CVE-2021-32829

ZStack is open source IaaS(infrastructure as a service) software aiming to automate datacenters, managing resources of compute, storage, and networking all by APIs. Affected versions of ZStack REST API are vulnerable to post-authentication Remote Code Execution (RCE) via bypass of the Groovy shell sandbox. The REST API exposes the GET zstack/v1/batch-queries?script endpoint which is backed up by the BatchQueryAction class. Messages are represented by the APIBatchQueryMsg, dispatched to the QueryFacadeImpl facade and handled by the BatchQuery class. The HTTP request parameter script is mapped to the APIBatchQueryMsg.script property and evaluated as a Groovy script in BatchQuery.query the evaluation of the user-controlled Groovy script is sandboxed by SandboxTransformer which will apply the restrictions defined in the registered (sandbox.register()) GroovyInterceptor. Even though the sandbox heavily restricts the receiver types to a small set of allowed types, the sandbox is non effective at controlling any code placed in Java annotations and therefore vulnerable to meta-programming escapes. This issue leads to post-authenticated remote code execution. For more details see the referenced GHSL-2021-065. This issue is patched in versions 3.8.21, 3.10.8, and 4.1.0.

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://blog.orange.tw/2019/02/abusing-meta-programming-for-unauthenticated-rce.html
• https://github.com/zstackio/zstack/security/advisories/GHSA-6xgq-7rqg-x3q5
• https://securitylab.github.com/advisories/GHSL-2021-065-zstack/
• https://blog.orange.tw/2019/02/abusing-meta-programming-for-unauthenticated-rce.html
• https://github.com/zstackio/zstack/security/advisories/GHSA-6xgq-7rqg-x3q5
• https://securitylab.github.com/advisories/GHSL-2021-065-zstack/