Is Semantic Scholar Safe?
Semantic Scholar — Nerq Trust Score 48.2/100 (D grade). Based on analysis of 2 trust dimensions, it is has notable safety concerns. Last updated: 2026-04-11.
Exercise caution with Semantic Scholar. Semantic Scholar is a AI tool with a Nerq Trust Score of 48.2/100 (D), based on 3 independent data dimensions. Below the recommended threshold of 70. Security: 90/100. Popularity: 0/100. Data sourced from privacy policy analysis, data handling practices, company background, and security certifications. Last updated: 2026-04-11. Machine-readable data (JSON).
Is Semantic Scholar safe?
NO — USE WITH CAUTION — Semantic Scholar has a Nerq Trust Score of 48.2/100 (D). It has below-average trust signals with significant gaps in security, maintenance, or documentation. Not recommended for production use without thorough manual review and additional security measures.
What is Semantic Scholar's trust score?
Semantic Scholar has a Nerq Trust Score of 48.2/100, earning a D grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Semantic Scholar?
Semantic Scholar's strongest signal is security at 90/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Semantic Scholar and who maintains it?
| Author | Unknown |
| Category | Ai Tool |
| Source | N/A |
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Safety Guide: Semantic Scholar
What is Semantic Scholar?
Semantic Scholar is a software tool — AI-powered academic search engine by Allen Institute for AI. Free, indexes 200M+ papers..
How to Verify Safety
Review the project for recent activity and known issues.
You can also check the trust score via API: GET /v1/preflight?target=Semantic Scholar
Key Safety Concerns for software tool
When evaluating any software tool, watch for: maintenance status, security.
Trust Assessment
Semantic Scholar has a Nerq Trust Score of 48/100 (D) and has not yet reached Nerq trust threshold (70+). This score is based on automated analysis of security, maintenance, community, and quality signals.
Alternatives
- haotian-liu/LLaVA — 71/100
- wan22_i2v_14b_orbit_shot_lora — 59/100
- ChuckNorris (L1B3RT4S Prompt Enhancer) — 46/100
Key Takeaways
- Semantic Scholar has a Trust Score of 48/100 (D).
- Review carefully before use — below trust threshold.
- Always verify independently using the Nerq API.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Privacy | 34/100 |
| Reliability | 46/100 |
| Transparency | 42/100 |
| Maintenance | 60/100 |
Based on 5 dimensions. Data from privacy policy analysis, data handling practices, company background, and security certifications.
What data does Semantic Scholar collect?
Semantic Scholar is an AI tool. AI-powered academic search engine by Allen Institute for AI. Free, indexes 200M+ papers.
Privacy score: 34/100. AI tools may use inputs for model improvement unless explicitly opted out. Check the data usage policy before sharing confidential information, code, or personal data.
Consider whether the tool offers enterprise plans with data isolation, SOC 2 compliance, or on-premise deployment options.
Full analysis: Semantic Scholar Privacy Report · Privacy review
Is Semantic Scholar secure?
Security score: 90/100. AI-powered academic search engine by Allen Institute for AI. Free, indexes 200M+ papers.
Check Semantic Scholar's security page for certifications such as SOC 2 Type II, ISO 27001, or GDPR compliance documentation. These certifications indicate that the vendor follows established security practices and undergoes regular audits.
For enterprise deployments, verify SSO/SAML support, role-based access control, and audit logging capabilities.
Full analysis: Semantic Scholar Security Report
Semantic Scholar Across Platforms
Same developer/company in other registries:
How we calculated this score
Semantic Scholar's trust score of 48.2/100 (D) is computed from privacy policy analysis, data handling practices, company background, and security certifications. The score reflects 5 independent dimensions: security (90/100), privacy (34/100), reliability (46/100), transparency (42/100), maintenance (60/100). Each dimension is weighted equally to produce the composite trust score.
Nerq analyzes over 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.
This page was last reviewed on April 11, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
Frequently Asked Questions
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Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.