CVE-2024-41120
Published: 26 July 2024
Summary
CVE-2024-41120 is a critical-severity Improper Input Validation (CWE-20) vulnerability in Opengeos Streamlit-Geospatial. Its CVSS base score is 9.8 (Critical).
Operationally, ranked at the 47.3th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-38939
Vulnerability details
streamlit-geospatial is a streamlit multipage app for geospatial applications. Prior to commit c4f81d9616d40c60584e36abb15300853a66e489, the `url` variable on line 63 of `pages/9_🔲_Vector_Data_Visualization.py` takes user input, which is later passed to the `gpd.read_file` method. `gpd.read_file` method creates a request to arbitrary destinations,…
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leading to blind server-side request forgery. Commit c4f81d9616d40c60584e36abb15300853a66e489 fixes this issue.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Directly implements checks on information inputs to reject invalid data before processing.
Penetration testing attempts server-side requests to internal resources, identifying SSRF weaknesses for remediation.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Outbound connections to external resources can be monitored and limited at the boundary, reducing SSRF impact.
Detects server-side request forgery through monitoring of unexpected outbound connections.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.