Submit #944843: SourceCodester Drug Recommendation System Using Machine Learning, PHP, and MySQL Database 1.0 SQL Injectioninfo

TitleSourceCodester Drug Recommendation System Using Machine Learning, PHP, and MySQL Database 1.0 SQL Injection
DescriptionA SQL Injection vulnerability was found in SourceCodester Drug Recommendation System Using Machine Learning, PHP, and MySQL Database v1.0. The issue is present in the /drug_recommender/Admin/edit_symptom.php endpoint through the id GET parameter. Since the application does not properly validate the input before using it in an SQL query, an unauthenticated attacker can manipulate the parameter and access sensitive information stored in the MySQL database, including user and patient data. Product Website: https://www.sourcecodester.com/php/18278/drug-recommender-web-app-student-project.html RESEARCHERS: Researcher 1: Karan Parelkar Email: [email protected] GitHub: https://github.com/KaranParelkar LinkedIn: https://www.linkedin.com/in/karan-parelkar-6a370125b/ Researcher 2: Anubhav Verma Email: [email protected] GitHub: https://github.com/anubhavv106 LinkedIn: https://www.linkedin.com/in/anubhav-verma-7123a1232/ Researcher 3: Parth Desai Email: [email protected] GitHub: https://github.com/ParthD31 LinkedIn: https://www.linkedin.com/in/parth-desai-801951224/
Source⚠️ https://github.com/KaranParelkar/Drug_recommendation_system/blob/main/sqli/edit_symptom_id_parameter/Readme.md
User
 anubhav106 (UID 98769)
Submission08/24/2026 15:18 (26 days ago)
Moderation09/19/2026 15:23 (26 days later)
StatusAccepted
VulDB entry407948 [SourceCodester Drug Recommendation System 1.0 /Admin/edit_symptom.php ID sql injection]
Points20

Do you know our Splunk app?

Download it now for free!