Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/VA:H/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-2025-27787 is a high-severity Path Traversal (CWE-22) vulnerability in Applio Applio. Its CVSS base score is 7.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 49% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to AC-3 (Access 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-2025-27787 is a denial-of-service (DoS) vulnerability affecting Applio, an open-source voice conversion tool, in versions 3.2.8-bugfix and prior. The issue resides in the restart.py component, where the user-supplied model_name parameter from train.py is passed unsanitized to the stop_train function. This constructs a file path to a config.json file, which is then read to extract a list of process IDs under "process_pids" and terminate those processes. The vulnerability enables path traversal (CWE-22), such as using "../../" in model_name to access config.json files from arbitrary locations, and improper handling akin to injection flaws (CWE-74). The CVSS v3.1 base score is 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H).
A remote, unauthenticated attacker can exploit this by first leveraging an arbitrary file write primitive—mentioned in the advisory as a prerequisite—to create a malicious config.json in a controllable location like logs/foobar, populated with a list of process IDs. The attacker then supplies a crafted model_name (e.g., "logs/foobar" or path-traversed equivalents) to trigger the endpoint, causing the server to kill all listed processes. By including hundreds of process IDs, the attacker induces widespread process termination, including Applio's own processes and potentially other critical system processes, resulting in effective DoS.
The GitHub Security Lab advisory (GHSL-2024-354) details the flaw with references to specific code lines in restart.py (L9) and train.py (L306), but as of publication on 2025-03-19, no patches or mitigations are available for Applio.
Applio's role as a voice conversion tool suggests relevance to AI/ML workflows, where model training and process management are common, heightening the risk in shared or exposed development environments. No real-world exploitation has been reported.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-6795
Vulnerability Data
Applio is a voice conversion tool. Versions 3.2.8-bugfix and prior are vulnerable to denial of service (DoS) in restart.py. `model_name` in train.py takes user input, and passes it to the `stop_train` function in restart.py, which uses it construct a path…
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to a folder with `config.json`. That `config.json` is opened and the list of values under "process_pids" are read. Next all the process IDs listed in the JSON are killed. Using one of the arbitrary file writes, one can write to `logs/foobar` a `config.json` file, which contains a list of process IDs. Then one can access this endpoint to kill these processes. Since an attacker can't know what process is running on which process ID, they can send a list of hundreds of process IDs, which can kill the process that applio is using to run, as well as other, potentially important processes, which leads to DoS. Note that constructing a path with user input also enables path traversal. For example, by supplying "../../" in `model_name` one can access `config.json` freom locations two folders down on the 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
Enforces the intended directory access authorizations that path traversal would otherwise bypass.
Input validation directly neutralizes special path elements before pathname construction occurs.
Least privilege reduces the impact of any unauthorized file access obtained via traversal.
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 SDLC practices directly require input validation and output encoding that prevent injection flaws.
Patching/maintenance can remediate known path-traversal flaws in deployed software (partial prevention of exploitability) but does nothing to stop the coding defect from being introduced in the first place.
PR.AA-05 defines and reviews access policies but does not address code-level pathname neutralization, so neither direction prevents CWE-22.
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.
Security testing in development catches path traversal via static/dynamic analysis.
Logging supports detection of injection attempts but does not prevent the weakness.
Monitoring activities can identify active injection attacks after they occur.
Secure SDLC mandates input validation and path sanitization that directly prevent path traversal.
Application security requirements include rules for safe file handling and canonicalization.
Secure architecture principles require least-privilege file access and directory isolation.