Flowise up to 2.2.3 Postgres_VectorStores tableName sql injection
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 6.3 | $0-$5k | 0.00 |
Summary
A vulnerability was found in Flowise up to 2.2.3. It has been rated as critical. This impacts the function Postgres_VectorStores. The manipulation of the argument tableName leads to sql injection.
This vulnerability is referenced as CVE-2025-29189. Remote exploitation of the attack is possible. No exploit is available.
Details
A vulnerability was found in Flowise up to 2.2.3 and classified as critical. This issue affects the function Postgres_VectorStores. The manipulation of the argument tableName with an unknown input leads to a sql injection vulnerability. Using CWE to declare the problem leads to 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. Impacted is confidentiality, integrity, and availability. The summary by CVE is:
Flowise <= 2.2.3 is vulnerable to SQL Injection. via tableName parameter at Postgres_VectorStores.
It is possible to read the advisory at drive.google.com. The identification of this vulnerability is CVE-2025-29189 since 03/11/2025. The exploitation is known to be easy. The attack may be initiated remotely. Technical details of the vulnerability are known, but there is no available exploit. The pricing for an exploit might be around USD $0-$5k at the moment (estimation calculated on 05/24/2025). The attack technique deployed by this issue is T1505 according to MITRE ATT&CK.
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
The vulnerability is also documented in the vulnerability database at EUVD (EUVD-2025-10669). Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Name
Version
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔍VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 6.3VulDB Meta Temp Score: 6.3
VulDB Base Score: 6.3
VulDB Temp Score: 6.3
VulDB Vector: 🔍
VulDB Reliability: 🔍
CVSSv2
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍
Exploiting
Class: Sql injectionCWE: CWE-89 / CWE-74 / CWE-707
CAPEC: 🔍
ATT&CK: 🔍
Physical: No
Local: No
Remote: Yes
Availability: 🔍
Status: Not defined
EPSS Score: 🔍
EPSS Percentile: 🔍
Price Prediction: 🔍
Current Price Estimation: 🔍
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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| Today | Unlock | Unlock | Unlock | Unlock |
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔍
Timeline
03/11/2025 🔍04/09/2025 🔍
04/09/2025 🔍
05/24/2025 🔍
Sources
Advisory: drive.google.comStatus: Not defined
CVE: CVE-2025-29189 (🔍)
GCVE (CVE): GCVE-0-2025-29189
GCVE (VulDB): GCVE-100-304115
EUVD: 🔍
Entry
Created: 04/09/2025 14:03Updated: 05/24/2025 17:05
Changes: 04/09/2025 14:03 (53), 05/24/2025 17:05 (1)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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