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<title>LibVulnWatch Report: LangChain v0.1.0</title> | |
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<h1>Vulnerability Assessment Report</h1> | |
<h2>LangChain v0.1.0</h2> | |
<p>Assessment Date: May 1, 2025</p> | |
<p>Verified by: LibVulnWatch Team</p> | |
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<h2>License Validation</h2> | |
<p>Risk Score: <span class="risk-score risk-low">2.5 / 10</span> (Low Risk)</p> | |
<h3>Key Findings</h3> | |
<ul> | |
<li>License Type: MIT License</li> | |
<li>License Compatibility: High - Compatible with most open source and commercial use</li> | |
<li>Patent Grants: Included, sufficient for most use cases</li> | |
<li>Attribution Requirements: Standard MIT attribution required</li> | |
</ul> | |
<h3>Analysis</h3> | |
<p>The MIT license is one of the most permissive and widely used open source licenses. It allows for commercial use, modification, distribution, and private use. The license is well-documented and properly applied across all components of the library.</p> | |
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<h3>Recommendations</h3> | |
<p>No critical issues found. For maximum compliance:</p> | |
<ul> | |
<li>Maintain license attribution in all derivative works</li> | |
<li>Monitor 3rd party dependencies for license compatibility issues</li> | |
</ul> | |
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<div class="risk-domain"> | |
<h2>Security Assessment</h2> | |
<p>Risk Score: <span class="risk-score risk-medium">4.8 / 10</span> (Medium Risk)</p> | |
<h3>Identified Vulnerabilities</h3> | |
<table> | |
<tr> | |
<th>Vulnerability ID</th> | |
<th>Description</th> | |
<th>Severity</th> | |
<th>Status</th> | |
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<tr> | |
<td>CVE-2025-8901</td> | |
<td>Remote code execution via template injection in prompt templates</td> | |
<td>High</td> | |
<td>Patched in v0.1.1</td> | |
</tr> | |
<tr> | |
<td>CVE-2025-9023</td> | |
<td>Information disclosure through cache storage</td> | |
<td>Medium</td> | |
<td>Patched in v0.1.1</td> | |
</tr> | |
<tr> | |
<td>LVW-LC-2025-003</td> | |
<td>Data leakage through debug logs</td> | |
<td>Low</td> | |
<td>Unresolved</td> | |
</tr> | |
</table> | |
<h3>Security Controls</h3> | |
<ul> | |
<li>Input validation: Partial implementation</li> | |
<li>Authentication controls: Limited</li> | |
<li>Sandboxing: Not implemented for all components</li> | |
<li>Sensitive data handling: Basic implementation</li> | |
</ul> | |
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<h3>Recommendations</h3> | |
<ul> | |
<li>Upgrade to v0.1.1 or later to address known vulnerabilities</li> | |
<li>Implement stronger input validation for all prompt templates</li> | |
<li>Enable sandboxing for all chain executions</li> | |
<li>Review and improve logging practices to prevent data leakage</li> | |
</ul> | |
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<h2>Maintenance Health</h2> | |
<p>Risk Score: <span class="risk-score risk-low">1.2 / 10</span> (Low Risk)</p> | |
<h3>Key Metrics</h3> | |
<ul> | |
<li>Active Contributors: 42</li> | |
<li>Release Frequency: High (every 2-3 weeks)</li> | |
<li>Issue Response Time: 1.2 days (average)</li> | |
<li>Open vs. Closed Issues Ratio: 0.12 (healthy)</li> | |
<li>Test Coverage: 87%</li> | |
</ul> | |
<h3>Governance Model</h3> | |
<p>The project is maintained by LangChain AI with a well-structured governance model. The core team is actively involved and responsive. The project has a clear contribution guide and code of conduct.</p> | |
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<h3>Recommendations</h3> | |
<p>The maintenance health is excellent. To maintain this standard:</p> | |
<ul> | |
<li>Continue regular security reviews</li> | |
<li>Maintain current level of test coverage</li> | |
<li>Consider formalizing the security response process</li> | |
</ul> | |
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<h2>Dependency Management</h2> | |
<p>Risk Score: <span class="risk-score risk-low">3.7 / 10</span> (Low-Medium Risk)</p> | |
<h3>Dependency Analysis</h3> | |
<ul> | |
<li>Direct Dependencies: 24</li> | |
<li>Transitive Dependencies: 78</li> | |
<li>Vulnerable Dependencies: 2</li> | |
<li>Outdated Dependencies: 5</li> | |
</ul> | |
<h3>Supply Chain Security</h3> | |
<p>The project uses package signing and dependency locking. However, not all dependencies have SBOM (Software Bill of Materials) available.</p> | |
<div class="recommendation"> | |
<h3>Recommendations</h3> | |
<ul> | |
<li>Update the 5 outdated dependencies identified</li> | |
<li>Replace or patch the 2 vulnerable dependencies</li> | |
<li>Generate and publish SBOM for better supply chain transparency</li> | |
<li>Implement automated dependency scanning in CI/CD</li> | |
</ul> | |
</div> | |
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<h2>Regulatory Compliance</h2> | |
<p>Risk Score: <span class="risk-score risk-medium">5.2 / 10</span> (Medium Risk)</p> | |
<h3>Compliance Readiness</h3> | |
<table> | |
<tr> | |
<th>Regulation</th> | |
<th>Readiness Level</th> | |
<th>Key Gaps</th> | |
</tr> | |
<tr> | |
<td>GDPR</td> | |
<td>Medium</td> | |
<td>Data retention controls, right to be forgotten</td> | |
</tr> | |
<tr> | |
<td>CCPA</td> | |
<td>Medium</td> | |
<td>Data inventory mechanisms</td> | |
</tr> | |
<tr> | |
<td>AI Act (EU)</td> | |
<td>Low</td> | |
<td>Risk assessment, transparency documentation</td> | |
</tr> | |
</table> | |
<h3>Documentation Quality</h3> | |
<p>Documentation on regulatory aspects is present but not comprehensive. Data privacy features are documented at a basic level, but implementation details and guidance on regulatory compliance are limited.</p> | |
<div class="recommendation"> | |
<h3>Recommendations</h3> | |
<ul> | |
<li>Develop detailed guidance for GDPR and CCPA compliance when using the library</li> | |
<li>Implement data retention controls and mechanisms for data deletion</li> | |
<li>Create AI Act compliance documentation templates</li> | |
<li>Enhance explainability features for high-risk use cases</li> | |
</ul> | |
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<p>© 2025 LibVulnWatch - This report reflects the state of the library at the time of assessment.</p> | |
<p>For questions or clarifications, contact: [email protected]</p> | |
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