Skip to content
Submit incident
AII-1001-85269
ConfirmedA court, a regulator or the organization itself has stated the core facts, or the record cites a court or regulator source.

Applio allows SSRF and arbitrary file write via model_download.py

GitHub Security Lab identified server-side request forgery and arbitrary file write vulnerabilities in Applio 3.2.7 through the model_download.py module, which accepts user-supplied URLs that are used to fetch and write files to the server. The vulnerabilities could enable remote code execution when combined with other flaws.

11 December 2024 Β· Applio Β· Security and cyberattacks
11 December 2024
AII-1001-852693 sources ↓
Quick facts
Category
Security and cyberattacks
Source
github.com
Date
11 December 2024
Drafted by
Raidu Incident Detection

What happened

Applio 3.2.7 contains vulnerabilities in model_download.py that allow server-side request forgery (SSRF) and arbitrary file writes.

The download.py endpoint accepts user-supplied URLs which are passed to model_download.py line 143, where an HTTP GET request is made to arbitrary destinations and files are downloaded and written to the server.

Reported impact

The blind SSRF allows attackers to send requests on behalf of the Applio server to probe for vulnerabilities on the server itself or on internal network systems reachable by the Applio server.

The file write capability can be combined with other vulnerabilities, including unsafe deserialization, to achieve remote code execution on the Applio server.

Index analysis

Similar SSRF and file write issues were identified in CVE-2025-27775 (GHSL-2024-342) and CVE-2025-27776 (GHSL-2024-343), indicating a pattern of unsafe handling of user-supplied URLs across multiple endpoints.

Governance controls

GitHub Security Lab reported the vulnerabilities on 2024-12-11 through coordinated disclosure. Unsafe deserialization vulnerabilities were fixed on 2025-02-01, but GHSL-2024-341 and related SSRF/file write issues remained unresolved by the 90-day disclosure deadline.

Classification

Category
Security and cyberattacks
Harm status
Potential harm
Intent
Unintentional
Timing
Post-deployment
Harmed
Business
AI systems
Applio

Sources and evidence

This record was researched and written by the Index, based on the following original reporting.

github.com
https://github.com/IAHispano/Applio/blob/29b4a00e4be209f9aac51cd9ccffcc632dfb2973/assets/flask/routes.py#L14
securitylab.github.com
https://securitylab.github.com/advisories/GHSL-2024-341_GHSL-2024-353_Applio/
cve.org
NVD entry