Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2024-12909 is a critical-severity SQL Injection (CWE-89) vulnerability in Llamaindex Llamaindex. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 32% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2024-12909 is a SQL injection vulnerability in the `run_sql_query` function of the `database_agent` within the FinanceChatLlamaPack of the run-llama/llama_index repository. It affects versions up to v0.12.3 and enables attackers to inject arbitrary SQL queries, which can lead to remote code execution (RCE) through PostgreSQL's large object functionality. The vulnerability is classified under CWE-89 and carries a CVSS v3.1 base score of 9.8 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H), marking it as critical.
The vulnerability is exploitable remotely over the network by unauthenticated attackers with low attack complexity and no requirement for user interaction. Successful exploitation allows arbitrary SQL injection, culminating in RCE on the underlying PostgreSQL database server, potentially compromising the host system with high impacts on confidentiality, integrity, and availability.
Mitigation is provided in version 0.3.0 of the affected package. The fixing commit is documented at https://github.com/run-llama/llama_index/commit/5d03c175476452db9b8abcdb7d5767dd7b310a75, with additional details available on the Huntr bounty page at https://huntr.com/bounties/44e8177f-200a-4ba3-a12c-8bc21e313a3f. Security practitioners should upgrade to the patched version and review deployments using LlamaIndex for database-integrated LLM agents.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-6982
Vulnerability Data
A vulnerability in the FinanceChatLlamaPack of the run-llama/llama_index repository, versions up to v0.12.3, allows for SQL injection in the `run_sql_query` function of the `database_agent`. This vulnerability can be exploited by an attacker to inject arbitrary SQL queries, leading to remote…
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code execution (RCE) through the use of PostgreSQL's large object functionality. The issue is fixed in version 0.3.0.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V6.2.5
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover SQLi flaws before deployment but does not stop their introduction.
Input validation directly stops untrusted data from reaching SQL query construction without neutralization.
Secure engineering principles require parameterized queries and input sanitization that structurally eliminate SQLi.
System monitoring can identify attempted SQLi exploitation via anomalous queries after the weakness exists.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly target injection flaws during coding and review so largely prevent CWE-89 introduction, yet the single broad outcome leaves residual risk from incomplete neutralization techniques or missed edge cases.
Training raises developer awareness of SQLi risks and can reduce introduction likelihood (partial) but removes none of the actual coding flaw's risk by itself since technical neutralization is still required.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
The same secure-coding and static-analysis activities surface missing neutralization of SQL metacharacters before the system is accepted.
Early warnings and shared best-practice information help organizations apply the latest remediation techniques against SQL-injection vulnerabilities.
Threat-intelligence feeds that surface new SQL-injection campaigns enable rapid updates to query-construction defenses and detection signatures before exploitation occurs.
Secure-coding rules and security testing phases mandate the use of parameterized queries or equivalent escaping, preventing the construction of dynamic SQL statements from untrusted input.
Language-specific secure coding rules, peer review and SAST together prevent the construction of SQL statements from untrusted data without proper parameterization or escaping.