VulnerabilityPublished 19 Mar 2026Updated 24 Mar 2026

CVE-2026-32622: dataease SQLBot · Missing Authorization

Affects dataease SQLBotSource CVE Database V5

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Not known to be exploited · CVSS 8.6 High : upgrade to 1.6.0 soon.

Data as of 31 Oct 2026, 20:20 UTC

CVSS 4.0 base score

8.6High

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

EPSS: 0.5% chance of exploitation in 30 days – higher than 47% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in 1.6.0

CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N

Attack Vector: Network
Attack Complexity: Low
Attack Requirements: None
Privileges Required: Low
User Interaction: None
Vulnerable system confidentiality: High
Vulnerable system integrity: High
Vulnerable system availability: None
Subsequent system confidentiality: None
Subsequent system integrity: None
Subsequent system availability: None

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

Attack Vector: Network: The vulnerable system is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: The attacker must take no measurable action to exploit the vulnerability. The attack requires no target-specific circumvention to exploit the vulnerability. An attacker can expect repeatable success against the vulnerable system.
Attack Requirements: None: The successful attack does not depend on the deployment and execution conditions of the vulnerable system. The attacker can expect to be able to reach the vulnerability and execute the exploit under all or most instances of the vulnerability.
Privileges Required: Low: The attacker requires privileges that provide basic capabilities that are typically limited to settings and resources owned by a single low-privileged user. Alternatively, an attacker with Low privileges has the ability to access only non-sensitive resources.
User Interaction: None: The vulnerable system can be exploited without interaction from any human user, other than the attacker.
Vulnerable system confidentiality: High: There is a total loss of confidentiality, resulting in all information within the Vulnerable System being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server.
Vulnerable system integrity: High: There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the vulnerable system. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the vulnerable system.
Vulnerable system availability: None: There is no impact to availability within the Vulnerable System.
Subsequent system confidentiality: None: There is no loss of confidentiality within the Subsequent System or all confidentiality impact is constrained to the Vulnerable System.
Subsequent system integrity: None: There is no loss of integrity within the Subsequent System or all integrity impact is constrained to the Vulnerable System.
Subsequent system availability: None: There is no impact to availability within the Subsequent System or all availability impact is constrained to the Vulnerable System.

Definitions: FIRST CVSS v4.0 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 19 Mar 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 31 Oct 2026.

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.
Weaponized: A Metasploit exploit module or Exploit-DB entry exists (Metasploit scanner modules do not count), or CISA SSVC or the CVSS exploit maturity 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

Upgrade SQLBot and dataease/SQLBot to 1.6.0.

Affected software

Product	Affected	Fixed in
dataeaseSQLBot	Affected <1.6.0	Fixed in 1.6.0
GitHubdataease/SQLBot`pkg:github/dataease/SQLBot`Other threats	Affected <1.6.0	Fixed in 1.6.0

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

To mitigate CVE-2026-32622, organizations should immediately upgrade SQLBot to version 1.6.0 or later, where the vulnerability is fixed. Until upgrade, restrict access to the Excel upload API to only highly trusted users and monitor usage for suspicious uploads. Implement additional input validation and sanitization on terminology descriptions before storage to prevent injection of malicious payloads. Employ semantic fencing or prompt filtering mechanisms to control how user-supplied terminology influences the LLM system prompt. Limit the privileges of the postgres database user to the minimum necessary, avoiding system-level permissions where possible. Monitor database and application logs for unusual COPY commands or other suspicious SQL activity. Enforce strong authentication and credential management to reduce risk from compromised accounts. Consider network segmentation to isolate SQLBot and its database from critical infrastructure. Finally, conduct security reviews of AI/LLM integrations to identify and remediate similar injection risks.

Description

SQLBot is an intelligent data query system based on a large language model and RAG. Versions 1.5.0 and below contain a Stored Prompt Injection vulnerability that chains three flaws: a missing permission check on the Excel upload API allowing any authenticated user to upload malicious terminology, unsanitized storage of terminology descriptions containing dangerous payloads, and a lack of semantic fencing when injecting terminology into the LLM's system prompt. Together, these flaws allow an attacker to hijack the LLM's reasoning to generate malicious PostgreSQL commands (e.g., COPY ... TO PROGRAM), ultimately achieving Remote Code Execution on the database or application server with postgres user privileges. The issue is fixed in v1.6.0.

Impact

The impact of CVE-2026-32622 is significant for organizations using SQLBot with PostgreSQL backends. Exploitation allows attackers to execute arbitrary commands on the database or application server with postgres user privileges, potentially leading to full system compromise. This jeopardizes the confidentiality, integrity, and availability of sensitive data and critical systems. Attackers can exfiltrate data, modify or delete records, deploy malware, or pivot to other parts of the network. Since the vulnerability requires only authenticated access without additional user interaction, insider threats or compromised credentials can be leveraged easily. The lack of semantic fencing in the LLM prompt injection expands the attack surface uniquely tied to AI-driven query systems, representing a novel vector for RCE. Organizations relying on SQLBot for data querying and analytics face operational disruption and reputational damage if exploited. The vulnerability also raises concerns about the security of integrating LLMs with backend databases without robust input validation and authorization controls.

