Learning with Texts 2.0.3 URL Parameter sql injection

Summaryinfo

A vulnerability was found in Learning with Texts 2.0.3. It has been classified as critical. This issue affects some unknown processing of the component URL Parameter Handler. Performing a manipulation results in sql injection. This vulnerability is reported as CVE-2024-48509. The attack is possible to be carried out remotely. No exploit exists.

Detailsinfo

A vulnerability, which was classified as critical, was found in Learning with Texts 2.0.3. This affects an unknown code block of the component URL Parameter Handler. The manipulation with an unknown input leads to a sql injection vulnerability. CWE is classifying the issue as 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. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:

Learning with Texts (LWT) 2.0.3 is vulnerable to SQL Injection. This occurs when the application fails to properly sanitize user inputs, allowing attackers to manipulate SQL queries by injecting malicious SQL statements into URL parameters. By exploiting this vulnerability, an attacker could gain unauthorized access to the database, retrieve sensitive information, modify or delete data, and execute arbitrary commands.

It is possible to read the advisory at medium.com. This vulnerability is uniquely identified as CVE-2024-48509 since 10/08/2024. The exploitability is told to be easy. It is possible to initiate the attack remotely. The technical details are unknown and an exploit is not publicly available. The pricing for an exploit might be around USD $0-$5k at the moment (estimation calculated on 10/21/2024). The attack technique deployed by this issue is T1505 according to MITRE ATT&CK.

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.

Productinfo

Name

• Learning with Texts

Version

• 2.0.3

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CPE 2.2info

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