Vulnerability-Lookup

GHSA-FMHH-RW3H-785M

Vulnerability from github – Published: 2025-04-09 12:57 – Updated: 2025-04-09 12:57

Summary

bep/imagemeta allows a potentially large memory allocation in PNG and WebP parsing

Details

Impact

The buffer created for parsing metadata for PNG and WebP images was only bounded by their input data type, which could lead to potentially large memory allocation, and unreasonably high for image metadata. Before v0.11.0, If you didn't trust the input images, this could be abused to construct denial-of-service attacks.

Patches

v0.11.0 added a 10 MB upper limit.

Severity

6.9 (Medium)


                  
                    CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

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JSON

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{
  "affected": [
    {
      "package": {
        "ecosystem": "Go",
        "name": "github.com/bep/imagemeta"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0.11.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2025-32025"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2025-04-09T12:57:56Z",
    "nvd_published_at": "2025-04-08T16:15:27Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\n\nThe buffer created for parsing metadata for PNG and WebP images was only bounded by their input data type, which could lead to potentially large memory allocation, and unreasonably high for image metadata. Before `v0.11.0`, If you didn\u0027t trust the input images, this could be abused to construct denial-of-service attacks.\n\n### Patches\n\n`v0.11.0` added a 10 MB upper limit.",
  "id": "GHSA-fmhh-rw3h-785m",
  "modified": "2025-04-09T12:57:56Z",
  "published": "2025-04-09T12:57:56Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/bep/imagemeta/security/advisories/GHSA-fmhh-rw3h-785m"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-32025"
    },
    {
      "type": "WEB",
      "url": "https://github.com/bep/imagemeta/commit/ee0de9b029f4e82106729f69559f27c9a404229d"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/bep/imagemeta"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
      "type": "CVSS_V4"
    }
  ],
  "summary": "bep/imagemeta allows a potentially large memory allocation in PNG and WebP parsing"
}

CVE-2025-32025 (GCVE-0-2025-32025)

Vulnerability from cvelistv5 – Published: 2025-04-08 15:13 – Updated: 2025-04-08 15:37

Title

bep/imagemeta allows a potentially large memory allocation in PNG and WebP parsing

Summary

bep/imagemeta is a Go library for reading EXIF, IPTC and XMP image meta data from JPEG, TIFF, PNG, and WebP files. The buffer created for parsing metadata for PNG and WebP images was only bounded by their input data type, which could lead to potentially large memory allocation, and unreasonably high for image metadata. Before v0.11.0, If you didn't trust the input images, this could be abused to construct denial-of-service attacks. v0.11.0 added a 10 MB upper limit.

Severity

6.9 (Medium)


                        
                          CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

SSVC

Exploitation: none Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-04-08 15:37 UTC

CWE

CWE-770 - Allocation of Resources Without Limits or Throttling

Assigner

GitHub_M CNA under the mitre root

CNA scorecard C 72/100 over 7639 records in the last 180 days details

References

2 references

URL	Tags
https://github.com/bep/imagemeta/security/advisor…	x_refsource_CONFIRM
https://github.com/bep/imagemeta/commit/ee0de9b02…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
bep	imagemeta	Affected: < v0.11.0

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2025-32025",
                "options": [
                  {
                    "Exploitation": "none"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-04-08T15:37:48.564851Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-04-08T15:37:58.737Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "imagemeta",
          "vendor": "bep",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c v0.11.0"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "bep/imagemeta is a Go library for reading EXIF, IPTC and XMP image meta data from JPEG, TIFF, PNG, and WebP files. The buffer created for parsing metadata for PNG and WebP images was only bounded by their input data type, which could lead to potentially large memory allocation, and unreasonably high for image metadata. Before v0.11.0, If you didn\u0027t trust the input images, this could be abused to construct denial-of-service attacks. v0.11.0 added a 10 MB upper limit."
        }
      ],
      "metrics": [
        {
          "cvssV4_0": {
            "attackComplexity": "LOW",
            "attackRequirements": "NONE",
            "attackVector": "LOCAL",
            "baseScore": 6.9,
            "baseSeverity": "MEDIUM",
            "privilegesRequired": "NONE",
            "subAvailabilityImpact": "NONE",
            "subConfidentialityImpact": "NONE",
            "subIntegrityImpact": "NONE",
            "userInteraction": "NONE",
            "vectorString": "CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
            "version": "4.0",
            "vulnAvailabilityImpact": "HIGH",
            "vulnConfidentialityImpact": "NONE",
            "vulnIntegrityImpact": "NONE"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-770",
              "description": "CWE-770: Allocation of Resources Without Limits or Throttling",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2025-04-08T15:13:24.770Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "name": "https://github.com/bep/imagemeta/security/advisories/GHSA-fmhh-rw3h-785m",
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/bep/imagemeta/security/advisories/GHSA-fmhh-rw3h-785m"
        },
        {
          "name": "https://github.com/bep/imagemeta/commit/ee0de9b029f4e82106729f69559f27c9a404229d",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/bep/imagemeta/commit/ee0de9b029f4e82106729f69559f27c9a404229d"
        }
      ],
      "source": {
        "advisory": "GHSA-fmhh-rw3h-785m",
        "discovery": "UNKNOWN"
      },
      "title": "bep/imagemeta allows a potentially large memory allocation in PNG and WebP parsing"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2025-32025",
    "datePublished": "2025-04-08T15:13:24.770Z",
    "dateReserved": "2025-04-01T21:57:32.955Z",
    "dateUpdated": "2025-04-08T15:37:58.737Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

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.

Vulnerability timeline

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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.

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