CVE-2026-104003

NVD	https://nvd.nist.gov/vuln/detail/CVE-2026-104003
CWE	https://cwe.mitre.org/data/definitions/94.html

The WP User Avatar / ProfilePress plugin for WordPress is vulnerable to Arbitrary Shortcode Execution in versions up to, and including, 4.17.5. This is due to the get_user_profile_structure() function assembling the front-end profile buffer — which includes raw comment excerpts inlined by author_comment_query() — and passing the entire buffer to do_shortcode() after only a narrow neutralization pass (ppress_neutralize_buffer_shortcodes) that blocks pp-custom-html and bracket fragments containing HTML delimiters but leaves any other well-formed shortcode intact. This makes it possible for authenticated attackers, with Subscriber-level access and above, to inject arbitrary shortcodes (from any active plugin or theme) with attacker-chosen attributes by posting a comment whose body contains the shortcode markup; the shortcode is then executed server-side when any visitor loads the targets front-end profile Comments tab, letting the attacker reach capability-gated or data-returning shortcodes and inject raw HTML markup into a publicly viewable page.

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.

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].

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

Weakness

Potential Mitigations

References

CVE-2026-104003

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

Weakness

Potential Mitigations

Related Attack Patterns

References