Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-27775 is a high-severity SSRF (CWE-918) vulnerability in Applio Applio. Its CVSS base score is 8.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 42th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to AC-4 (Information Flow Enforcement) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
Applio, an open-source voice conversion tool, is affected by a server-side request forgery vulnerability combined with an arbitrary file write flaw in versions 3.2.7 and earlier. The issues reside in model_download.py, where untrusted input supplied to download functionality permits outbound requests from the server and uncontrolled writes to the local filesystem.
An unauthenticated remote attacker can trigger the blind SSRF to reach internal network resources or the server itself and can write attacker-controlled files. These primitives may be chained with other weaknesses, such as unsafe deserialization, to obtain remote code execution on the Applio host.
The GitHub Security Lab advisory (GHSL-2024-341) confirms the absence of patches at disclosure and points to the affected code paths in routes.py, model_download.py, and the download tab. The EPSS score has remained low, with a recorded peak of 0.0316 and a current value of 0.0239.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-6787
Vulnerability Data
Applio is a voice conversion tool. Versions 3.2.7 and prior are vulnerable to server-side request forgery (SSRF) and file write in `model_download.py` (line 143 in 3.2.7). The blind SSRF allows for sending requests on behalf of Applio server and can…
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be leveraged to probe for other vulnerabilities on the server itself or on other back-end systems on the internal network, that the Applio server can reach. The file write allows for writing files on the server, which can be coupled with other vulnerabilities, for example an unsafe deserialization, to achieve remote code execution on the Applio server. As of time of publication, no known patches are available.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.6V1.5.3V5.3.2V10.4.7
Mitigating Controls (NIST 800-53 r5) AI
Information flow enforcement can restrict which destinations the server is allowed to contact on behalf of users.
Input validation directly stops untrusted URLs from being accepted and fetched without destination checks.
Boundary protection limits the network reach of server-initiated requests even if SSRF occurs.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure development practices directly include input validation and destination allow-listing that prevent SSRF.
Runtime monitoring of web applications and services can detect anomalous outbound requests indicative of SSRF.
Vulnerability identification processes can discover and record SSRF flaws in web applications.
Network segmentation and egress controls can limit the damage from successful SSRF requests.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.