Is Llama 2 13B Chat Safe?
Llama 2 13B Chat — Nerq Trust Score 63.1/100 (C grade). Based on analysis of 4 trust dimensions, it is generally safe but has some concerns. Last updated: 2026-05-05.
Use Llama 2 13B Chat with some caution. Llama 2 13B Chat is a software tool with a Nerq Trust Score of 63.1/100 (C), based on 4 independent data dimensions. Below the recommended threshold of 70. Maintenance: 0/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-05-05. Machine-readable data (JSON).
Is Llama 2 13B Chat safe?
CAUTION — Llama 2 13B Chat has a Nerq Trust Score of 63.1/100 (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.
What is Llama 2 13B Chat's trust score?
Llama 2 13B Chat has a Nerq Trust Score of 63.1/100, earning a C grade. This score is based on 4 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Llama 2 13B Chat?
Llama 2 13B Chat's strongest signal is compliance at 81/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Llama 2 13B Chat and who maintains it?
| Author | meta |
| Category | Ai |
| Source | https://replicate.com/meta/llama-2-13b-chat |
| Protocols | replicate_api · rest |
Regulatory Compliance
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 81/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in ai
Llama 2 13B Chat Across Platforms
Same developer/company in other registries:
What Is Llama 2 13B Chat?
Llama 2 13B Chat is a software tool in the ai category: A large language model for chat completions.. Nerq Trust Score: 63/100 (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 Llama 2 13B Chat's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Llama 2 13B Chat performs in each:
- Maintenance (0/100): Llama 2 13B Chat 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 (81/100): Llama 2 13B Chat 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 63.1/100 (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 Llama 2 13B Chat?
Llama 2 13B Chat is designed for:
- Developers and teams working with ai tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Llama 2 13B Chat 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 Llama 2 13B Chat's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Review the repository 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 Llama 2 13B Chat's dependency tree. - Review permissions — Understand what access Llama 2 13B Chat requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Llama 2 13B Chat 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=llama-2-13b-chat - Review the license — Confirm that Llama 2 13B Chat'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 Llama 2 13B Chat
When evaluating whether Llama 2 13B Chat is safe, consider these category-specific risks:
Understand how Llama 2 13B Chat processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Llama 2 13B Chat's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Llama 2 13B Chat. Security patches and bug fixes are only effective if you're running the latest version.
If Llama 2 13B Chat 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 Llama 2 13B Chat's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Llama 2 13B Chat in violation of its license can expose your organization to legal liability.
Best Practices for Using Llama 2 13B Chat Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Llama 2 13B Chat while minimizing risk:
Periodically review how Llama 2 13B Chat is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Llama 2 13B Chat and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Llama 2 13B Chat only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Llama 2 13B Chat's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Llama 2 13B Chat is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Llama 2 13B Chat?
Even promising tools aren't right for every situation. Consider avoiding Llama 2 13B Chat 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 Llama 2 13B Chat's trust score of 63.1/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Llama 2 13B Chat Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among ai tools, the average Trust Score is 62/100. Llama 2 13B Chat's score of 63.1/100 is above the category average of 62/100.
This positions Llama 2 13B Chat favorably among ai 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 Llama 2 13B Chat 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, Llama 2 13B Chat'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 Llama 2 13B Chat's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=llama-2-13b-chat&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 Llama 2 13B Chat are strengthening or weakening over time.
Llama 2 13B Chat vs Alternatives
In the ai category, Llama 2 13B Chat scores 63.1/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Llama 2 13B Chat vs Arize Phoenix — Trust Score: 61.0/100
- Llama 2 13B Chat vs Hermes-3-Llama-3.2-3B — Trust Score: 60.1/100
- Llama 2 13B Chat vs AlphaMaze-v0.2-1.5B — Trust Score: 59.2/100
Key Takeaways
- Llama 2 13B Chat has a Trust Score of 63.1/100 (C) and is not yet Nerq Verified.
- Llama 2 13B Chat shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among ai tools, Llama 2 13B Chat 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.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Maintenance | 0/100 |
| Popularity | 0/100 |
Based on 2 dimensions. Data from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Llama 2 13B Chat collect?
Privacy assessment for Llama 2 13B Chat is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Is Llama 2 13B Chat 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: Llama 2 13B Chat Security Report
Llama 2 13B Chat Across Platforms
Same developer/company in other registries:
How we calculated this score
Llama 2 13B Chat's trust score of 63.1/100 (C) is computed from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 2 independent dimensions: maintenance (0/100), popularity (0/100). 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 May 05, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
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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.