Python CVE-2026-32611

Summary

The GHSA-x46r fix (commit 39161f0) addressed SQL injection in the TimescaleDB export module by converting all SQL operations to use parameterized queries and psycopg.sql composable objects. However, the DuckDB export module (glances/exports/glances_duckdb/__init__.py) was not included in this fix and contains the same class of vulnerability: table names and column names derived from monitoring statistics are directly interpolated into SQL statements via f-strings. While DuckDB INSERT values already use parameterized queries (? placeholders), the DDL construction and table name references do not escape or parameterize identifier names.

Details

The DuckDB export module constructs SQL DDL statements by directly interpolating stat field names and plugin names into f-strings.

Vulnerable CREATE TABLE construction (glances/exports/glances_duckdb/__init__.py:156-162):

create_query = f"""
CREATE TABLE {plugin} (
{', '.join(creation_list)}
);"""
self.client.execute(create_query)

The creation_list is built from stat dictionary keys in the update() method (glances/exports/glances_duckdb/__init__.py:117-118):

for key, value in plugin_stats.items():
    creation_list.append(f"{key} {convert_types[type(self.normalize(value)).__name__]}")

The INSERT statement also uses the unescaped plugin name (glances/exports/glances_duckdb/__init__.py:172-174):

insert_query = f"""
INSERT INTO {plugin} VALUES (
{', '.join(['?' for _ in values])}
);"""

While INSERT values use ? placeholders (safe), the table name {plugin} is directly interpolated in both CREATE TABLE and INSERT INTO statements. Column names in creation_list are also directly interpolated without quoting.

Comparison with the TimescaleDB fix (commit 39161f0):

The TimescaleDB fix addressed this exact pattern by:

1. Using psycopg.sql.Identifier() for table and column names
2. Using psycopg.sql.SQL() for composing queries
3. Using %s placeholders for all values

The DuckDB module was not part of this fix despite having the same vulnerability class.

Attack vector:

The primary attack vector is through stat dictionary keys. While most keys come from hardcoded psutil field names (e.g., cpu_percent, memory_usage), any future plugin that introduces dynamic keys from external data (container labels, custom metrics, user-defined sensor names) would create an exploitable injection path. Additionally, the table name (plugin) comes from the internal plugins list, but any custom plugin with a crafted name could inject SQL.

PoC

The injection is demonstrable when column or table names contain SQL metacharacters:

# Simulated injection via a hypothetical plugin with dynamic keys
# If a stat dict contained a key like:
#   "cpu_percent BIGINT); DROP TABLE cpu; --"
# The creation_list would produce:
#   "cpu_percent BIGINT); DROP TABLE cpu; -- VARCHAR"
# Which in the CREATE TABLE f-string becomes:
#   CREATE TABLE plugin_name (
#     time TIMETZ,
#     hostname_id VARCHAR,
#     cpu_percent BIGINT); DROP TABLE cpu; -- VARCHAR
#   );

# Verify with DuckDB export enabled:
# 1. Configure DuckDB export in glances.conf:
# [duckdb]
# database=/tmp/glances.duckdb
# 2. Start Glances with DuckDB export and debug logging
glances --export duckdb --debug 2>&1 | grep "Create table"
# 3. Observe the unescaped SQL in debug output

Impact

• Defense-in-depth gap: The identical vulnerability pattern was identified and fixed in TimescaleDB (GHSA-x46r) but the fix was not applied to the sibling DuckDB module. This represents an incomplete patch that leaves the same attack surface open through a different code path.
• Future exploitability: If any Glances plugin is added or modified to produce stat dictionary keys from external/user-controlled data (e.g., container metadata, custom metric names, SNMP OID labels), the DuckDB export would become immediately exploitable for SQL injection without any additional code changes.
• Data integrity: A successful injection in the CREATE TABLE statement could corrupt the DuckDB database, create unauthorized tables, or modify schema in ways that affect other applications reading from the same database file.

Recommended Fix

Apply the same parameterization approach used in the TimescaleDB fix. DuckDB supports identifier quoting with double quotes:

# glances/exports/glances_duckdb/__init__.py

def _quote_identifier(name):
    """Quote a SQL identifier to prevent injection."""
# DuckDB uses double-quote escaping for identifiers
    return '"' + name.replace('"', '""') + '"'

def export(self, plugin, creation_list, values_list):
    """Export the stats to the DuckDB server."""
    logger.debug(f"Export {plugin} stats to DuckDB")

    table_list = [t[0] for t in self.client.sql("SHOW TABLES").fetchall()]
    if plugin not in table_list:
# Quote table and column names to prevent injection
        quoted_plugin = _quote_identifier(plugin)
        quoted_fields = []
        for item in creation_list:
            parts = item.split(' ', 1)
            col_name = _quote_identifier(parts[0])
            col_type = parts[1] if len(parts) > 1 else 'VARCHAR'
            quoted_fields.append(f"{col_name} {col_type}")

        create_query = f"CREATE TABLE {quoted_plugin} ({', '.join(quoted_fields)});"
        try:
            self.client.execute(create_query)
        except Exception as e:
            logger.error(f"Cannot create table {plugin}: {e}")
            return

    self.client.commit()
# Insert with quoted table name
    quoted_plugin = _quote_identifier(plugin)
    for values in values_list:
        insert_query = f"INSERT INTO {quoted_plugin} VALUES ({', '.join(['?' for _ in values])});"
        try:
            self.client.execute(insert_query, values)
        except Exception as e:
            logger.error(f"Cannot insert data into table {plugin}: {e}")

    self.client.commit()