CVE-2020-27212 (GCVE-0-2020-27212)

Vulnerability from cvelistv5 – Published: 2021-05-21 11:48 – Updated: 2024-08-04 16:11
VLAI
Summary
STMicroelectronics STM32L4 devices through 2020-10-19 have incorrect access control. The flash read-out protection (RDP) can be degraded from RDP level 2 (no access via debug interface) to level 1 (limited access via debug interface) by injecting a fault during the boot phase.
CWE
  • n/a
Show details on NVD website

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                ],
                "negate": false,
                "operator": "OR"
              }
            ],
            "operator": "AND"
          }
        ],
        "cveTags": [],
        "descriptions": [
          {
            "lang": "en",
            "value": "STMicroelectronics STM32L4 devices through 2020-10-19 have incorrect access control. The flash read-out protection (RDP) can be degraded from RDP level 2 (no access via debug interface) to level 1 (limited access via debug interface) by injecting a fault during the boot phase."
          },
          {
            "lang": "es",
            "value": "Los dispositivos STMicroelectronics STM32L4 versi\u00f3n hasta el 2020-10-19, presentan un control de acceso incorrecto.\u0026#xa0;La protecci\u00f3n de lectura flash (RDP) se puede degradar desde el nivel 2 de RDP (sin acceso por medio de la interfaz de depuraci\u00f3n) al nivel 1 (acceso limitado por medio de la interfaz de depuraci\u00f3n) inyectando un fallo durante la fase de arranque"
          }
        ],
        "id": "CVE-2020-27212",
        "lastModified": "2024-11-21T05:20:51.937",
        "metrics": {
          "cvssMetricV2": [
            {
              "acInsufInfo": false,
              "baseSeverity": "MEDIUM",
              "cvssData": {
                "accessComplexity": "MEDIUM",
                "accessVector": "LOCAL",
                "authentication": "NONE",
                "availabilityImpact": "PARTIAL",
                "baseScore": 4.4,
                "confidentialityImpact": "PARTIAL",
                "integrityImpact": "PARTIAL",
                "vectorString": "AV:L/AC:M/Au:N/C:P/I:P/A:P",
                "version": "2.0"
              },
              "exploitabilityScore": 3.4,
              "impactScore": 6.4,
              "obtainAllPrivilege": false,
              "obtainOtherPrivilege": false,
              "obtainUserPrivilege": false,
              "source": "nvd@nist.gov",
              "type": "Primary",
              "userInteractionRequired": false
            }
          ],
          "cvssMetricV31": [
            {
              "cvssData": {
                "attackComplexity": "HIGH",
                "attackVector": "LOCAL",
                "availabilityImpact": "HIGH",
                "baseScore": 7.0,
                "baseSeverity": "HIGH",
                "confidentialityImpact": "HIGH",
                "integrityImpact": "HIGH",
                "privilegesRequired": "LOW",
                "scope": "UNCHANGED",
                "userInteraction": "NONE",
                "vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H",
                "version": "3.1"
              },
              "exploitabilityScore": 1.0,
              "impactScore": 5.9,
              "source": "nvd@nist.gov",
              "type": "Primary"
            }
          ]
        },
        "published": "2021-05-21T12:15:07.730",
        "references": [
          {
            "source": "cve@mitre.org",
            "tags": [
              "Third Party Advisory"
            ],
            "url": "https://eprint.iacr.org/2021/640"
          },
          {
            "source": "cve@mitre.org",
            "tags": [
              "Third Party Advisory"
            ],
            "url": "https://www.aisec.fraunhofer.de/de/das-institut/wissenschaftliche-exzellenz/security-and-trust-in-open-source-security-tokens.html"
          },
          {
            "source": "cve@mitre.org",
            "tags": [
              "Third Party Advisory"
            ],
            "url": "https://www.aisec.fraunhofer.de/en/FirmwareProtection.html"
          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "tags": [
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            "url": "https://eprint.iacr.org/2021/640"
          },
          {
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            "tags": [
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            "url": "https://www.aisec.fraunhofer.de/de/das-institut/wissenschaftliche-exzellenz/security-and-trust-in-open-source-security-tokens.html"
          },
          {
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            "tags": [
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            "url": "https://www.aisec.fraunhofer.de/en/FirmwareProtection.html"
          }
        ],
        "sourceIdentifier": "cve@mitre.org",
        "vulnStatus": "Modified",
        "weaknesses": [
          {
            "description": [
              {
                "lang": "en",
                "value": "CWE-74"
              }
            ],
            "source": "nvd@nist.gov",
            "type": "Primary"
          }
        ]
      }
    }
  }
}



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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.

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.

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Detection rules are retrieved from Rulezet.

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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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