CVE-2026-28414: gradio: security flaw enables exploitation

GHSA-39mp-8hj3-5c49 HIGH PoC AVAILABLE NUCLEI TEMPLATE CISA: TRACK*
Published February 27, 2026
CISO Take

Gradio is ubiquitous in ML teams for model demos, internal tooling, and rapid prototyping — often exposed on internal networks or directly to the internet. Any Windows-based deployment running Python 3.13+ and Gradio < 6.7 allows unauthenticated attackers to read arbitrary files, including model weights, API keys, .env files, and training data. Patch immediately to 6.7 or restrict network access; assume compromise if this was internet-facing.

What is the risk?

Risk is HIGH due to zero-prerequisite exploitation: no authentication, no user interaction, low complexity, and network-accessible. The Python 3.13 behavioral change in os.path.isabs creates a silent regression in path validation logic that bypasses even Gradio's own authentication layer. Exposure is significant because Gradio is the de facto standard for ML model UIs and is frequently deployed without hardening. Windows-based MLOps environments and data science workstations are particularly at risk.

What systems are affected?

Package Ecosystem Vulnerable Range Patched
Gradio pip No patch
43.0K OpenSSF 5.6 685 dependents Pushed 4d ago 26% patched ~110d to patch Full package profile →
Gradio pip < 6.7.0 6.7.0
43.0K OpenSSF 5.6 685 dependents Pushed 4d ago 26% patched ~110d to patch Full package profile →

How severe is it?

CVSS 3.1
7.5 / 10
EPSS
3.1%
chance of exploitation in 30 days
Higher than 86% of all CVEs
Exploitation Status
Exploit Available
Exploitation: MEDIUM
Sophistication
Trivial
Exploitation Confidence
medium
VulnCheck KEV (exploitation reported — broader/earlier than CISA) — May 2026
CISA SSVC: Public PoC
Public PoC indexed (trickest/cve)
Nuclei detection template available
Composite signal derived from CISA KEV, VulnCheck KEV, CISA SSVC, EPSS, Metasploit, Exploit-DB, trickest/cve, Nuclei templates, and inthewild.io exploitation reports.

What is the attack surface?

AV AC PR UI S C I A
AV Network
AC Low
PR None
UI None
S Unchanged
C High
I None
A None

What should I do?

1 step
  1. 1) Patch immediately: upgrade Gradio to 6.7+. 2) Identify all Windows-based Gradio deployments via asset inventory (grep requirements.txt, pyproject.toml, conda envs for 'gradio'). 3) Restrict network access to Gradio instances — bind to localhost only unless external access is required. 4) Audit access logs for path traversal patterns: requests containing '../', absolute paths, or Windows-style paths (e.g., /windows/, /users/). 5) Rotate any credentials (API keys, tokens, DB passwords) that may have been accessible from the server filesystem. 6) If Python 3.13 is required but patching is delayed, downgrade to Python 3.12 as a temporary workaround. 7) Implement WAF rules blocking directory traversal sequences on Gradio endpoints.

What does CISA's SSVC say?

Decision Track*
Exploitation poc
Automatable No
Technical Impact partial

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:

EU AI Act
Art. 15 - Accuracy, robustness and cybersecurity Art. 9 - Risk management system Article 15 - Accuracy, Robustness and Cybersecurity Article 9 - Risk Management System
ISO 42001
A.6.2.6 - AI system security A.8.2 - AI system vulnerability management A.9.1 - AI System Security
NIST AI RMF
GOVERN 1.7 - Processes for decommissioning AI systems MANAGE 2.2 - Mechanisms to sustain and monitor AI risk treatments
OWASP LLM Top 10
LLM03 - Supply Chain Vulnerabilities LLM05:2025 - Improper Output Handling / Supply Chain Vulnerabilities LLM06 - Sensitive Information Disclosure LLM06:2025 - Sensitive Information Disclosure

Frequently Asked Questions

What is CVE-2026-28414?

Gradio is ubiquitous in ML teams for model demos, internal tooling, and rapid prototyping — often exposed on internal networks or directly to the internet. Any Windows-based deployment running Python 3.13+ and Gradio < 6.7 allows unauthenticated attackers to read arbitrary files, including model weights, API keys, .env files, and training data. Patch immediately to 6.7 or restrict network access; assume compromise if this was internet-facing.

