Vulnerability-Lookup

PYSEC-2026-3856

Vulnerability from pysec - Published: 2026-09-10 09:44 - Updated: 2026-09-10 11:02

Details

A vulnerability in keras-team/keras versions < 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.getitem method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models.

Severity

5.5 (Medium)


                  
                    CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H

Impacted products

Name	purl
keras	pkg:pypi/keras

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "keras",
        "purl": "pkg:pypi/keras"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.15.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.2.0",
        "0.3.0",
        "0.3.1",
        "0.3.2",
        "0.3.3",
        "1.0.0",
        "1.0.1",
        "1.0.2",
        "1.0.3",
        "1.0.4",
        "1.0.5",
        "1.0.6",
        "1.0.7",
        "1.0.8",
        "1.1.0",
        "1.1.1",
        "1.1.2",
        "1.2.0",
        "1.2.1",
        "1.2.2",
        "2.0.0",
        "2.0.1",
        "2.0.2",
        "2.0.3",
        "2.0.4",
        "2.0.5",
        "2.0.6",
        "2.0.7",
        "2.0.8",
        "2.0.9",
        "2.1.0",
        "2.1.1",
        "2.1.2",
        "2.1.3",
        "2.1.4",
        "2.1.5",
        "2.1.6",
        "2.10.0",
        "2.10.0rc0",
        "2.10.0rc1",
        "2.11.0",
        "2.11.0rc0",
        "2.11.0rc1",
        "2.11.0rc2",
        "2.11.0rc3",
        "2.12.0",
        "2.12.0rc0",
        "2.12.0rc1",
        "2.13.1",
        "2.13.1rc0",
        "2.13.1rc1",
        "2.14.0",
        "2.14.0rc0",
        "2.15.0",
        "2.15.0rc0",
        "2.15.0rc1",
        "2.2.0",
        "2.2.1",
        "2.2.2",
        "2.2.3",
        "2.2.4",
        "2.2.5",
        "2.3.0",
        "2.3.1",
        "2.4.0",
        "2.4.1",
        "2.4.2",
        "2.4.3",
        "2.5.0rc0",
        "2.6.0",
        "2.6.0rc0",
        "2.6.0rc1",
        "2.6.0rc2",
        "2.6.0rc3",
        "2.7.0",
        "2.7.0rc0",
        "2.7.0rc2",
        "2.8.0",
        "2.8.0rc0",
        "2.8.0rc1",
        "2.9.0",
        "2.9.0rc0",
        "2.9.0rc1",
        "2.9.0rc2",
        "3.0.0",
        "3.0.1",
        "3.0.2",
        "3.0.3",
        "3.0.4",
        "3.0.5",
        "3.1.0",
        "3.1.1",
        "3.10.0",
        "3.11.0",
        "3.11.1",
        "3.11.2",
        "3.11.3",
        "3.12.0",
        "3.12.1",
        "3.12.2",
        "3.12.3",
        "3.12.4",
        "3.13.0",
        "3.13.1",
        "3.13.2",
        "3.14.0",
        "3.14.1",
        "3.2.0",
        "3.2.1",
        "3.3.0",
        "3.3.1",
        "3.3.2",
        "3.3.3",
        "3.4.0",
        "3.4.1",
        "3.5.0",
        "3.6.0",
        "3.7.0",
        "3.8.0",
        "3.9.0",
        "3.9.1",
        "3.9.2"
      ]
    }
  ],
  "aliases": [
    "CVE-2026-12570",
    "GHSA-74m6-m3xx-3vmj"
  ],
  "details": "A vulnerability in keras-team/keras versions \u003c 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models.",
  "id": "PYSEC-2026-3856",
  "modified": "2026-09-10T11:02:11.020664Z",
  "published": "2026-09-10T09:44:51.470942Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-12570"
    },
    {
      "type": "WEB",
      "url": "https://github.com/keras-team/keras/pull/22975"
    },
    {
      "type": "WEB",
      "url": "https://github.com/keras-team/keras/commit/4933ea4a5b3fcc24ceacdc276f5bb5dfbd06756c"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/keras-team/keras"
    },
    {
      "type": "WEB",
      "url": "https://github.com/keras-team/keras/releases/tag/v3.15.0"
    },
    {
      "type": "WEB",
      "url": "https://huntr.com/bounties/a064f475-780a-409a-82f7-678512f27ad8"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/keras"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-74m6-m3xx-3vmj"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Keras model loading is vulnerable to denial of service through HDF5 shape bombs"
}

CVE-2026-12570 (GCVE-0-2026-12570)

Vulnerability from cvelistv5 – Published: 2026-08-10 06:29 – Updated: 2026-08-10 17:37

Title

Denial of Service via HDF5 Shape Bomb in keras.models.load_model() in keras-team/keras

Summary

A vulnerability in keras-team/keras versions <= 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models.

