CVE-2016-5636 Details
Integer overflow in the get_data function in zipimport.c in CPython (aka Python) before 2.7.12, 3.x before 3.4.5, and 3.5.x before 3.5.2 allows remote attackers to have unspecified impact via a negative data size value, which triggers a heap-based buffer overflow.
View at NVD
Exploit prediction scoring system (EPSS) score for CVE-2016-5636
EPSS (Exploit Prediction Scoring System): EPSS predicts the likelihood that a vulnerability will be exploited in the wild. A higher percentage means a greater chance of an exploit occurring. The EPSS model produces a probability score between 0 and 1 (0 and 100%).
63.69 Probability of exploitation activity being observed over the next 30 days (98th percentile)
CVSS score for CVE-2016-5636
CVSS (Common Vulnerability Scoring System): An open framework owned and managed by FIRST.Org, Inc. that assigns a numerical score from 0 to 10 to software vulnerabilities to indicate their severity.
9.8 Critical
Products affected by CVE-2016-5636
Python 2.7.6
Python 2.7.7
Python 2.7.8
Python 2.7.9
Python 3.1.3
DVE Score by Bitsight AI
DVE scores complement traditional static scoring systems like CVSS with Bitsight AI powered real-time threat intelligence and underground cyber criminal activity so that security teams can reduce alert fatigue and focus on vulnerabilities most likely to be exploited.
Not available
More on DVE scores

CVE-2016-5636 Global Footprint

Top 10 Identified Countries

Country Observations Percentage
NL 12,577 16.66%
US 11,593 15.36%
DE 10,187 13.49%
CN 6,202 8.22%
JP 4,261 5.64%
KR 2,953 3.91%
IT 1,884 2.50%
FR 1,874 2.48%
CA 1,670 2.21%
GB 1,594 2.11%

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CVE-2016-5636 Industry Footprint

Top 10 Identified Industries

*Service provider organizations (typically Technology and Telecommunications) are disproportionally represented in the results given their upstream ownership of end-user infrastructure. See our FAQs.

Industry* Observations Percentage
Technology 22,286 61.58%
Telecommunications 8,401 23.21%
Education 3,213 8.88%
Energy/Resources 511 1.41%
Government/Politics 504 1.39%
Media/Entertainment 364 1.01%
Business Services 298 0.82%
Legal 142 0.39%
Transportation 81 0.22%
Retail 62 0.17%

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