CVE-2026-12044

NVD	https://nvd.nist.gov/vuln/detail/CVE-2026-12044
CWE	https://cwe.mitre.org/data/definitions/89.html

SQL injection in pgAdmin 4 across every dialog template that renders COMMENT ON ... IS <description> for a user-supplied description field. The Jinja templates for Domains (and their constraints), Foreign Tables, Languages, and Event Triggers, plus the Views OID-lookup query, interpolated the description directly inside a single-quoted SQL literal – {{ data.description }} – instead of passing it through the qtLiteral escape filter. An authenticated pgAdmin user with permission to create or alter the affected object types could submit a description containing an apostrophe, break out of the literal and chain arbitrary SQL. The injected SQL runs under the PostgreSQL role the user is already authenticated as; for a connected role with COPY ... TO/FROM PROGRAM (typically PostgreSQL superuser), this chains to OS command execution on the PostgreSQL host. The defect does not cross a privilege boundary – the user already has direct SQL access to that role through pgAdmins Query Tool – so the attacker gains no capability beyond what their database role already grants. The marginal impact captures bypass of any application-layer Query Tool gating an operator may have configured.

The defect was originally reported against the Domain Dialog description field; a code-wide audit identified sixteen sites of the same pattern across the templates listed above. The same review also surfaced ten related sinks in the pgstattuple/pgstatindex stats templates – pgstattuple({{schema}}.{{table}}) and the matching pgstatindex shape – where qtIdent escapes embedded double quotes inside the identifier but not apostrophes, so a user with CREATE privilege on a schema could plant a table or index named foobar and a later stats viewer would render an unbalanced literal.

Fix is layered:

Sites: replace every {{ x.description }} with {{ x.description|qtLiteral(conn) }} (no surrounding quotes – the filter wraps the value in escaped quotes itself). Plumb conn=self.conn through every render_template call that loads one of these templates. Also corrects a { % elif Jinja typo in the foreign-table schema diff (dead branch). Rewrite the ten pgstattuple/pgstatindex stats sites to address the relation via OID + ::oid::regclass cast (e.g. pgstattuple({{ tid }}::oid::regclass)), eliminating the embedded literal-call form entirely so that bug-class can no longer recur there.
Driver hardening: qtLiteral (in utils/driver/psycopg3/__init__.py) used to silently return the raw unescaped value when its conn argument was falsy. It now raises ValueError – surfacing the entire bug class going forward. The change immediately uncovered eight latent plumbing bugs (in schemas/__init__.py, schemas/functions/__init__.py, schemas/tables/utils.py, foreign_servers/__init__.py, and seven sites in roles/__init__.py) – all fixed as part of this patch. The inner except block that swallowed adapter-level failures and returned the raw value is also removed, so unadaptable inputs raise instead of leaking unescaped values.
Regression tests: a per-template behavioural test renders each previously-vulnerable template with an apostrophe-injection payload and asserts the escaped fragment is present and the vulnerable fragment absent; a lint test walks every *.sql template flagging any {{ ... }} single-quote-wrapped interpolation against an explicit allowlist; unit tests cover the new qtLiteral fail-fast and inner-except raise paths.

This issue affects pgAdmin 4: from 1.0 before 9.16.

Weakness

The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. Without sufficient removal or quoting of SQL syntax in user-controllable inputs, the generated SQL query can cause those inputs to be interpreted as SQL instead of ordinary user data.

Potential Mitigations

Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid [REF-1482].
For example, consider using persistence layers such as Hibernate or Enterprise Java Beans, which can provide significant protection against SQL injection if used properly.
If available, use structured mechanisms that automatically enforce the separation between data and code. These mechanisms may be able to provide the relevant quoting, encoding, and validation automatically, instead of relying on the developer to provide this capability at every point where output is generated.
Process SQL queries using prepared statements, parameterized queries, or stored procedures. These features should accept parameters or variables and support strong typing. Do not dynamically construct and execute query strings within these features using “exec” or similar functionality, since this may re-introduce the possibility of SQL injection. [REF-867]
Run your code using the lowest privileges that are required to accomplish the necessary tasks [REF-76]. If possible, create isolated accounts with limited privileges that are only used for a single task. That way, a successful attack will not immediately give the attacker access to the rest of the software or its environment. For example, database applications rarely need to run as the database administrator, especially in day-to-day operations.
Specifically, follow the principle of least privilege when creating user accounts to a SQL database. The database users should only have the minimum privileges necessary to use their account. If the requirements of the system indicate that a user can read and modify their own data, then limit their privileges so they cannot read/write others’ data. Use the strictest permissions possible on all database objects, such as execute-only for stored procedures.
While it is risky to use dynamically-generated query strings, code, or commands that mix control and data together, sometimes it may be unavoidable. Properly quote arguments and escape any special characters within those arguments. The most conservative approach is to escape or filter all characters that do not pass an extremely strict allowlist (such as everything that is not alphanumeric or white space). If some special characters are still needed, such as white space, wrap each argument in quotes after the escaping/filtering step. Be careful of argument injection (CWE-88).
Instead of building a new implementation, such features may be available in the database or programming language. For example, the Oracle DBMS_ASSERT package can check or enforce that parameters have certain properties that make them less vulnerable to SQL injection. For MySQL, the mysql_real_escape_string() API function is available in both C and PHP.
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.
When constructing SQL query strings, use stringent allowlists that limit the character set based on the expected value of the parameter in the request. This will indirectly limit the scope of an attack, but this technique is less important than proper output encoding and escaping.
Note that proper output encoding, escaping, and quoting is the most effective solution for preventing SQL injection, although input validation may provide some defense-in-depth. This is because it effectively limits what will appear in output. Input validation will not always prevent SQL injection, especially if you are required to support free-form text fields that could contain arbitrary characters. For example, the name “O’Reilly” would likely pass the validation step, since it is a common last name in the English language. However, it cannot be directly inserted into the database because it contains the “’” apostrophe character, which would need to be escaped or otherwise handled. In this case, stripping the apostrophe might reduce the risk of SQL injection, but it would produce incorrect behavior because the wrong name would be recorded.
When feasible, it may be safest to disallow meta-characters entirely, instead of escaping them. This will provide some defense in depth. After the data is entered into the database, later processes may neglect to escape meta-characters before use, and you may not have control over those processes.
Ensure that error messages only contain minimal details that are useful to the intended audience and no one else. The messages need to strike the balance between being too cryptic (which can confuse users) or being too detailed (which may reveal more than intended). The messages should not reveal the methods that were used to determine the error. Attackers can use detailed information to refine or optimize their original attack, thereby increasing their chances of success.
If errors must be captured in some detail, record them in log messages, but consider what could occur if the log messages can be viewed by attackers. Highly sensitive information such as passwords should never be saved to log files.
Avoid inconsistent messaging that might accidentally tip off an attacker about internal state, such as whether a user account exists or not.
In the context of SQL Injection, error messages revealing the structure of a SQL query can help attackers tailor successful attack strings.

Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')

Weakness

Potential Mitigations

References

CVE-2026-12044

Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')

Weakness

Potential Mitigations

Related Attack Patterns

References