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-2025-27774 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, contains 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 at the model download handling logic, where untrusted input is passed to network requests and file operations without adequate validation or restrictions.
An unauthenticated remote attacker can supply crafted inputs to trigger blind SSRF requests originating from the Applio server, enabling internal network reconnaissance or, when paired with a separate arbitrary file read issue such as CVE-2025-27784, direct access to internal resources. The accompanying file write primitive can be chained with other weaknesses, for example unsafe deserialization, to achieve remote code execution on the server.
Public references, including the GitHub Security Lab advisory GHSL-2024-341, confirm that no patches have been released for the affected code paths in routes.py, model_download.py, or the download tab handler. The EPSS score remains low with only minor fluctuation between its current value of 0.0173 and recorded peak of 0.0224.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-6786
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 156 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 blind SSRF can also be coupled with the an arbitrary file read (e.g., CVE-2025-27784) to read files from hosts on the internal network, that the Applio server can reach, which would make it a full SSRF. 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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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.