use malicious input to modify data or possibly alter control flow in unexpected ways, including arbitrary command execution.
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