CVE-2026-32611
Glances is an open-source system cross-platform monitoring tool.
Executive Summary
CVE-2026-32611 is a high severity vulnerability affecting appsec, ai-code. It is classified as SQL Injection. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.
Precogs AI Insight
"The root cause of this vulnerability lies in within Glances, allowing an architectural oversight in input validation. This flaw provides a direct pathway for attackers to trigger a denial of service state, crashing critical operational components. Precogs AI Analysis Engine leverages inter-procedural taint tracking to block malicious interactions before they reach production."
What is this vulnerability?
CVE-2026-32611 is categorized as a critical SQL Injection flaw. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.
Glances is an open-source system cross-platform monitoring tool. The GHSA-x46r fix (commit 39161f0) addressed SQL injection in the TimescaleDB export modul...
This architectural defect enables adversaries to bypass intended security controls, directly manipulating the application's execution state or data layer. Immediate strategic intervention is required.
Risk Assessment
| Metric | Value |
|---|---|
| CVSS Base Score | 7 (HIGH) |
| Vector String | CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:L/A:L |
| Published | March 18, 2026 |
| Last Modified | March 19, 2026 |
| Related CWEs | CWE-89 |
Impact on Systems
✅ Data Exfiltration: Full compromise of the database schema, allowing extraction of all tables, user records, and PII.
✅ Authentication Bypass: Attackers can manipulate boolean logic in authentication queries to log in as administrators.
✅ Remote Code Execution: In severe configurations (e.g., xp_cmdshell in MSSQL), attackers can execute shell commands on the database underlying OS.
How to fix this issue?
Implement the following strategic mitigations immediately to eliminate the attack surface.
1. Prepared Statements Migrate entirely to parameterized queries (Prepared Statements) or an Object-Relational Mapper (ORM) to decouple code from data.
2. Input Validation Implement rigorous allow-list input validation for all sorting, filtering, and query parameters.
3. Principle of Least Privilege Ensure the database service account has the minimum necessary privileges, restricting DROP, TRUNCATE, and system execution commands.
Vulnerability Signature
// Example of a vulnerable Node.js/Express snippet
const category = req.query.category;
// DANGEROUS: Direct string concatenation of user input
const query = `SELECT * FROM products WHERE category = '$\{category\}'`;
db.query(query, (err, result) =\> \{
if (err) throw err;
console.log(result);
\});
// SECURED: Using parameterized queries avoids SQL injection
const category = req.query.category; // Ensure scope appropriately
// Safe: The database driver treats '?' strictly as data, not executable code
const query = 'SELECT * FROM products WHERE category = ?';
db.query(query, [category], (err, result) =\> \{
if (err) throw err;
console.log(result);
\});
References and Sources
- NVD — CVE-2026-32611
- MITRE — CVE-2026-32611
- CWE-89 — MITRE CWE
- CWE-89 Details
- Application Security Vulnerabilities
- AI Code Security Vulnerabilities
Vulnerability Code Signature
Attack Data Flow
| Stage | Detail |
|---|---|
| Source | User-controlled HTTP request parameter |
| Vector | String concatenation into SQL query string |
| Sink | Database engine executes the malformed query |
| Impact | Full database compromise, unauthorized data modification or exfiltration |
Vulnerable Code Pattern
# ❌ VULNERABLE: Direct string concatenation
def get_user(user_id):
query = "SELECT * FROM users WHERE id = '" + user_id + "'"
cursor.execute(query) # Taint sink: unparameterized query
return cursor.fetchone()
Secure Code Pattern
# ✅ SECURE: Parameterized query
def get_user(user_id):
query = "SELECT * FROM users WHERE id = %s"
cursor.execute(query, (user_id,)) # Sanitized binding
return cursor.fetchone()
How Precogs Detects This
Precogs AI Analysis Engine traces data flow from HTTP request parameters through string concatenation directly into database execution sinks, identifying critical SQL injection vectors via Code Property Graph traversal.\n