GongShengyue OnlineBooks up to dfc5eacc08d3b0396c266049548618f6fb9587ea listSplit Interface BooksServlet.java column sql injection
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 5.7 | $0-$5k | 2.37+ |
Summary
A vulnerability marked as critical has been reported in GongShengyue OnlineBooks up to dfc5eacc08d3b0396c266049548618f6fb9587ea. This issue affects some unknown processing of the file src/cn/ylcto/book/servlet/BooksServlet.java of the component listSplit Interface. This manipulation of the argument column causes sql injection. The identification of this vulnerability is CVE-2026-90511. It is possible to initiate the attack remotely. Furthermore, there is an exploit available. This product is using a rolling release to provide continious delivery. Therefore, no version details for affected nor updated releases are available.
Details
A vulnerability was found in GongShengyue OnlineBooks up to dfc5eacc08d3b0396c266049548618f6fb9587ea. It has been declared as critical. Affected by this vulnerability is an unknown code of the file src/cn/ylcto/book/servlet/BooksServlet.java of the component listSplit Interface. The manipulation of the argument column 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.
It is possible to read the advisory at github.com. This vulnerability is known as CVE-2026-90511. The exploitation appears to be easy. The attack can be launched remotely. Technical details and also a public exploit are known. The attack technique deployed by this issue is T1505 according to MITRE ATT&CK.
It is possible to download the exploit at github.com. It is declared as proof-of-concept.
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Vendor
Name
Version
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 6.3VulDB Meta Temp Score: 5.7
VulDB Base Score: 6.3
VulDB Temp Score: 5.7
VulDB Vector: 🔒
VulDB Reliability: 🔍
CVSSv2
| AV | AC | Au | C | I | A |
|---|---|---|---|---|---|
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
|---|---|---|---|---|---|
| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
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: 🔒
Access: Public
Status: Proof-of-Concept
Download: 🔒
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
|---|---|---|---|---|
| Today | Unlock | Unlock | Unlock | Unlock |
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔒
Timeline
09/12/2026 Advisory disclosed09/12/2026 VulDB entry created
09/12/2026 VulDB entry last update
Sources
Advisory: github.comStatus: Not defined
CVE: CVE-2026-90511 (🔒)
GCVE (CVE): GCVE-0-2026-90511
GCVE (VulDB): GCVE-100-403099
scip Labs: https://www.scip.ch/en/?labs.20161013
Entry
Created: 09/12/2026 11:07Changes: 09/12/2026 11:07 (57)
Complete: 🔍
Submitter: hhhha
Cache ID: 216::103
Submit
Accepted
- Submit #911884: https://github.com/GongShengyue/OnlineBooks OnlineBooks 1.0 SQL Injection (by hhhha)
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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