CVE-2019-20634
An issue was discovered in Proofpoint Email Protection through 2019-09-08. By collecting scores...
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.
Attack profile
How easy it is to exploit
- Attack vector
- Network
- Complexity
- High
- Privileges needed
- None
- User interaction
- None
What an attacker can affect
- Confidentiality
- Low
- Integrity
- None
- Availability
- None
Exploit likelihood
What each source reports
CVE List Score used
3.7
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.
- Record
CVE-2019-20634- CVSS 3.1
- 3.7 Low
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:N/A:N - Updated
- 2026-11-02
EUVDEUVD-2019-11173
3.7
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.
- Record
EUVD-2019-11173- CVSS 3.1
- 3.7 Low
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:N/A:N - Updated
- 2026-11-03
GitHub AdvisoriesGHSA-f9h8-wxp6-hpxv
3.7
An issue was discovered in Proofpoint Email Protection through 2019-09-08. By collecting scores...
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.
- Record
GHSA-f9h8-wxp6-hpxv- CVSS 3.1
- 3.7 Low
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:N/A:N - Weakness
- CWE-20, CWE-697
- Updated
- 2026-11-02
NVD
3.7
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.
- Record
CVE-2019-20634- CVSS 3.1
- 3.7 Low
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:N/A:N - CVSS 2.0
- 4.3 Medium
AV:N/AC:M/Au:N/C:P/I:N/A:N - Weakness
- CWE-697
- Updated
- 2026-11-02
Affected products
History
| Recorded | Changed | Sources |
|---|---|---|
| aliases | EUVD | |
| first indexed | CVE List, GitHub Advisories, NVD |
Dates are when Every CVE recorded each change. Upstream dates may differ.
In short
CVE-2019-20634 is a low vulnerability (CVSS 3.7) in Proofpoint Email Protection, published March 30, 2020. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 1.64%, the 76th percentile. No source names a fixed version.
References
github.com/moohax/Proof-Pudding
github.com/moohax/Talks/blob/master/slides/DerbyCon19.pdf
proofpoint.com/us/security/CVE-2019-20634
proofpoint.com/us/security/security-advisories/pfpt-sn-2020-0001
atlas.mitre.org/studies/AML.CS0008
nvd.nist.gov/vuln/detail/CVE-2019-20634
github.com/advisories/GHSA-f9h8-wxp6-hpxv