CVE-2024-47869
Gradio Project Gradio ≤ 4.44.0
Raw vector
CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N/E:X/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-2024-47869 is a low-severity Observable Discrepancy (CWE-203) vulnerability in Gradio Project Gradio. Its CVSS base score is 2.3 (Low).
Operationally, exploitation aligns with the MITRE ATT&CK technique Account Discovery (T1087); ranked at the 22th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Other AI Platforms; in the Other ATLAS/OWASP Terms risk domain.
The strongest mitigations our analysis identified map to IA-6 (Authentication Feedback) and SI-11 (Error Handling) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-0067
Vulnerability Data
Gradio is an open-source Python package designed for quick prototyping. This vulnerability involves a **timing attack** in the way Gradio compares hashes for the `analytics_dashboard` function. Since the comparison is not done in constant time, an attacker could exploit this…
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by measuring the response time of different requests to infer the correct hash byte-by-byte. This can lead to unauthorized access to the analytics dashboard, especially if the attacker can repeatedly query the system with different keys. Users are advised to upgrade to `gradio>4.44` to mitigate this issue. To mitigate the risk before applying the patch, developers can manually patch the `analytics_dashboard` dashboard to use a **constant-time comparison** function for comparing sensitive values, such as hashes. Alternatively, access to the analytics dashboard can be disabled.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Other AI Platforms
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Gradio is an open-source Python package for quick prototyping of web interfaces for machine learning models, classifying it as an 'Other Platforms' tool in the AI ecosystem. The vulnerability is a timing attack in its analytics dashboard, confirming AI-related context.
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 1 hardening rule · 1 OS baseline
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Mitigating Controls (NIST 800-53 r5) AI
Obscures authentication feedback so that success/failure differences are not observable to attackers.
Requires error messages to avoid revealing exploitable details, directly stopping observable response discrepancies.
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 prevent observable response discrepancies via consistent error handling and timing.
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.
Accurate, synchronized timestamps reduce observable timing discrepancies that an attacker could exploit to infer sensitive information or distinguish between success and failure paths.