Is Tokenscope Safe?

Tokenscope — Nerq Trust Score 55.0/100 (C grade). Based on analysis of 5 trust dimensions, it is has notable safety concerns. Last updated: 2026-04-24.

Use Tokenscope with some caution. Tokenscope is a software tool with a Nerq Trust Score of 55.0/100 (C). Below the recommended threshold of 70. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-04-24. Machine-readable data (JSON).

Is Tokenscope safe?

CAUTION — Tokenscope has a Nerq Trust Score of 55.0/100 (C). It has moderate trust signals but shows some areas of concern that warrant attention. Suitable for development use — review security and maintenance signals before production deployment.

Security Analysis → Tokenscope Privacy Report →

What is Tokenscope's trust score?

Tokenscope has a Nerq Trust Score of 55.0/100, earning a C grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.

Overall Trust
55.0

What are the key security findings for Tokenscope?

Tokenscope's strongest signal is overall trust at 55.0/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.

Composite trust score: 55.0/100 across all available signals

What is Tokenscope and who maintains it?

Author0xaa276069230a04e9c1c3573b8d916dad9133d1ca
CategoryUncategorized
Sourcehttps://8004scan.io/agents/tokenscope

What Is Tokenscope?

Tokenscope is a software tool in the uncategorized category: TokenScope generates crypto due diligence reports for ERC-20 tokens.. Nerq Trust Score: 55/100 (C).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including security vulnerabilities, maintenance activity, license compliance, and community adoption.

How Nerq Assesses Tokenscope's Safety

Nerq evaluates every software tool across 13+ independent trust signals drawn from public sources including GitHub, NVD, OSV.dev, OpenSSF Scorecard, and package registries. These signals are grouped into five core dimensions: Security (known CVEs, dependency vulnerabilities, security policies), Maintenance (commit frequency, release cadence, issue response times), Documentation (README quality, API docs, examples), Compliance (license, regulatory alignment across 52 jurisdictions), and Community (stars, forks, downloads, ecosystem integrations).

Tokenscope receives an overall Trust Score of 55.0/100 (C), which Nerq considers moderate. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.

Nerq updates trust scores continuously as new data becomes available. To get the latest assessment, query the API: GET nerq.ai/v1/preflight?target=TokenScope

Each dimension is weighted according to its importance for the tool's category. For example, Security and Maintenance carry higher weight for tools that handle sensitive data or execute code, while Community and Documentation are weighted more heavily for developer-facing libraries and frameworks. This ensures that Tokenscope's score reflects the risks most relevant to its actual usage patterns. The final score is a weighted average across all five dimensions, normalized to a 0-100 scale with letter grades from A (highest) to F (lowest).

Who Should Use Tokenscope?

Tokenscope is designed for:

Risk guidance: Tokenscope is suitable for development and testing environments. Before production deployment, conduct a thorough review of its security posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.

How to Verify Tokenscope's Safety Yourself

While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:

  1. Check the source code — Review the repository security policy, open issues, and recent commits for signs of active maintenance.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Tokenscope's dependency tree.
  3. Review permissions — Understand what access Tokenscope requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Tokenscope in a sandboxed environment before granting access to production data or systems.
  5. Monitor continuously — Use Nerq's API to set up automated trust checks: GET nerq.ai/v1/preflight?target=TokenScope
  6. Review the license — Confirm that Tokenscope's license is compatible with your intended use case. Pay attention to restrictions on commercial use, redistribution, and derivative works. Some AI tools use dual licensing or have separate terms for enterprise customers that differ from the open-source license.
  7. Check community signals — Look at the project's issue tracker, discussion forums, and social media presence. A healthy community actively reports bugs, contributes fixes, and discusses security concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Tokenscope

When evaluating whether Tokenscope is safe, consider these category-specific risks:

Data handling

Understand how Tokenscope processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency security

Check Tokenscope's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.

Update frequency

Regularly check for updates to Tokenscope. Security patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Tokenscope connects to external APIs or services, each integration point is a potential attack surface. Audit all third-party connections, verify that data shared with external services is minimized, and ensure that integration credentials are rotated regularly.

