cve-2024-1544
Vulnerability from cvelistv5
Published
2024-08-27 18:44
Modified
2024-08-27 19:14
Severity ?
EPSS score ?
Summary
Generating the ECDSA nonce k samples a random number r and then
truncates this randomness with a modular reduction mod n where n is the
order of the elliptic curve. Meaning k = r mod n. The division used
during the reduction estimates a factor q_e by dividing the upper two
digits (a digit having e.g. a size of 8 byte) of r by the upper digit of
n and then decrements q_e in a loop until it has the correct size.
Observing the number of times q_e is decremented through a control-flow
revealing side-channel reveals a bias in the most significant bits of
k. Depending on the curve this is either a negligible bias or a
significant bias large enough to reconstruct k with lattice reduction
methods. For SECP160R1, e.g., we find a bias of 15 bits.
References
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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. 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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.\"},{\"lang\":\"es\",\"value\":\"Generar el nonce k ECDSA muestra un n\u00famero aleatorio r y luego trunca esta aleatoriedad con una reducci\u00f3n modular mod n donde n es el orden de la curva el\u00edptica. Significado k = r mod n. La divisi\u00f3n utilizada durante la reducci\u00f3n estima un factor q_e dividiendo los dos d\u00edgitos superiores (un d\u00edgito que tiene, por ejemplo, un tama\u00f1o de 8 bytes) de r por el d\u00edgito superior de n y luego disminuye q_e en un bucle hasta que tenga el tama\u00f1o correcto. Observar el n\u00famero de veces que q_e disminuye a trav\u00e9s de un canal lateral revelador de flujo de control revela un sesgo en los bits m\u00e1s significativos de k. Dependiendo de la curva, esto es un sesgo insignificante o un sesgo significativo lo suficientemente grande como para reconstruir k con m\u00e9todos de reducci\u00f3n de celos\u00eda. Para SECP160R1, por ejemplo, encontramos un sesgo de 15 bits.\"}],\"metrics\":{\"cvssMetricV31\":[{\"source\":\"facts@wolfssl.com\",\"type\":\"Secondary\",\"cvssData\":{\"version\":\"3.1\",\"vectorString\":\"CVSS:3.1/AV:L/AC:H/PR:H/UI:N/S:U/C:H/I:N/A:N\",\"baseScore\":4.1,\"baseSeverity\":\"MEDIUM\",\"attackVector\":\"LOCAL\",\"attackComplexity\":\"HIGH\",\"privilegesRequired\":\"HIGH\",\"userInteraction\":\"NONE\",\"scope\":\"UNCHANGED\",\"confidentialityImpact\":\"HIGH\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"NONE\"},\"exploitabilityScore\":0.5,\"impactScore\":3.6}]},\"weaknesses\":[{\"source\":\"facts@wolfssl.com\",\"type\":\"Secondary\",\"description\":[{\"lang\":\"en\",\"value\":\"CWE-203\"}]}],\"references\":[{\"url\":\"https://github.com/wolfSSL/wolfssl/releases/tag/v5.7.2-stable\",\"source\":\"facts@wolfssl.com\"}]}}" } }
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Sightings
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