CVE-2008-4864 (GCVE-0-2008-4864)

Vulnerability from cvelistv5 – Published: 2008-10-31 22:00 – Updated: 2024-08-07 10:31
VLAI
Summary
Multiple integer overflows in imageop.c in the imageop module in Python 1.5.2 through 2.5.1 allow context-dependent attackers to break out of the Python VM and execute arbitrary code via large integer values in certain arguments to the crop function, leading to a buffer overflow, a different vulnerability than CVE-2007-4965 and CVE-2008-1679.
Severity
No CVSS data available.
CWE
  • n/a
Date Public
2008-10-27 00:00
Show details on NVD website

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      "current_release_date": "2025-11-21T13:14:28+00:00",
      "cve": "CVE-2008-4864",
      "id": "CVE-2008-4864",
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      "source": "Red Hat CSAF VEX",
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      "id": "CVE-2008-4864",
      "initial_release_date": "2023-02-15T06:06:40Z",
      "product_status:known_not_affected": "593",
      "source": "SUSE CSAF VEX",
      "status": "interim",
      "title": "SUSE CVE CVE-2008-4864",
      "url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2008-4864.json",
      "version": "18"
    }
  }
}



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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

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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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