Vulnerability-Lookup

GSD-2018-16647

Vulnerability from gsd - Updated: 2023-12-13 01:22

Details

In Artifex MuPDF 1.13.0, the pdf_get_xref_entry function in pdf/pdf-xref.c allows remote attackers to cause a denial of service (segmentation fault in fz_write_data in fitz/output.c) via a crafted pdf file.

Aliases

CVE-2018-16647

Aliases

CVE-2018-16647

JSON

To clipboard

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    "alias": "CVE-2018-16647",
    "description": "In Artifex MuPDF 1.13.0, the pdf_get_xref_entry function in pdf/pdf-xref.c allows remote attackers to cause a denial of service (segmentation fault in fz_write_data in fitz/output.c) via a crafted pdf file.",
    "id": "GSD-2018-16647",
    "references": [
      "https://www.suse.com/security/cve/CVE-2018-16647.html"
    ]
  },
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      "remediation": "unknown",
      "reportConfidence": "confirmed",
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}

CVE-2018-16647 (GCVE-0-2018-16647)

Vulnerability from cvelistv5 – Published: 2018-09-06 23:00 – Updated: 2024-09-12 16:17

Summary

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

3 references

URL	Tags
https://bugs.ghostscript.com/show_bug.cgi?id=699686
https://lists.debian.org/debian-lts-announce/2020…	mailing-list
https://cgit.ghostscript.com/cgi-bin/cgit.cgi/mup…

Date Public

2018-09-06 00:00

Show details on NVD website

JSON

To clipboard

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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.

Detection rules are retrieved from Rulezet.

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.

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.