FKIE_CVE-2026-108258

Vulnerability from fkie_nvd - Published: 2026-10-09 21:17 - Updated: 2026-10-09 21:17
Summary
Shiny for Python is a framework for building interactive web applications in Python. From 1.4.0 until 1.6.4, bookmark restore accepts a client-supplied state_id and joins it into the server-side shiny_bookmarks directory without validating that it is a single safe path segment. An unauthenticated request can use parent-directory segments or an absolute path to make the server open input.json and values.json outside the bookmark store, even when bookmark_store is set to disable. In applications configured with bookmark_store set to server and using ui.input_file(), the restore handler can additionally copy and expose an attacker-selected file from an attacker-selected directory. This issue is fixed in version 1.6.4.
Impacted products
Vendor Product Version

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "py-shiny",
          "vendor": "posit-dev",
          "versions": [
            {
              "status": "affected",
              "version": "\u003e= 1.4.0, \u003c 1.6.4"
            }
          ]
        }
      ],
      "source": "security-advisories@github.com"
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "Shiny for Python is a framework for building interactive web applications in Python. From 1.4.0 until 1.6.4, bookmark restore accepts a client-supplied state_id and joins it into the server-side shiny_bookmarks directory without validating that it is a single safe path segment. An unauthenticated request can use parent-directory segments or an absolute path to make the server open input.json and values.json outside the bookmark store, even when bookmark_store is set to disable. In applications configured with bookmark_store set to server and using ui.input_file(), the restore handler can additionally copy and expose an attacker-selected file from an attacker-selected directory. This issue is fixed in version 1.6.4."
    }
  ],
  "id": "CVE-2026-108258",
  "lastModified": "2026-10-09T21:17:03.853",
  "metrics": {
    "cvssMetricV40": [
      {
        "cvssData": {
          "Automatable": "NOT_DEFINED",
          "Recovery": "NOT_DEFINED",
          "Safety": "NOT_DEFINED",
          "attackComplexity": "LOW",
          "attackRequirements": "NONE",
          "attackVector": "NETWORK",
          "availabilityRequirement": "NOT_DEFINED",
          "baseScore": 6.9,
          "baseSeverity": "MEDIUM",
          "confidentialityRequirement": "NOT_DEFINED",
          "exploitMaturity": "NOT_DEFINED",
          "integrityRequirement": "NOT_DEFINED",
          "modifiedAttackComplexity": "NOT_DEFINED",
          "modifiedAttackRequirements": "NOT_DEFINED",
          "modifiedAttackVector": "NOT_DEFINED",
          "modifiedPrivilegesRequired": "NOT_DEFINED",
          "modifiedSubAvailabilityImpact": "NOT_DEFINED",
          "modifiedSubConfidentialityImpact": "NOT_DEFINED",
          "modifiedSubIntegrityImpact": "NOT_DEFINED",
          "modifiedUserInteraction": "NOT_DEFINED",
          "modifiedVulnAvailabilityImpact": "NOT_DEFINED",
          "modifiedVulnConfidentialityImpact": "NOT_DEFINED",
          "modifiedVulnIntegrityImpact": "NOT_DEFINED",
          "privilegesRequired": "NONE",
          "providerUrgency": "NOT_DEFINED",
          "subAvailabilityImpact": "NONE",
          "subConfidentialityImpact": "NONE",
          "subIntegrityImpact": "NONE",
          "userInteraction": "NONE",
          "valueDensity": "NOT_DEFINED",
          "vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:N/VA:N/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",
          "version": "4.0",
          "vulnAvailabilityImpact": "NONE",
          "vulnConfidentialityImpact": "LOW",
          "vulnIntegrityImpact": "NONE",
          "vulnerabilityResponseEffort": "NOT_DEFINED"
        },
        "source": "security-advisories@github.com",
        "type": "Secondary"
      }
    ]
  },
  "published": "2026-10-09T21:17:03.853",
  "references": [
    {
      "source": "security-advisories@github.com",
      "url": "https://github.com/posit-dev/py-shiny/commit/1d8ecb46cbc9621b7dc8812111d26692e086b376"
    },
    {
      "source": "security-advisories@github.com",
      "url": "https://github.com/posit-dev/py-shiny/releases/tag/v1.6.4"
    },
    {
      "source": "security-advisories@github.com",
      "url": "https://github.com/posit-dev/py-shiny/security/advisories/GHSA-47c3-hpmg-7j6p"
    }
  ],
  "sourceIdentifier": "security-advisories@github.com",
  "vulnStatus": "Received",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-22"
        }
      ],
      "source": "security-advisories@github.com",
      "type": "Primary"
    }
  ]
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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

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.

Loading…

Loading…

Loading…

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.


Loading…