Is Faceswap Safe? — Trust Score: 69.3/100
According to Nerq's independent analysis of deepfakes/faceswap, this other has a trust score of 69.3 out of 100, earning a C grade. With 54,975 stars on github, it is below the recommended threshold of 70. Security score: 0/100. Compliance: 71/100 across 52 jurisdictions. Data sourced from 13+ independent signals including GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-18. Machine-readable data (JSON).
Is Faceswap safe?
CAUTION — Faceswap has a Nerq Trust Score of 69.3/100 (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.
Trust Assessment
Moderate — deepfakes/faceswap shows mixed trust signals. Some areas are strong while others could be improved. We recommend reviewing the full KYA (Know Your Agent) report before integrating it into production workflows.
Trust Signal Breakdown
Details
| Author | Unknown |
| Category | other |
| Stars | 54,975 |
| Source | https://github.com/deepfakes/faceswap |
Regulatory Compliance
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 71/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
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What Is Faceswap?
Faceswap is a AI tool in the other category. Deepfakes Software For All
As of March 2026, Faceswap has 54,975 stars on github, making it one of the most popular tools in its category in the AI ecosystem. But popularity alone does not equal safety — which is why Nerq independently analyzes every tool across 13+ trust signals.
How Nerq Assesses Faceswap's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Faceswap performs in each:
- Security (0/100): Faceswap's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (0/100): Faceswap is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (0/100): Documentation quality is insufficient. This includes README completeness, API documentation, usage examples, and contribution guidelines.
- Compliance (71/100): Faceswap is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 69.3/100 (C) reflects the weighted combination of these signals. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.
Who Should Use Faceswap?
Faceswap is designed for:
- Developers and teams working with other tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Faceswap 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 Faceswap's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any AI tool:
- Check the source code — Review the repository's security policy, open issues, and recent commits for signs of active maintenance.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Faceswap's dependency tree. - Review permissions — Understand what access Faceswap requires. AI tools should follow the principle of least privilege.
- Test in isolation — Run Faceswap in a sandboxed environment before granting access to production data or systems.
- Monitor continuously — Use Nerq's API to set up automated trust checks:
GET nerq.ai/v1/preflight?target=deepfakes/faceswap - Review the license — Confirm that Faceswap'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.
- 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 Faceswap
When evaluating whether Faceswap is safe, consider these category-specific risks:
Understand how Faceswap processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Faceswap's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Faceswap. Security patches and bug fixes are only effective if you're running the latest version.
If Faceswap 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.
Verify that Faceswap's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Faceswap in violation of its license can expose your organization to legal liability.
Best Practices for Using Faceswap Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Faceswap while minimizing risk:
Periodically review how Faceswap is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Faceswap and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Faceswap only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Faceswap's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Faceswap is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Faceswap?
Even promising tools aren't right for every situation. Consider avoiding Faceswap in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional compliance review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Faceswap's trust score of 69.3/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Faceswap Compares to Industry Standards
Nerq indexes over 204,000 AI agents and tools across dozens of categories. Among other tools, the average Trust Score is 62/100. Faceswap's score of 69.3/100 is above the category average of 62/100.
This positions Faceswap favorably among other tools. While it outperforms the average, there is still room for improvement in certain trust dimensions.
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 Faceswap 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, Faceswap'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 Faceswap's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=deepfakes/faceswap&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 Faceswap are strengthening or weakening over time.
Faceswap vs Alternatives
In the other category, Faceswap scores 69.3/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Faceswap vs cs-video-courses — Trust Score: 69.3/100
- Faceswap vs awesome-scalability — Trust Score: 71.8/100
- Faceswap vs superpowers — Trust Score: 71.8/100
Key Takeaways
- Faceswap has a Trust Score of 69.3/100 (C) and is not yet Nerq Verified.
- Faceswap shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among other tools, Faceswap scores above the category average of 62/100, demonstrating above-average reliability.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
Frequently Asked Questions
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Related Safety Checks
Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.