CVE Vulnerabilities

CVE-2021-21480

Improper Control of Generation of Code ('Code Injection')

Published: Mar 09, 2021 | Modified: May 05, 2025
CVSS 3.x
8.8
HIGH
Source:
NVD
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVSS 2.x
9 HIGH
AV:N/AC:L/Au:S/C:C/I:C/A:C
RedHat/V2
RedHat/V3
Ubuntu

SAP MII allows users to create dashboards and save them as JSP through the SSCE (Self Service Composition Environment). An attacker can intercept a request to the server, inject malicious JSP code in the request and forward to server. When this dashboard is opened by users having at least SAP_XMII Developer role, malicious content in the dashboard gets executed, leading to remote code execution in the server, which allows privilege escalation. The malicious JSP code can contain certain OS commands, through which an attacker can read sensitive files in the server, modify files or even delete contents in the server thus compromising the confidentiality, integrity and availability of the server hosting the SAP MII application. Also, an attacker authenticated as a developer can use the application to upload and execute a file which will permit them to execute operating systems commands completely compromising the server hosting the application.

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

Name Vendor Start Version End Version
Manufacturing_integration_and_intelligence Sap 15.1 (including) 15.1 (including)
Manufacturing_integration_and_intelligence Sap 15.2 (including) 15.2 (including)
Manufacturing_integration_and_intelligence Sap 15.3 (including) 15.3 (including)
Manufacturing_integration_and_intelligence Sap 15.4 (including) 15.4 (including)

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().
  • For Python programs, it is frequently encouraged to use the ast.literal_eval() function instead of eval, since it is intentionally designed to avoid executing code. However, an adversary could still cause excessive memory or stack consumption via deeply nested structures [REF-1372], so the python documentation discourages use of ast.literal_eval() on untrusted data [REF-1373].

References