Is CVE-2026-28414 actively exploited?

Proof-of-concept exploit code is publicly available for CVE-2026-28414, increasing the risk of exploitation.

How to fix CVE-2026-28414?

1) Patch immediately: upgrade Gradio to 6.7+. 2) Identify all Windows-based Gradio deployments via asset inventory (grep requirements.txt, pyproject.toml, conda envs for 'gradio'). 3) Restrict network access to Gradio instances — bind to localhost only unless external access is required. 4) Audit access logs for path traversal patterns: requests containing '../', absolute paths, or Windows-style paths (e.g., /windows/, /users/). 5) Rotate any credentials (API keys, tokens, DB passwords) that may have been accessible from the server filesystem. 6) If Python 3.13 is required but patching is delayed, downgrade to Python 3.12 as a temporary workaround. 7) Implement WAF rules blocking directory traversal sequences on Gradio endpoints.

What systems are affected by CVE-2026-28414?

This vulnerability affects the following AI/ML architecture patterns: model serving, ML development environments, MLOps evaluation pipelines, internal model demo portals, training pipelines, agent frameworks with Gradio UI.

What is the CVSS score for CVE-2026-28414?

CVE-2026-28414 has a CVSS v3.1 base score of 7.5 (HIGH). The EPSS exploitation probability is 3.09%.

What is the AI security impact?

Affected AI Architectures

model servingML development environmentsMLOps evaluation pipelinesinternal model demo portalstraining pipelinesagent frameworks with Gradio UI

MITRE ATLAS Techniques

AML.T0006 Active Scanning
AML.T0007 Discover AI Artifacts
AML.T0010.001 AI Software
AML.T0025 Exfiltration via Cyber Means
AML.T0035 AI Artifact Collection
AML.T0037 Data from Local System
AML.T0048.004 AI Intellectual Property Theft
AML.T0049 Exploit Public-Facing Application
AML.T0055 Unsecured Credentials

Compliance Controls Affected

EU AI Act: Art. 15, Art. 9, Article 15, Article 9
ISO 42001: A.6.2.6, A.8.2, A.9.1
NIST AI RMF: GOVERN 1.7, MANAGE 2.2
OWASP LLM Top 10: LLM03, LLM05:2025, LLM06, LLM06:2025

What are the technical details?

Original Advisory

Gradio is an open-source Python package designed for quick prototyping. Prior to version 6.7, Gradio apps running on Window with Python 3.13+ are vulnerable to an absolute path traversal issue that enables unauthenticated attackers to read arbitrary files from the file system. Python 3.13+ changed the definition of `os.path.isabs` so that root-relative paths like `/windows/win.ini` on Windows are no longer considered absolute paths, resulting in a vulnerability in Gradio's logic for joining paths safely. This can be exploited by unauthenticated attackers to read arbitrary files from the Gradio server, even when Gradio is set up with authentication. Version 6.7 fixes the issue.

Exploitation Scenario

An adversary identifies a company's internal ML demo portal running Gradio on a Windows server (common in enterprise ML teams). Using a simple HTTP GET request with a crafted path like /file=/windows/win.ini or /file=/../../../users/mluser/.env, the attacker bypasses Gradio's path validation because Python 3.13's os.path.isabs no longer flags root-relative paths as absolute on Windows. The attacker systematically reads .env files (harvesting Hugging Face tokens, OpenAI API keys, AWS credentials), model configuration files, and proprietary fine-tuning datasets — all without any credentials. With harvested cloud credentials, the attacker pivots to S3 buckets containing full training datasets and model artifacts.

Weaknesses (CWE)

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:H/I:N/A:N

Timeline

Published
February 27, 2026
Last Modified
March 5, 2026
First Seen
February 27, 2026

Scanner Template Available

A Nuclei vulnerability scanner template exists for this CVE. You can scan your infrastructure for this vulnerability immediately.

View template on GitHub
nuclei -t http/cves/2026/CVE-2026-28414.yaml -u https://target.example.com

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