Severity

5.5 (Medium)


                        
                          CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H

SSVC

Exploitation: poc Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-08-10 17:37 UTC

CWE

CWE-770 - Allocation of Resources Without Limits or Throttling

Assigner

@huntr_ai mitre root

References

2 references

URL	Tags
https://huntr.com/bounties/a064f475-780a-409a-82f…
https://github.com/keras-team/keras/commit/4933ea…

Impacted products

1 product

Vendor	Product	Version
keras-team	keras-team/keras	Affected: unspecified , < 3.12.3, 3.15.0 (custom)

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2026-12570",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-08-10T17:37:17.637683Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2026-08-10T17:37:39.037Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "references": [
          {
            "tags": [
              "exploit"
            ],
            "url": "https://huntr.com/bounties/a064f475-780a-409a-82f7-678512f27ad8"
          }
        ],
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "keras-team/keras",
          "vendor": "keras-team",
          "versions": [
            {
              "lessThan": "3.12.3, 3.15.0",
              "status": "affected",
              "version": "unspecified",
              "versionType": "custom"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "A vulnerability in keras-team/keras versions \u003c= 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models."
        }
      ],
      "metrics": [
        {
          "cvssV3_0": {
            "attackComplexity": "LOW",
            "attackVector": "LOCAL",
            "availabilityImpact": "HIGH",
            "baseScore": 5.5,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "REQUIRED",
            "vectorString": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
            "version": "3.0"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-770",
              "description": "CWE-770 Allocation of Resources Without Limits or Throttling",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2026-08-10T06:29:56.111Z",
        "orgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
        "shortName": "@huntr_ai"
      },
      "references": [
        {
          "url": "https://huntr.com/bounties/a064f475-780a-409a-82f7-678512f27ad8"
        },
        {
          "url": "https://github.com/keras-team/keras/commit/4933ea4a5b3fcc24ceacdc276f5bb5dfbd06756c"
        }
      ],
      "source": {
        "advisory": "a064f475-780a-409a-82f7-678512f27ad8",
        "discovery": "EXTERNAL"
      },
      "title": "Denial of Service via HDF5 Shape Bomb in keras.models.load_model() in keras-team/keras"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
    "assignerShortName": "@huntr_ai",
    "cveId": "CVE-2026-12570",
    "datePublished": "2026-08-10T06:29:56.111Z",
    "dateReserved": "2026-06-18T01:55:25.311Z",
    "dateUpdated": "2026-08-10T17:37:39.037Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2"
}

GHSA-74M6-M3XX-3VMJ

Vulnerability from github – Published: 2026-08-10 09:31 – Updated: 2026-09-01 20:22

Summary

Keras model loading is vulnerable to denial of service through HDF5 shape bombs

Details

Severity

5.5 (Medium)


                  
                    CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "keras"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.15.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-12570"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-09-01T20:22:06Z",
    "nvd_published_at": "2026-08-10T07:16:44Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability in keras-team/keras versions \u003c 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models.",
  "id": "GHSA-74m6-m3xx-3vmj",
  "modified": "2026-09-01T20:22:06Z",
  "published": "2026-08-10T09:31:20Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-12570"
    },
    {
      "type": "WEB",
      "url": "https://github.com/keras-team/keras/pull/22975"
    },
    {
      "type": "WEB",
      "url": "https://github.com/keras-team/keras/commit/4933ea4a5b3fcc24ceacdc276f5bb5dfbd06756c"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/keras-team/keras"
    },
    {
      "type": "WEB",
      "url": "https://github.com/keras-team/keras/releases/tag/v3.15.0"
    },
    {
      "type": "WEB",
      "url": "https://huntr.com/bounties/a064f475-780a-409a-82f7-678512f27ad8"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Keras model loading is vulnerable to denial of service through HDF5 shape bombs"
}

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.

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.

Action not permitted

PYSEC-2026-3856

CVE-2026-12570 (GCVE-0-2026-12570)

GHSA-74M6-M3XX-3VMJ

Tags

Sightings

Nomenclature

Related by attack behaviour