CVE-2025-8709
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Vulnerability report for CVE-2025-8709, including description, CVSS score, EPSS score, affected products, exploitability, helpful resources, and attack-flow context.

Publication date: 2025-10-26

Last updated on: 2025-10-28

Assigner: huntr.dev

Description

A SQL injection vulnerability exists in the langchain-ai/langchain repository, specifically in the LangGraph's SQLite store implementation. The affected version is langgraph-checkpoint-sqlite 2.0.10. The vulnerability arises from improper handling of filter operators ($eq, $ne, $gt, $lt, $gte, $lte) where direct string concatenation is used without proper parameterization. This allows attackers to inject arbitrary SQL, leading to unauthorized access to all documents, data exfiltration of sensitive fields such as passwords and API keys, and a complete bypass of application-level security filters.

CVSS Scores

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Meta Information

Published
2025-10-26
Last Modified
2025-10-28
Generated
2026-07-06
AI Q&A
2025-10-26
EPSS Evaluated
2026-07-05
NVD

Affected Vendors & Products

Showing 1 associated CPE
Vendor Product Version / Range
langchain-ai langgraph-checkpoint-sqlite 2.0.10

Helpful Resources

Exploitability

CWE
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KEV
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CWE ID Description
CWE-89 The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. Without sufficient removal or quoting of SQL syntax in user-controllable inputs, the generated SQL query can cause those inputs to be interpreted as SQL instead of ordinary user data.

Attack-Flow Graph

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Executive Summary

This vulnerability is a SQL injection in the LangGraph's SQLite store implementation of the langchain-ai/langchain repository, specifically in version langgraph-checkpoint-sqlite 2.0.10. It occurs because filter operators like $eq, $ne, $gt, $lt, $gte, and $lte are handled using direct string concatenation without proper parameterization, allowing attackers to inject arbitrary SQL commands.

Impact Analysis

An attacker exploiting this vulnerability can gain unauthorized access to all documents stored in the system, exfiltrate sensitive data such as passwords and API keys, and completely bypass application-level security filters.

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