CVE-2024-1561 (GCVE-0-2024-1561)
Vulnerability from cvelistv5 – Published: 2024-04-16 00:00 – Updated: 2025-02-13 17:32Title
Arbitrary Local File Read via Component Method Invocation in gradio-app/gradio
Summary
An issue was discovered in gradio-app/gradio, where the `/component_server` endpoint improperly allows the invocation of any method on a `Component` class with attacker-controlled arguments. Specifically, by exploiting the `move_resource_to_block_cache()` method of the `Block` class, an attacker can copy any file on the filesystem to a temporary directory and subsequently retrieve it. This vulnerability enables unauthorized local file read access, posing a significant risk especially when the application is exposed to the internet via `launch(share=True)`, thereby allowing remote attackers to read files on the host machine. Furthermore, gradio apps hosted on `huggingface.co` are also affected, potentially leading to the exposure of sensitive information such as API keys and credentials stored in environment variables.
Severity
7.5 (High)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-05-13 19:06 UTC
CWE
- CWE-29 - Path Traversal: '\..\filename'
Assigner
References
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| gradio-app | gradio-app/gradio |
Affected:
unspecified , < 4.13.0
(custom)
|
guessed | |
| gradio_project | gradio |
Affected:
4.12.0
cpe:2.3:a:gradio_project:gradio:-:*:*:*:*:python:*:* |
Shadowserver
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: ae45d364-f1b7-4aeb-9119-378e07ee8d63
Exploited: Yes
Characteristics
Severity:
75.0
Timestamps
First Seen: 2024-09-18
Asserted: 2024-09-18
Last Seen: 2026-07-17
Scope
Asset Exposure: ['internet-facing']
Notes: Affected: Gradio / Gradio | Class: ai-system | Severity: High (CVSS 7.5) | IoT: no | In CISA KEV: no | Honeypot connections on 2026-07-17: 3
Evidence
Type: Honeypot
Signal: In The Wild Attempts
Confidence: 70%
Source: shadowserver
Details
| 1D | 1 |
|---|---|
| Iot | no |
| Feed | Shadowserver Foundation honeypot/exploited-vulnerabilities |
| Type | http-scan |
| Class | ai-system |
| 7D Avg | 1 |
| Vendor | Gradio |
| 30D Avg | 5 |
| 90D Avg | 4 |
| Product | Gradio |
| Cisa Kev | no |
| Connections | 3 |
| Observation Date | 2026-07-17 |
| Vulnerability Class | CVSS |
| Vulnerability Score | 7.5 |
| Vulnerability Severity | High |
References
Created: 2026-06-30 09:23 UTC
| Updated: 2026-07-19 01:01 UTC
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: a566af8f-9d2b-43b7-ba36-9c6aa7c98189
Exploited: Yes
Timestamps
First Seen: 2025-10-05
Asserted: 2025-10-05
Scope
Notes: KEVIntel entry: Arbitrary Local File Read via Component Method Invocation in gradio-app/gradio | Affected: gradio-app / gradio-app/gradio | CVSS: 7.5 (HIGH) | Used in malware: unknown | Not yet in CISA KEV: True
Evidence
Type: Public Report
Signal: Successful Exploitation
Confidence: 70%
Source: kevintel
Details
| Feed | KEVIntel (kevintel.com) |
|---|---|
| Title | Arbitrary Local File Read via Component Method Invocation in gradio-app/gradio |
| Vendor | gradio-app |
| Product | gradio-app/gradio |
| Added Date | 2025-10-05T00:00:00.000Z |
| Cvss Score | 7.5 |
| Epss Score | None |
| Cvss Severity | HIGH |
| Epss Percentile | None |
| Used In Malware | unknown |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | True |
References
Created: 2026-06-23 14:03 UTC
| Updated: 2026-07-10 06:14 UTC
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"references": [
{
"url": "https://huntr.com/bounties/4acf584e-2fe8-490e-878d-2d9bf2698338"
},
{
"url": "https://github.com/gradio-app/gradio/commit/24a583688046867ca8b8b02959c441818bdb34a2"
},
{
"url": "https://www.gradio.app/changelog#4-13-0"
}
],
"source": {
"advisory": "4acf584e-2fe8-490e-878d-2d9bf2698338",
"discovery": "EXTERNAL"
},
"title": "Arbitrary Local File Read via Component Method Invocation in gradio-app/gradio"
}
},
"cveMetadata": {
"assignerOrgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
"assignerShortName": "@huntr_ai",
"cveId": "CVE-2024-1561",
"datePublished": "2024-04-16T00:00:15.906Z",
"dateReserved": "2024-02-15T19:12:58.336Z",
"dateUpdated": "2025-02-13T17:32:16.918Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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