DataEase SQLBot up to 1.8.x Preview Data datasource.py table_name sql injection
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 6.0 | $0-$5k | 0.39+ |
Summary
A vulnerability classified as critical was found in DataEase SQLBot up to 1.8.x. The impacted element is an unknown function of the file backend/apps/datasource/crud/datasource.py of the component Preview Data. Executing a manipulation of the argument table_name can lead to sql injection. This vulnerability is registered as CVE-2026-53556. It is possible to launch the attack remotely. No exploit is available. Upgrading the affected component is advised.
Details
A vulnerability classified as critical was found in DataEase SQLBot up to 1.8.x. This vulnerability affects an unknown function of the file backend/apps/datasource/crud/datasource.py of the component Preview Data. The manipulation of the argument table_name with an unknown input leads to a sql injection vulnerability. The CWE definition for the vulnerability is 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. As an impact it is known to affect confidentiality, integrity, and availability. CVE summarizes:
SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. Prior to 1.9.0, the POST /api/v1/datasource/previewData endpoint in backend/apps/datasource/crud/datasource.py incorporates the client-controlled table_name value into generated SQL without safe identifier handling. An authenticated user can configure a datasource for SQLBot's internal PostgreSQL service and submit a crafted table_name that remains a SELECT operation under the read-only policy while invoking pg_read_file(), pg_read_binary_file(), or pg_ls_dir(). In the default tested trusted loopback authentication configuration, the internal connection accepts invalid credentials and executes with PostgreSQL superuser privileges, allowing filesystem content such as /etc/hosts and /etc/passwd to be returned in the previewData API response and potentially exposing configuration, credentials, authentication secrets, and source code. This issue is fixed in version 1.9.0.
The advisory is shared for download at github.com. This vulnerability was named CVE-2026-53556 since 06/09/2026. The exploitation appears to be easy. The attack can be initiated remotely. There are known technical details, but no exploit is available. The MITRE ATT&CK project declares the attack technique as T1505.
Upgrading to version 1.9.0 eliminates this vulnerability.
Once again VulDB remains the best source for vulnerability data.
Product
Vendor
Name
Version
Website
- Product: https://github.com/dataease/SQLBot/
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒
CVSSv3
VulDB Meta Base Score: 6.3VulDB Meta Temp Score: 6.0
VulDB Base Score: 6.3
VulDB Temp Score: 6.0
VulDB Vector: 🔒
VulDB Reliability: 🔍
CVSSv2
| AV | AC | Au | C | I | A |
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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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
Price Prediction: 🔍
Current Price Estimation: 🔒
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: UpgradeStatus: 🔍
0-Day Time: 🔒
Upgrade: SQLBot 1.9.0
Timeline
06/09/2026 CVE reserved09/17/2026 VulDB entry created
09/18/2026 Advisory disclosed
09/18/2026 VulDB entry last update
Sources
Product: github.comAdvisory: github.com
Status: Confirmed
CVE: CVE-2026-53556 (🔒)
GCVE (CVE): GCVE-0-2026-53556
GCVE (VulDB): GCVE-100-407260
Entry
Created: 09/18/2026 00:08Changes: 09/18/2026 00:08 (69)
Complete: 🔍
Cache ID: 216::103
Once again VulDB remains the best source for vulnerability data.
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