FKIE_CVE-2026-31221

Vulnerability from fkie_nvd - Published: 2026-05-12 16:16 - Updated: 2026-05-15 19:16
Summary
PyTorch-Lightning versions 2.6.0 and earlier contain an insecure deserialization vulnerability (CWE-502) in the checkpoint loading mechanism. The LightningModule.load_from_checkpoint() method, which is commonly used to load saved model states, internally calls torch.load() without setting the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the Pickle module. A remote attacker can exploit this by providing a maliciously crafted checkpoint file, leading to arbitrary code execution on the victim's system when the file is loaded.
Impacted products
Vendor Product Version
lightningai pytorch_lightning *

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  "descriptions": [
    {
      "lang": "en",
      "value": "PyTorch-Lightning versions 2.6.0 and earlier contain an insecure deserialization vulnerability (CWE-502) in the checkpoint loading mechanism. The LightningModule.load_from_checkpoint() method, which is commonly used to load saved model states, internally calls torch.load() without setting the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the Pickle module. A remote attacker can exploit this by providing a maliciously crafted checkpoint file, leading to arbitrary code execution on the victim\u0027s system when the file is loaded."
    }
  ],
  "id": "CVE-2026-31221",
  "lastModified": "2026-05-15T19:16:57.333",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "LOCAL",
          "availabilityImpact": "HIGH",
          "baseScore": 7.8,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
          "version": "3.1"
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        "source": "nvd@nist.gov",
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          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
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          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
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  "published": "2026-05-12T16:16:14.020",
  "references": [
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      "source": "cve@mitre.org",
      "tags": [
        "Product"
      ],
      "url": "https://github.com/Lightning-AI/pytorch-lightning"
    },
    {
      "source": "cve@mitre.org",
      "tags": [
        "Exploit",
        "Third Party Advisory"
      ],
      "url": "https://www.notion.so/CVE-2026-31221-35d1e1393188815f8db7c4fd08076639"
    }
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  "sourceIdentifier": "cve@mitre.org",
  "vulnStatus": "Modified",
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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.

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