Colosseum
Reports/social-core

social-core

Python Social Auth - Core

python-social-auth904 starsPythonBSD-3-Clause
Scanned: February 16, 2026
Report Version: 1.0.0

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Overall Grade

C

4,816 total findings

Architecture
A55
Correctness
A4
Performance
D2044
Security
D2713

What Traditional Tools Missed

CategoryColosseumBanditSemgrep
Bandit1,9856610
Semgrep1,98504
Total4,8166614

4,816 findings (100%) were not detected by Bandit or Semgrep. These include compound vulnerabilities, logic errors, and context-dependent security issues that rule-based scanners aren't designed to catch.

Notable Findings

CriticalPerformance

Potential hotspot: _compute_expiration_from_relative has high complexity score (12)

Impact: Potential hotspot: _compute_expiration_from_relative has high complexity score (12)
Recommended Fix: Review and remediate.
CriticalPerformance

Potential hotspot: getAssociation has high complexity score (12)

Impact: Potential hotspot: getAssociation has high complexity score (12)
Recommended Fix: Review and remediate.
CriticalPerformance

Potential hotspot: do_disconnect has high complexity score (26)

Impact: Potential hotspot: do_disconnect has high complexity score (26)
Recommended Fix: Review and remediate.
CriticalPerformance

Potential hotspot: refresh_token has high complexity score (10)

Impact: Potential hotspot: refresh_token has high complexity score (10)
Recommended Fix: Review and remediate.
CriticalPerformance

Potential hotspot: do_complete has high complexity score (47)

Impact: Potential hotspot: do_complete has high complexity score (47)
Recommended Fix: Review and remediate.
CriticalPerformance

Potential hotspot: do_auth has high complexity score (19)

Impact: Potential hotspot: do_auth has high complexity score (19)
Recommended Fix: Review and remediate.
CriticalPerformance

Potential hotspot: drop_lists has high complexity score (10)

Impact: Potential hotspot: drop_lists has high complexity score (10)
Recommended Fix: Review and remediate.
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Responsible Disclosure

This public report is intended to demonstrate the depth of analysis possible with modern code scanning tools and to help the broader open source community understand common vulnerability patterns.

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