CWE-862Missing Authorization (opens in a new tab)
Class weaknessLikelihood of exploit: HighCWE Top 25 (2025): #4OWASP Top 10 A01:2025: Broken Access Control (opens in a new tab)
The product does not perform an authorization check when an actor attempts to access a resource or perform an action.
Architecture and Design
Divide the product into anonymous, normal, privileged, and administrative areas. Reduce the attack surface by carefully mapping roles with data and functionality. Use role-based access control (RBAC) to enforce the roles at the appropriate boundaries.
Architecture and Design
Ensure that access control checks are performed related to the business logic. These checks may be different than the access control checks that are applied to more generic resources such as files, connections, processes, memory, and database records.
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.
OWASP Cheat Sheets
Authorization (opens in a new tab)
OWASP ASVS 4.0.3
V8.3.8 (opens in a new tab)
V13.4.2 (opens in a new tab)
V7.2.2 (opens in a new tab)
Attack patterns
Exploitation of Thunderbolt Protection Flaws (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).
CWE-20Improper Input Validation (opens in a new tab)
Class weaknessLikelihood of exploit: HighCWE Top 25 (2025): #18OWASP Top 10 A05:2025: Injection (opens in a new tab)
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.
MITRE discourages mapping vulnerabilities to this broad entry; the root cause is usually a more specific weakness.
Architecture and Design · Attack Surface Reduction
Consider using language-theoretic security (LangSec) techniques that characterize inputs using a formal language and build "recognizers" for that language. This effectively requires parsing to be a distinct layer that effectively enforces a boundary between raw input and internal data representations, instead of…
Architecture and Design · Libraries or Frameworks
Use an input validation framework such as Struts or the OWASP ESAPI Validation API. Note that using a framework does not automatically address all input validation problems; be mindful of weaknesses that could arise from misusing the framework itself (CWE-1173).
Architecture and Design · Implementation · Attack Surface Reduction
Understand all the potential areas where untrusted inputs can enter the product, including but not limited to: parameters or arguments, cookies, anything read from the network, environment variables, reverse DNS lookups, query results, request headers, URL components, e-mail, files, filenames, databases, and any…
OWASP Cheat Sheets
XML Security (opens in a new tab)
Mass Assignment (opens in a new tab)
Injection Prevention (opens in a new tab)
SQL Injection Prevention (opens in a new tab)
Injection Prevention in Java (opens in a new tab)
OWASP ASVS 4.0.3
V13.3.1 (opens in a new tab)
V5.1.4 (opens in a new tab)
V5.1.3 (opens in a new tab)
Attack patterns
Buffer Overflow via Environment Variables (opens in a new tab)
Server Side Include (SSI) Injection (opens in a new tab)
Cross Zone Scripting (opens in a new tab)
Command Line Execution through SQL Injection (opens in a new tab)
Object Relational Mapping Injection (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).
CWE-74Improper Neutralization of Special Elements in Output Used by a Downstream Component (Injection) (opens in a new tab)
Class weaknessLikelihood of exploit: HighOWASP Top 10 A05:2025: Injection (opens in a new tab)
The product constructs all or part of a command, data structure, or record using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify how it is parsed or interpreted when it is sent to a downstream component.
MITRE discourages mapping vulnerabilities to this broad entry; the root cause is usually a more specific weakness.
Requirements
Programming languages and supporting technologies might be chosen which are not subject to these issues.
Implementation
Utilize an appropriate mix of allowlist and denylist parsing to filter control-plane syntax from all input.
OWASP Cheat Sheets
Abuse Case (opens in a new tab)
Deserialization (opens in a new tab)
Injection Prevention (opens in a new tab)
SQL Injection Prevention (opens in a new tab)
Injection Prevention in Java (opens in a new tab)
OWASP ASVS 4.0.3
V1.5.1 (opens in a new tab)
Attack patterns
Buffer Overflow via Environment Variables (opens in a new tab)
Server Side Include (SSI) Injection (opens in a new tab)
HTTP Request Splitting (opens in a new tab)
Command Line Execution through SQL Injection (opens in a new tab)
Double Encoding (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).
CWE-77Improper Neutralization of Special Elements used in a Command (Command Injection) (opens in a new tab)
Class weaknessLikelihood of exploit: HighCWE Top 25 (2025): #23OWASP Top 10 A05:2025: Injection (opens in a new tab)
The product constructs all or part of a command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended command when it is sent to a downstream component.
Architecture and Design
If at all possible, use library calls rather than external processes to recreate the desired functionality.
Implementation
If possible, ensure that all external commands called from the program are statically created.
Implementation · Input Validation
Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
OWASP Cheat Sheets
Abuse Case (opens in a new tab)
Deserialization (opens in a new tab)
Injection Prevention (opens in a new tab)
SQL Injection Prevention (opens in a new tab)
Injection Prevention in Java (opens in a new tab)
OWASP ASVS 4.0.3
V1.5.1 (opens in a new tab)
Attack patterns
LDAP Injection (opens in a new tab)
Command Delimiters (opens in a new tab)
IMAP/SMTP Command Injection (opens in a new tab)
Manipulating Writeable Terminal Devices (opens in a new tab)
Exploiting Multiple Input Interpretation Layers (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

Community reviews

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 27 Mar 2026, 19:07 UTC

WeaknessesCWE-862, CWE-20, CWE-74 +1

Technical details

References

Community reviews

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