Логотип exploitDog
bind:CVE-2019-20634
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Логотип exploitDog

exploitDog

bind:CVE-2019-20634

Количество 2

Количество 2

nvd логотип

CVE-2019-20634

почти 6 лет назад

An issue was discovered in Proofpoint Email Protection through 2019-09-08. By collecting scores from Proofpoint email headers, it is possible to build a copy-cat Machine Learning Classification model and extract insights from this model. The insights gathered allow an attacker to craft emails that receive preferable scores, with a goal of delivering malicious emails.

CVSS3: 3.7
EPSS: Низкий
github логотип

GHSA-f9h8-wxp6-hpxv

больше 3 лет назад

An issue was discovered in Proofpoint Email Protection through 2019-09-08. By collecting scores from Proofpoint email headers, it is possible to build a copy-cat Machine Learning Classification model and extract insights from this model. The insights gathered allow an attacker to craft emails that receive preferable scores, with a goal of delivering malicious emails.

CVSS3: 3.7
EPSS: Низкий

Уязвимостей на страницу

Уязвимость
CVSS
EPSS
Опубликовано
nvd логотип
CVE-2019-20634

An issue was discovered in Proofpoint Email Protection through 2019-09-08. By collecting scores from Proofpoint email headers, it is possible to build a copy-cat Machine Learning Classification model and extract insights from this model. The insights gathered allow an attacker to craft emails that receive preferable scores, with a goal of delivering malicious emails.

CVSS3: 3.7
0%
Низкий
почти 6 лет назад
github логотип
GHSA-f9h8-wxp6-hpxv

An issue was discovered in Proofpoint Email Protection through 2019-09-08. By collecting scores from Proofpoint email headers, it is possible to build a copy-cat Machine Learning Classification model and extract insights from this model. The insights gathered allow an attacker to craft emails that receive preferable scores, with a goal of delivering malicious emails.

CVSS3: 3.7
0%
Низкий
больше 3 лет назад

Уязвимостей на страницу