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CVE-2024-48057 (GCVE-0-2024-48057)

Vulnerability from cvelistv5 – Published: 2024-11-04 00:00 – Updated: 2024-11-05 17:28
VLAI
Summary
localai <=2.20.1 is vulnerable to Cross Site Scripting (XSS). When calling the delete model API and passing inappropriate parameters, it can cause a one-time storage XSS, which will trigger the payload when a user accesses the homepage.
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-11-05 17:27 UTC
CWE
  • n/a
  • CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
  • CWE-352 - Cross-Site Request Forgery (CSRF)
Impacted products
Vendor Product Version CPE status
mudler localai Affected: 0 , ≤ 2.20.1 (custom)
    cpe:2.3:a:mudler:localai:*:*:*:*:*:*:*:*
Create a notification for this product.
Show details on NVD website

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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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Detection rules are retrieved from Rulezet.

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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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