{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2024-1544",
                "options": [
                  {
                    "Exploitation": "none"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2024-08-27T19:14:00.889289Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2024-08-27T19:14:35.190Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "defaultStatus": "unknown",
          "product": "wolfSSL",
          "programFiles": [
            "wolfcrypt/src/ecc.c"
          ],
          "vendor": "wolfSSL",
          "versions": [
            {
              "lessThanOrEqual": "5.6.4",
              "status": "affected",
              "version": "0",
              "versionType": "Release"
            }
          ]
        }
      ],
      "credits": [
        {
          "lang": "en",
          "type": "finder",
          "user": "00000000-0000-4000-9000-000000000000",
          "value": "Florian Sieck, Luca Wilke and Thomas Eisenbarth from Universit\u00e4t zu L\u00fcbeck"
        }
      ],
      "datePublic": "2024-07-08T17:30:00.000Z",
      "descriptions": [
        {
          "lang": "en",
          "supportingMedia": [
            {
              "base64": false,
              "type": "text/html",
              "value": "Generating the ECDSA nonce k samples a random number r and then \u003cbr\u003etruncates this randomness with a modular reduction mod n where n is the \u003cbr\u003eorder of the elliptic curve. Meaning k = r mod n. The division used \u003cbr\u003eduring the reduction estimates a factor q_e by dividing the upper two \u003cbr\u003edigits (a digit having e.g. a size of 8 byte) of r by the upper digit of \u003cbr\u003en and then decrements q_e in a loop until it has the correct size. \u003cbr\u003eObserving the number of times q_e is decremented through a control-flow \u003cbr\u003erevealing side-channel reveals a bias in the most significant bits of \u003cbr\u003ek. Depending on the curve this is either a negligible bias or a \u003cbr\u003esignificant bias large enough to reconstruct k with lattice reduction \u003cbr\u003emethods. For SECP160R1, e.g., we find a bias of 15 bits."
            }
          ],
          "value": "Generating the ECDSA nonce k samples a random number r and then \ntruncates this randomness with a modular reduction mod n where n is the \norder of the elliptic curve. Meaning k = r mod n. The division used \nduring the reduction estimates a factor q_e by dividing the upper two \ndigits (a digit having e.g. a size of 8 byte) of r by the upper digit of \nn and then decrements q_e in a loop until it has the correct size. \nObserving the number of times q_e is decremented through a control-flow \nrevealing side-channel reveals a bias in the most significant bits of \nk. Depending on the curve this is either a negligible bias or a \nsignificant bias large enough to reconstruct k with lattice reduction \nmethods. For SECP160R1, e.g., we find a bias of 15 bits."
        }
      ],
      "impacts": [
        {
          "descriptions": [
            {
              "lang": "en",
              "value": "Information Disclosure"
            }
          ]
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "HIGH",
            "attackVector": "LOCAL",
            "availabilityImpact": "NONE",
            "baseScore": 4.1,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "NONE",
            "privilegesRequired": "HIGH",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:L/AC:H/PR:H/UI:N/S:U/C:H/I:N/A:N",
            "version": "3.1"
          },
          "format": "CVSS",
          "scenarios": [
            {
              "lang": "en",
              "value": "GENERAL"
            }
          ]
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-203",
              "description": "CWE-203 Observable Discrepancy",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2026-01-27T21:58:42.146Z",
        "orgId": "50d2cd11-d01a-48ed-9441-5bfce9d63b27",
        "shortName": "wolfSSL"
      },
      "references": [
        {
          "url": "https://github.com/wolfSSL/wolfssl/releases/tag/v5.7.2-stable"
        },
        {
          "url": "https://github.com/wolfSSL/wolfssl/pull/7020"
        }
      ],
      "source": {
        "discovery": "EXTERNAL"
      },
      "title": "ECDSA nonce bias caused by truncation",
      "x_generator": {
        "engine": "Vulnogram 0.1.0-dev"
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "50d2cd11-d01a-48ed-9441-5bfce9d63b27",
    "assignerShortName": "wolfSSL",
    "cveId": "CVE-2024-1544",
    "datePublished": "2024-08-27T18:44:52.770Z",
    "dateReserved": "2024-02-15T17:38:16.603Z",
    "dateUpdated": "2026-01-27T21:58:42.146Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2"
}