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How the CVE Works:
The vulnerability (CVE-2025-XXXX) in llama_index v0.12.21 arises due to improper sanitization of user-supplied input in SQL queries across multiple vector store integrations. Attackers can craft malicious input that manipulates SQL queries executed by the library, leading to unauthorized data access or modification. Since llama_index is often used in web applications, this flaw could expose sensitive user data or allow privilege escalation. The lack of prepared statements or input validation in affected functions enables classic SQL injection attacks.
DailyCVE Form:
Platform: llama_index
Version: v0.12.21
Vulnerability: SQL Injection
Severity: Critical
Date: Jun 5, 2025
Prediction: Patch by Jun 20, 2025
What Undercode Say:
Exploitation:
1. Identify vulnerable endpoints using llama_index vector stores.
- Craft malicious SQL payloads like `’ OR 1=1 –` to bypass authentication.
- Exfiltrate data via UNION-based attacks or blind SQLi.
Protection:
1. Update immediately upon patch release.
2. Use parameterized queries to prevent injection.
3. Implement input validation via regex or allowlists.
Analytics:
- Affected functions:
VectorStoreQuery, `SQLDatabase` integrations. - Risk score: 9.8 (CVSS v3.1).
Commands:
Check installed version: pip show llama-index Mitigation workaround (temporary): sed -i 's/raw_query/parameterized_query/g' /path/to/llama_index/sql.py
Code Fix Example:
Vulnerable code:
cursor.execute(f"SELECT FROM vectors WHERE id = {user_input}")
Fixed code:
cursor.execute("SELECT FROM vectors WHERE id = ?", (user_input,))
Detection:
Log suspicious queries:
import re
if re.search(r"[\'\";]", user_input):
log.warning("Potential SQLi attempt detected.")
References:
- GitHub Advisory: GHSA-xxxx-xxxx-xxxx
- NVD: CVE-2025-XXXX
Sources:
Reported By: github.com
Extra Source Hub:
Undercode
