Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/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-2025-27777 is a high-severity SSRF (CWE-918) vulnerability in Applio Applio. Its CVSS base score is 7.7 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 32th 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.
CVE-2025-27777 is a server-side request forgery (SSRF) vulnerability in Applio, an open-source voice conversion tool. Versions 3.2.7 and prior are affected, with the flaw located in the `model_download.py` file at line 195. This blind SSRF allows attackers to force the Applio server to send requests on their behalf, as documented in the CVE description and referenced GitHub code locations including `assets/flask/routes.py` and `tabs/download/download.py`. The vulnerability is rated 7.5 (High) under CVSS 3.1 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N) and maps to CWE-918.
Any unauthenticated attacker with network access to the Applio server can exploit this blind SSRF to probe for other vulnerabilities on the server itself or on backend systems reachable by the Applio server within the internal network. Exploitation enables port scanning, service discovery, or chaining with other issues, such as the arbitrary file read in CVE-2025-27784, to achieve full SSRF and read files from internal hosts accessible to the server.
The GitHub Security Lab advisory (GHSL-2024-341_GHSL-2024-353_Applio) details the issue but notes that, as of publication on 2025-03-19, no patches are available for this vulnerability. Security practitioners should monitor the Applio repository for updates and consider network segmentation or disabling the affected model download functionality until remediation is released.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-6789
Vulnerability Data
Applio is a voice conversion tool. Versions 3.2.7 and prior are vulnerable to server-side request forgery (SSRF) in `model_download.py` (line 195 in 3.2.7). The blind SSRF allows for sending requests on behalf of Applio server and can be leveraged to…
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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 a 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. 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.