CVE-2023-43364 (GCVE-0-2023-43364)

Vulnerability from cvelistv5 – Published: 2023-12-12 00:00 – Updated: 2024-10-09 13:30
VLAI
Summary
main.py in Searchor before 2.4.2 uses eval on CLI input, which may cause unexpected code execution.
SSVC
Exploitation: poc Automatable: yes Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-10-09 13:28 UTC
CWE
  • n/a
  • CWE-94 - Improper Control of Generation of Code ('Code Injection')
Show details on NVD website

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        "assignerOrgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
        "assignerShortName": "mitre",
        "cveId": "CVE-2023-43364",
        "datePublished": "2023-12-12T00:00:00.000Z",
        "dateReserved": "2023-09-18T00:00:00.000Z",
        "dateUpdated": "2024-10-09T13:30:12.973Z",
        "state": "PUBLISHED"
      },
      "dataType": "CVE_RECORD",
      "dataVersion": "5.1"
    }
  }
}



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Tags
Taxonomy of the tags.


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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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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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