Cyber Posture

CVE-2025-27784

HighPublic PoC

Published: 19 March 2025

Published
19 March 2025
Modified
01 August 2025
KEV Added
Patch
CVSS Score 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
EPSS Score 0.0043 62.9th percentile
Risk Priority 15 60% EPSS · 20% KEV · 20% CVSS

Description

Adversaries may search local file systems and remote file shares for files containing insecurely stored credentials.

Security Summary

CVE-2025-27784 is an arbitrary file read vulnerability in Applio, an open-source voice conversion tool. It affects versions 3.2.8-bugfix and prior, stemming from improper handling in the `export_pth` function within the train.py module. The flaw, associated with CWE-200 (Exposure of Sensitive Information to an Unauthorized Actor), carries a CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N), indicating high confidentiality impact with network accessibility and no requirements for privileges or user interaction.

Remote attackers can exploit this vulnerability without authentication by triggering the flawed export function, enabling them to read arbitrary files on the Applio server. When combined with blind server-side request forgery, it allows extraction of files from internal network servers that the Applio instance can access, potentially exposing sensitive configuration, credentials, or other data.

The GitHub Security Lab advisory (GHSL-2024-341 and GHSL-2024-353) details the issue with references to specific code lines in train.py but notes no patches are available as of the CVE's publication on 2025-03-19. Security practitioners should monitor the Applio repository for updates and consider network segmentation or disabling the affected train functionality until remediation.

Details

CWE(s)
CWE-200NVD-CWE-noinfo

Affected Products

applio
applio
≤ 3.2.8-bugfix

MITRE ATT&CK Enterprise Techniques

T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
T1005 Data from Local System Collection
Adversaries may search local system sources, such as file systems, configuration files, local databases, virtual machine files, or process memory, to find files of interest and sensitive data prior to Exfiltration.
T1552.001 Credentials In Files Credential Access
Adversaries may search local file systems and remote file shares for files containing insecurely stored credentials.
Why these techniques?

Arbitrary file read in public-facing app enables remote exploitation (T1190), direct local file access (T1005), and extraction of credentials from files (T1552.001).

Confidence: HIGH · MITRE ATT&CK Enterprise v19.0

References