CVE-2023-25657

Nautobot is a Network Source of Truth and Network Automation Platform. All users of Nautobot versions earlier than 1.5.7 are impacted by a remote code execution vulnerability. Nautobot did not properly sandbox Jinja2 template rendering. In Nautobot 1.5.7 has enabled sandboxed environments for the Jinja2 template engine used internally for template rendering for the following objects: extras.ComputedField, extras.CustomLink, extras.ExportTemplate, extras.Secret, extras.Webhook. While no active exploits of this vulnerability are known this change has been made as a preventative measure to protect against any potential remote code execution attacks utilizing maliciously crafted template code. This change forces the Jinja2 template engine to use a SandboxedEnvironment on all new installations of Nautobot. This addresses any potential unsafe code execution everywhere the helper function nautobot.utilities.utils.render_jinja2 is called. Additionally, the documentation that had previously suggesting the direct use of jinja2.Template has been revised to suggest render_jinja2. Users are advised to upgrade to Nautobot 1.5.7 or newer. For users that are unable to upgrade to the latest release of Nautobot, you may add the following setting to your nautobot_config.py to apply the sandbox environment enforcement: TEMPLATES[1][OPTIONS][environment] = jinja2.sandbox.SandboxedEnvironment After applying this change, you must restart all Nautobot services, including any Celery worker processes. Note: Nautobot specifies two template engines by default, the first being “django” for the Django built-in template engine, and the second being “jinja” for the Jinja2 template engine. This recommended setting will update the second item in the list of template engines, which is the Jinja2 engine. For users that are unable to immediately update their configuration such as if a Nautobot service restart is too disruptive to operations, access to provide custom Jinja2 template values may be mitigated using permissions to restrict “change” (write) actions to the affected object types listed in the first section. Note: This solution is intended to be stopgap until you can successfully update your nautobot_config.py or upgrade your Nautobot instance to apply the sandboxed environment enforcement.

Weakness

The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.

Affected Software

Extended Description

When a product allows a user’s input to contain code syntax, it might be possible for an attacker to craft the code in such a way that it will alter the intended control flow of the product. Such an alteration could lead to arbitrary code execution. Injection problems encompass a wide variety of issues – all mitigated in very different ways. For this reason, the most effective way to discuss these weaknesses is to note the distinct features which classify them as injection weaknesses. The most important issue to note is that all injection problems share one thing in common – i.e., they allow for the injection of control plane data into the user-controlled data plane. This means that the execution of the process may be altered by sending code in through legitimate data channels, using no other mechanism. While buffer overflows, and many other flaws, involve the use of some further issue to gain execution, injection problems need only for the data to be parsed. The most classic instantiations of this category of weakness are SQL injection and format string vulnerabilities.

Potential Mitigations

• Run your code in a “jail” or similar sandbox environment that enforces strict boundaries between the process and the operating system. This may effectively restrict which code can be executed by your product.
• Examples include the Unix chroot jail and AppArmor. In general, managed code may provide some protection.
• This may not be a feasible solution, and it only limits the impact to the operating system; the rest of your application may still be subject to compromise.
• Be careful to avoid CWE-243 and other weaknesses related to jails.
• Assume all input is malicious. Use an “accept known good” input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
• When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, “boat” may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as “red” or “blue.”
• Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code’s environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
• To reduce the likelihood of code injection, use stringent allowlists that limit which constructs are allowed. If you are dynamically constructing code that invokes a function, then verifying that the input is alphanumeric might be insufficient. An attacker might still be able to reference a dangerous function that you did not intend to allow, such as system(), exec(), or exit().

Related Attack Patterns

• https://cwe.mitre.org/data/definitions/242.html
• https://cwe.mitre.org/data/definitions/35.html
• https://cwe.mitre.org/data/definitions/77.html

References

• https://github.com/nautobot/nautobot/commit/d47f157e83b0c353bb2b697f911882c71cf90ca0
• https://github.com/nautobot/nautobot/security/advisories/GHSA-8mfq-f5wj-vw5m
• https://jinja.palletsprojects.com/en/3.0.x/sandbox/#sandbox
• https://github.com/nautobot/nautobot/commit/d47f157e83b0c353bb2b697f911882c71cf90ca0
• https://github.com/nautobot/nautobot/security/advisories/GHSA-8mfq-f5wj-vw5m
• https://jinja.palletsprojects.com/en/3.0.x/sandbox/#sandbox