CVE-2026-43624: F5-TTS: path traversal enables arbitrary file write
HIGH PoC AVAILABLEF5-TTS through v1.1.20 contains an unauthenticated path traversal in its Gradio-based fine-tuning interface, allowing any network-reachable attacker to write attacker-controlled JSON content to arbitrary filesystem paths by supplying absolute path strings as project names to an unsanitized os.path.join() call. With a CVSS of 8.2, zero authentication required, zero user interaction, low attack complexity, and full network accessibility, this is trivially exploitable against any exposed instance — a particularly serious condition on AI training servers, which routinely operate with broad filesystem permissions over model checkpoints, training datasets, and configuration directories. While no public exploit or CISA KEV listing currently exists, the vulnerability class is well-understood and requires no ML knowledge to weaponize: a single crafted HTTP request is sufficient. Organizations running F5-TTS fine-tuning interfaces should upgrade to the patched version (commit 2f53ded) or immediately restrict network access to the Gradio finetune handlers behind authentication and VPN.
What is the risk?
HIGH. The attack surface is maximally favorable to an attacker — no credentials, no interaction, low complexity, over the network. AI fine-tuning servers are high-value targets: they typically hold write access to model weight directories, training pipelines, and configuration stores. An unauthenticated arbitrary file write on such a host can escalate to persistent access (cron injection, startup script overwrite), training data poisoning, or backdoored model deployment, converting a single file-write primitive into full pipeline compromise. The absence of a current public exploit or KEV entry reduces immediate threat pressure but the simplicity of the attack class means weaponization time is near-zero once the vulnerability is public.
How does the attack unfold?
How severe is it?
What is the attack surface?
What should I do?
1 step-
1) Upgrade F5-TTS to the patched version incorporating commit 2f53ded68e5f69e248ceb200a51ef4d1dc647936 — this introduces path validation ensuring resolved paths remain within the intended base directory. 2) If immediate upgrade is not possible, restrict network access to the Gradio finetune interface — place behind VPN, firewall rule, or require authentication via reverse proxy. 3) Run the F5-TTS server process under a least-privilege OS account with write permissions scoped only to required project directories. 4) Audit the server filesystem for unexpected directories or JSON files outside the configured F5-TTS project base path, particularly in /tmp, /etc/cron.d, /etc/cron.hourly, and user home directories. 5) Apply WAF or ingress rules blocking requests with absolute path patterns (/tmp/, /etc/, /root/, ../ sequences) in project name parameters. 6) Review any downstream models produced during the exposure window for unexpected behavioral changes.
What does CISA's SSVC say?
Source: CISA Vulnrichment (SSVC v2.0). Decision based on the CISA Coordinator decision tree.
How is it classified?
Which compliance frameworks are affected?
This CVE is relevant to:
Frequently Asked Questions
What is CVE-2026-43624?
F5-TTS through v1.1.20 contains an unauthenticated path traversal in its Gradio-based fine-tuning interface, allowing any network-reachable attacker to write attacker-controlled JSON content to arbitrary filesystem paths by supplying absolute path strings as project names to an unsanitized os.path.join() call. With a CVSS of 8.2, zero authentication required, zero user interaction, low attack complexity, and full network accessibility, this is trivially exploitable against any exposed instance — a particularly serious condition on AI training servers, which routinely operate with broad filesystem permissions over model checkpoints, training datasets, and configuration directories. While no public exploit or CISA KEV listing currently exists, the vulnerability class is well-understood and requires no ML knowledge to weaponize: a single crafted HTTP request is sufficient. Organizations running F5-TTS fine-tuning interfaces should upgrade to the patched version (commit 2f53ded) or immediately restrict network access to the Gradio finetune handlers behind authentication and VPN.
Is CVE-2026-43624 actively exploited?
Proof-of-concept exploit code is publicly available for CVE-2026-43624, increasing the risk of exploitation.
How to fix CVE-2026-43624?
1) Upgrade F5-TTS to the patched version incorporating commit 2f53ded68e5f69e248ceb200a51ef4d1dc647936 — this introduces path validation ensuring resolved paths remain within the intended base directory. 2) If immediate upgrade is not possible, restrict network access to the Gradio finetune interface — place behind VPN, firewall rule, or require authentication via reverse proxy. 3) Run the F5-TTS server process under a least-privilege OS account with write permissions scoped only to required project directories. 4) Audit the server filesystem for unexpected directories or JSON files outside the configured F5-TTS project base path, particularly in /tmp, /etc/cron.d, /etc/cron.hourly, and user home directories. 5) Apply WAF or ingress rules blocking requests with absolute path patterns (/tmp/, /etc/, /root/, ../ sequences) in project name parameters. 6) Review any downstream models produced during the exposure window for unexpected behavioral changes.
What systems are affected by CVE-2026-43624?
This vulnerability affects the following AI/ML architecture patterns: ML training pipelines, AI fine-tuning environments, Model serving infrastructure (co-located with finetune server).
What is the CVSS score for CVE-2026-43624?
CVE-2026-43624 has a CVSS v3.1 base score of 8.2 (HIGH). The EPSS exploitation probability is 0.39%.
What is the AI security impact?
Affected AI Architectures
MITRE ATLAS Techniques
AML.T0010.001 AI Software AML.T0020 Poison Training Data AML.T0049 Exploit Public-Facing Application Compliance Controls Affected
What are the technical details?
Original Advisory
F5-TTS through version 1.1.20 contains a path traversal vulnerability in the finetune Gradio handlers that allows unauthenticated attackers to write arbitrary files by passing unsanitized user-supplied project names directly to os.path.join() without validating the resulting path stays within the intended base directory. Attackers can supply absolute path arguments such as /tmp/EVIL to override the base directory entirely and create arbitrary directories with attacker-controlled JSON content at any filesystem path writable by the server process.
Exploitation Scenario
An attacker scans for internet-exposed Gradio interfaces (common in shared research GPU clusters and self-hosted ML environments) and identifies an F5-TTS instance. Without any credentials, they send a POST request to the finetune project creation endpoint supplying a project name of '/etc/cron.d/r00t' with a JSON body containing a cron job payload. The server, passing the name directly to os.path.join() without validation, writes the file to /etc/cron.d/r00t under the server process user's permissions, establishing command execution persistence. Alternatively, the attacker targets the F5-TTS model checkpoint directory to overwrite legitimate fine-tuned weights with backdoored speech synthesis model files that produce subtly altered output — enabling a supply chain attack on any downstream deployment consuming models from this training server. The entire attack requires no ML knowledge and executes in under 30 seconds.
Weaknesses (CWE)
CWE-22 Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
Primary
CWE-22 Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') CWE-22 — Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal'): The product uses external input to construct a pathname that is intended to identify a file or directory that is located underneath a restricted parent directory, but the product does not properly neutralize special elements within the pathname that can cause the pathname to resolve to a location that is outside of the restricted directory.
- [Implementation] Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylis
- [Architecture and Design] For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.
Source: MITRE CWE corpus.
CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:L References
Timeline
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