CVE-2022-50944 (GCVE-0-2022-50944)
Vulnerability from cvelistv5 – Published: 2026-05-10 12:12 – Updated: 2026-07-15 01:24
VLAI
EPSS
VEX
Title
Aero CMS 0.0.1 PHP Code Injection via posts.php
Summary
Aero CMS 0.0.1 contains a PHP code injection vulnerability that allows authenticated attackers to execute arbitrary PHP code by uploading malicious files through the image parameter. Attackers can upload PHP files with embedded code to the admin posts.php endpoint with source=add_post parameter, and the uploaded files are executed by the server.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: total
CISA Coordinator (v2.0.3)
CWE
- CWE-94 - Improper Control of Generation of Code ('Code Injection')
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://www.exploit-db.com/exploits/51085 | exploit |
| https://github.com/MegaTKC/AeroCMS | product |
| https://www.vulncheck.com/advisories/aero-cms-php… | third-party-advisory |
Credits
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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
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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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.
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