CVE-2024-45300

Sept. 29, 2024, 12:08 a.m.

5.9
Medium

Description

alf.io is an open source ticket reservation system for conferences, trade shows, workshops, and meetups. Prior to version 2.0-M5, a race condition allows the user to bypass the limit on the number of promo codes and use the discount coupon multiple times. In "alf.io", an event organizer can apply price discounts by using promo codes to your events. The organizer can limit the number of promo codes that will be used for this, but the time-gap between checking the number of codes and restricting the use of the codes allows a threat actor to bypass the promo code limit. Version 2.0-M5 fixes this issue.

Product(s) Impacted

Vendor Product Versions
Alf
  • Alf
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-362
Concurrent Execution using Shared Resource with Improper Synchronization ('Race Condition')
The product contains a code sequence that can run concurrently with other code, and the code sequence requires temporary, exclusive access to a shared resource, but a timing window exists in which the shared resource can be modified by another code sequence that is operating concurrently.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a alf alf / / / / / / / /

CVSS Score

5.9 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: HIGH
  • Privileges Required: NONE
  • Scope: UNCHANGED
  • Confidentiality Impact: NONE
  • Integrity Impact: HIGH
  • Availability Impact: NONE
  • CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:H/A:N

    View Vector String

Timeline

Published: Sept. 6, 2024, 1:15 p.m.
Last Modified: Sept. 29, 2024, 12:08 a.m.

Status : Analyzed

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

security-advisories@github.com

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.