Overview 1 match · 0 in Waratek scope · 0 protected · 0 exploited · 0 CISA KEV · 0 public PoC · 0 EPSS ≥ 0.5
1match
0in Waratek scope0.0%
0protected0.0%
0exploited0.0%
0CISA KEV0.0%
0public PoC0.0%
0EPSS ≥ 0.50.0%
Protected by Waratek
0
0.0%
Rule in development
0
0.0%
Mitigation candidate
0
0.0%
No exploit published
0
0.0%
Outside Waratek scope
0
0.0%
Not applicable
1
100.0%
Withdrawn CVE
0
0.0%
blocked by ARMR today
0
0.0%
partly blocked
0
0.0%
not blocked
1
100.0%
not established
0
0.0%
unrecorded
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0.0%
Exploited
0
0.0%
Working exploit published
0
0.0%
Proof of concept only
1
100.0%
Forecast only
0
0.0%
No public exploit
0
0.0%
| CVE | Severity | Published▾ | Status | Exploitation | Description |
|---|---|---|---|---|---|
| CVE-2020-28975 | High | 2020-11-21 | Not applicable | Proof of concept only | svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 0.23.2 and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the _n_support array. NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute. |