CVE-2024-13538
Published: 18 February 2025
Summary
CVE-2024-13538 is a medium-severity Generation of Error Message Containing Sensitive Information (CWE-209) vulnerability in Bigbuy Dropshipping Connector For Woocommerce. Its CVSS base score is 5.3 (Medium).
Operationally, ranked in the top 31.6% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-4847
Vulnerability details
The BigBuy Dropshipping Connector for WooCommerce plugin for WordPress is vulnerable to Full Path Disclosure in all versions up to, and including, 2.0.0. This is due the /vendor/cocur/slugify/bin/generate-default.php file being directly accessible and triggering an error. This makes it possible…
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for unauthenticated attackers to retrieve the full path of the web application, which can be used to aid other attacks. The information displayed is not useful on its own, and requires another vulnerability to be present for damage to an affected website.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Detects error messages that leak sensitive information as evidence of disclosure.
The control directly mitigates generation of error messages containing sensitive authentication details by requiring obscured feedback instead of verbose responses.
Misdirection allows generation of misleading error messages that withhold or falsify sensitive details.
Validates pathnames and filenames to prevent traversal outside intended directories.
Explicitly requires error messages to avoid including sensitive or exploitable details while still supporting corrective action.
Validation ensures error messages contain only expected, non-sensitive content and blocks leakage via verbose errors.
Fail-safe procedures can be defined to suppress or sanitize error output, reducing generation of messages that contain sensitive information.