Is Semantic Scholar Safe?
Semantic Scholar — Nerq Trust Score 48.2/100 (D grade). Score based on 2 independent trust signals. Last analyzed: 2026-04-12
Semantic Scholar is a AI tool with a Nerq Trust Score of 48.2/100 (D), based on 3 independent data dimensions. Last analyzed: 2026-04-12 Security: 90/100. Popularity: 0/100. Data sourced from privacy policy analysis, data handling practices, company background, and security certifications. Last updated: 2026-04-12. Machine-readable data (JSON).
Is Semantic Scholar safe?
Trust Score Breakdown — Semantic Scholar has a Nerq Trust Score of 48.2/100 (D). Measured across 2 independent trust signals (as of 2026-04-12).
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.
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.
Measured Signals
Semantic Scholar has a Nerq Trust Score of 48/100 (D). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Alternatives
- haotian-liu/LLaVA — 61/100
- 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).
- The score is a measured composite — it is not a suitability judgment. Evaluate the individual signals against your own requirements.
- Query the current measured values via the Nerq API.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Maintenance | 50/100 |
| Popularity | 0/100 |
| Quality | 40/100 |
| Community | 35/100 |
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
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), maintenance (50/100), popularity (0/100), quality (40/100), community (35/100). 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.
Signals last measured on April 12, 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 measurements based on publicly available signals. They are not endorsements, verdicts, or guarantees of suitability. Always evaluate the signals against your own requirements.