License and IP compliance

Verify that Tokenscope's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Tokenscope in violation of its license can expose your organization to legal liability.

Best Practices for Using Tokenscope Safely

Whether you're an individual developer or an enterprise team, these practices will help you get the most from Tokenscope while minimizing risk:

Conduct regular audits

Periodically review how Tokenscope is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.

Keep dependencies updated

Ensure Tokenscope and all its dependencies are running the latest stable versions to benefit from security patches.

Follow least privilege

Grant Tokenscope only the minimum permissions it needs to function. Avoid granting admin or root access.

Monitor for security advisories

Subscribe to Tokenscope's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.

Document usage policies

Create and maintain a clear policy for how Tokenscope is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Tokenscope?

Even promising tools aren't right for every situation. Consider avoiding Tokenscope in these scenarios:

For each scenario, evaluate whether Tokenscope's trust score of 55.0/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.

How Tokenscope Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among uncategorized tools, the average Trust Score is 62/100. Tokenscope's score of 55.0/100 is near the category average of 62/100.

This places Tokenscope in line with the typical uncategorized tool tool. It meets baseline expectations but does not distinguish itself from peers on trust metrics.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderate in isolation may actually represent strong performance within a challenging category — or vice versa. Nerq's category-relative analysis helps teams make informed decisions by showing not just absolute quality, but how a tool ranks against its direct peers.

Trust Score History

Nerq continuously monitors Tokenscope and recalculates its Trust Score as new data becomes available. Our scoring engine ingests real-time signals from source repositories, vulnerability databases (NVD, OSV.dev), package registries, and community metrics. When a new CVE is published, a major release ships, or maintenance patterns change, Tokenscope's score is updated within 24 hours.

Historical trust trends reveal whether a tool is improving, stable, or declining over time. A tool that consistently maintains or improves its score demonstrates ongoing commitment to security and quality. Conversely, a downward trend may signal reduced maintenance, growing technical debt, or unresolved vulnerabilities. To track Tokenscope's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=TokenScope&include=history

Nerq retains trust score snapshots at regular intervals, enabling trend analysis across weeks and months. Enterprise users can access detailed historical reports showing how each dimension — security, maintenance, documentation, compliance, and community — has evolved independently, providing granular visibility into which aspects of Tokenscope are strengthening or weakening over time.

Key Takeaways

What data does Tokenscope collect?

Privacy assessment for Tokenscope is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.

Is Tokenscope secure?

Security score: under assessment. Review security practices and consider alternatives with higher security scores for sensitive use cases.

Nerq monitors this entity against NVD, OSV.dev, and registry-specific vulnerability databases for ongoing security assessment.

Full analysis: Tokenscope Security Report

How we calculated this score

Tokenscope's trust score of 55.0/100 (C) is computed from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 0 independent dimensions: . 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 24, 2026. Data version: 1.0.

Full methodology documentation · Machine-readable data (JSON API)

Frequently Asked Questions

Is Tokenscope Safe?
Use with some caution. TokenScope with a Nerq Trust Score of 55.0/100 (C). Strongest signal: overall trust (55.0/100). Score based on multiple trust dimensions.
What is Tokenscope's trust score?
TokenScope: 55.0/100 (C). Score based on multiple trust dimensions. Scores update as new data becomes available. API: GET nerq.ai/v1/preflight?target=TokenScope
What are safer alternatives to Tokenscope?
In the Uncategorized category, more software tools are being analyzed — check back soon. TokenScope scores 55.0/100.
How often is Tokenscope's safety score updated?
Nerq continuously monitors Tokenscope and updates its trust score as new data becomes available. Current: 55.0/100 (C), last verified 2026-04-24. API: GET nerq.ai/v1/preflight?target=TokenScope
Can I use Tokenscope in a regulated environment?
Tokenscope has not reached the Nerq Verified threshold of 70. Additional due diligence is recommended.
API: /v1/preflight Trust Badge API Docs

See Also

Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.

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