CVE-2026-33324: dataease SQLBot · SQL Injection
Affects dataease SQLBotSource CVE Database V5
Not known to be exploited · CVSS 9.4 Critical : upgrade to 1.7.1 as a priority.
Data as of 2 Nov 2026, 10:58 UTC
Contested
Critical score, yet low EPSS after six months- EPSS
- 0.6% chance of exploitation in 30 days – higher than 48% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 1.7.1
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:HExploitation evidence
Disclosed: evidence found.
CVE published 5 May 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: 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 2 Nov 2026.
What to do
Upgrade SQLBot and dataease/SQLBot to 1.7.1.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| dataeaseSQLBot | Affected
| Fixed in
|
GitHubdataease/SQLBotpkg:github/dataease/SQLBotOther threats | Affected
| Fixed in
|
Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.
AI-suggested
Upgrade SQLBot to version 1.7.1 or later, where this vulnerability is fixed. Since this is not a cloud service, remediation depends on applying the official patch. Patch status is not explicitly stated in the vendor advisory but the description confirms the issue is fixed in 1.7.1. No other mitigations are indicated.
Description
SQLBot is an intelligent Text-to-SQL system based on large language models and RAG. In versions 1.7.0 and earlier, the Text2SQL chat interface is vulnerable to prompt injection. The user-provided question parameter is directly concatenated into the LLM prompt without filtering or escaping, and the SQL extracted from the LLM response is executed against the database without validation or sanitization. An authenticated attacker can craft a malicious question to manipulate the LLM into generating and executing arbitrary SQL statements. When connected to a PostgreSQL data source, this can lead to remote code execution via COPY FROM PROGRAM. This issue has been fixed in version 1.7.1.