A Server-Side Template Injection (SSTI) vulnerability exists in the Frappe ERPNext through 15.89.0 Print Format rendering mechanism. Specifically, the API frappe.www.printview.get_html_and_style() triggers the rendering of the html field inside a Print Format document using frappe.render_template(template, doc) via the get_rendered_template() call chain. Although ERPNext wraps Jinja2 in a SandboxedEnvironment, it exposes sensitive functions such as frappe.db.sql through get_safe_globals(). An authenticated attacker with permission to create or modify a Print Format can inject arbitrary Jinja expressions into the html field. Once the malicious Print Format is saved, the attacker can call get_html_and_style() with a target document (e.g., Supplier or Sales Invoice) to trigger the render process. This leads to information disclosure from the database, such as database version, schema details, or sensitive values, depending on the injected payload. Exploitation flow: Create a Print Format with SSTI payload in the html field; call the get_html_and_style() API; triggers frappe.render_template(template, doc) inside get_rendered_template(); leaks database information via frappe.db.sql or other exposed globals.
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 |
|---|
| Erpnext | Frappe | * | 15.89.0 (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