CVE-2025-58163 (GCVE-0-2025-58163)
Vulnerability from cvelistv5 – Published: 2025-09-03 01:34 – Updated: 2025-09-03 15:44
VLAI
EPSS
VEX
Title
FreeScout's deserialization of untrusted data can lead to Remote Code Execution
Summary
FreeScout is a free help desk and shared inbox built with PHP's Laravel framework. Versions 1.8.185 and earlier contain a deserialization of untrusted data vulnerability that allows authenticated attackers with knowledge of the application's APP_KEY to achieve remote code execution. The vulnerability is exploited via endpoint, e.g.: `/help/{mailbox_id}/auth/{customer_id}/{hash}/{timestamp}` where the `customer_id` and `timestamp` parameters are processed through the decrypt function in `app/Helper.php` without proper validation. The code decrypts using Laravel's built-in encryption functions, which subsequently deserialize the decrypted payload without sanitization, allowing attackers to craft malicious serialized PHP objects using classes to trigger arbitrary command execution. This is fixed in version 1.8.186.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-09-03 13:47 UTC
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/freescout-help-desk/freescout/… | x_refsource_CONFIRM |
| https://github.com/freescout-help-desk/freescout/… | x_refsource_MISC |
| https://github.com/freescout-help-desk/freescout/… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| freescout-help-desk | freescout |
Affected:
< 1.8.186
|
guessed |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
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