CVE-2024-8309VulnerabilityPublished 29 Oct 2024Updated 15 Oct 2025

CVE-2024-8309: langchain-ai/langchain · Improper Neutralization of Special Elements used in an SQL Command

Affects langchain-ai/langchainSource CVE Database V5

Not known to be exploited · 13% EPSS · CVSS 4.9 Medium.

Data as of 26 Oct 2026, 06:26 UTC

CVSS 3.0 base score

4.9Medium

How severe the flaw is on the 0–10 CVSS scale.

EPSS: 13.7% chance of exploitation in 30 days – higher than 96% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

CVSS:3.0/AV:L/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:L

Attack Vector: Local
Attack Complexity: High
Privileges Required: None
User Interaction: None
Scope: Unchanged
Confidentiality: Low
Integrity: Low
Availability: Low

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Local: The vulnerable component is not bound to the network stack and the attacker’s path is via read/write/execute capabilities. Either: the attacker exploits the vulnerability by accessing the target system locally (e.g., keyboard, console), or remotely (e.g., SSH); or the attacker relies on User Interaction by another person to perform actions required to exploit the vulnerability (e.g., tricking a legitimate user into opening a malicious document).
Attack Complexity: High: A successful attack depends on conditions beyond the attacker's control. That is, a successful attack cannot be accomplished at will, but requires the attacker to invest in some measurable amount of effort in preparation or execution against the vulnerable component before a successful attack can be expected. For example, a successful attack may require an attacker to: gather knowledge about the environment in which the vulnerable target/component exists; prepare the target environment to improve exploit reliability; or inject themselves into the logical network path between the target and the resource requested by the victim in order to read and/or modify network communications (e.g., a man in the middle attack).
Privileges Required: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files to carry out an attack.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: Low: There is some loss of confidentiality. Access to some restricted information is obtained, but the attacker does not have control over what information is obtained, or the amount or kind of loss is limited. The information disclosure does not cause a direct, serious loss to the impacted component.
Integrity: Low: Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact on the impacted component.
Availability: Low: Performance is reduced or there are interruptions in resource availability. Even if repeated exploitation of the vulnerability is possible, the attacker does not have the ability to completely deny service to legitimate users. The resources in the impacted component are either partially available all of the time, or fully available only some of the time, but overall there is no direct, serious consequence to the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 29 Oct 2024
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-26.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Affected software

Product	Affected	Fixed in
PyPIlangchain-ai/langchain`pkg:pypi/langchain-ai/langchain`Other threats	Affected =0.2.5	Fixed in–

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AI-suggested

1. Implement strict input validation and sanitization on all prompts and inputs to the GraphCypherQAChain to prevent injection of malicious SQL commands. 2. Employ parameterized queries or prepared statements within the langchain-ai/langchain codebase to avoid direct concatenation of user inputs into SQL commands. 3. Isolate database access privileges, ensuring the application runs with least privilege necessary to limit the impact of any injection. 4. Monitor database logs and application behavior for anomalous queries or unexpected data modifications indicative of exploitation attempts. 5. Use runtime application self-protection (RASP) or web application firewalls (WAF) configured to detect and block SQL injection patterns. 6. Segregate multi-tenant data strictly to prevent cross-tenant data leakage. 7. Stay updated on vendor patches or advisories and apply them promptly once available. 8. Conduct security code reviews and penetration testing focusing on prompt injection vectors in AI workflows.

Description

A vulnerability in the GraphCypherQAChain class of langchain-ai/langchain version 0.2.5 allows for SQL injection through prompt injection. This vulnerability can lead to unauthorized data manipulation, data exfiltration, denial of service (DoS) by deleting all data, breaches in multi-tenant security environments, and data integrity issues. Attackers can create, update, or delete nodes and relationships without proper authorization, extract sensitive data, disrupt services, access data across different tenants, and compromise the integrity of the database.

Impact

For European organizations, the impact includes potential unauthorized access to sensitive data, disruption of AI-driven services, and compromise of multi-tenant environments common in cloud deployments. Data exfiltration risks threaten compliance with GDPR and other data protection regulations, potentially leading to legal and financial penalties. Integrity violations can undermine trust in AI outputs and decision-making processes. Denial of service through data deletion can cause operational downtime and loss of critical information. Organizations using langchain-ai/langchain in sectors like finance, healthcare, or government are particularly vulnerable due to the sensitivity of their data and regulatory requirements. The medium severity score suggests exploitation is not trivial but feasible, especially by skilled insiders or attackers with local access.

Summary

CVE-2024-8309 is an SQL injection vulnerability classified under CWE-89, found in the GraphCypherQAChain class of the langchain-ai/langchain library version 0.2.5. This vulnerability arises from improper neutralization of special elements in SQL commands, specifically via prompt injection vectors. Attackers can craft malicious prompts that manipulate the underlying SQL queries executed by the GraphCypherQAChain, enabling unauthorized creation, modification, or deletion of nodes and relationships within the database. This can lead to unauthorized data exfiltration, data integrity violations, denial of service through mass deletion, and breaches in multi-tenant environments where data isolation is critical. The CVSS 3.0 score is 4.9 (medium), reflecting local attack vector and high attack complexity, but no privileges or user interaction required. The vulnerability affects confidentiality, integrity, and availability of data managed by langchain-ai/langchain, especially in AI applications leveraging graph databases. No patches or known exploits are currently available, but the risk is significant given the potential for data compromise and service disruption.

CWE-89Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') (opens in a new tab)
Base weaknessLikelihood of exploit: HighCWE Top 25 (2025): #2OWASP Top 10 A05:2025: Injection (opens in a new tab)
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.
Architecture and Design · Libraries or Frameworks
Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.
Architecture and Design · Parameterization
If available, use structured mechanisms that automatically enforce the separation between data and code. These mechanisms may be able to provide the relevant quoting, encoding, and validation automatically, instead of relying on the developer to provide this capability at every point where output is generated.
Architecture and Design · Operation · Environment Hardening
Run your code using the lowest privileges that are required to accomplish the necessary tasks. If possible, create isolated accounts with limited privileges that are only used for a single task. That way, a successful attack will not immediately give the attacker access to the rest of the software or its environment.
OWASP Cheat Sheets
Query Parameterization (opens in a new tab)
Unvalidated Redirects and Forwards (opens in a new tab)
XML Security (opens in a new tab)
XML External Entity Prevention (opens in a new tab)
File Upload (opens in a new tab)
OWASP ASVS 4.0.3
V5.3.4 (opens in a new tab)
V5.3.5 (opens in a new tab)
V1.5.1 (opens in a new tab)
Attack patterns
Command Line Execution through SQL Injection (opens in a new tab)
Object Relational Mapping Injection (opens in a new tab)
SQL Injection through SOAP Parameter Tampering (opens in a new tab)
Expanding Control over the Operating System from the Database (opens in a new tab)
SQL Injection (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 15 Oct 2025, 13:20 UTC

WeaknessesCWE-89

Technical details

References

Community reviews

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