--- title: "datafog-python vs heretic" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/datafog-datafog-python-vs-p-e-w-heretic" tools: ["datafog-datafog-python", "p-e-w-heretic"] --- # datafog-python vs heretic *GraphCanon updated Sep 20, 2026* ## Verdict Pick datafog-python if datafog-python is an offline PII firewall for AI agents and LLM apps, featuring fast local detection and redaction of PII with minimal dependencies; pick heretic if heretic is a Python-based tool for automatic censorship removal in language models, using transformer technology. [datafog-python](https://datafog.ai) reports 72 GitHub stars, 14 forks, and 8 open issues, last pushed Sep 10, 2026. [heretic](https://heretic-project.org) has 32k stars, 3.5k forks, and 84 open issues, last pushed Sep 5, 2026. Figures are from public GitHub metadata via [datafog-python's repository](https://github.com/DataFog/datafog-python) and [heretic's repository](https://github.com/p-e-w/heretic). | | [datafog-python](/tools/datafog-datafog-python.md) | [heretic](/tools/p-e-w-heretic.md) | | --- | --- | --- | | Tagline | Offline PII firewall for AI agents and LLM apps | Fully automatic censorship removal for language models | | Stars | 72 | 31,738 | | Forks | 14 | 3,547 | | Open issues | 8 | 84 | | Language | Python | Python | | Adopt for | datafog-python is an offline PII firewall for AI agents and LLM apps, featuring fast local detection and redaction of PII with minimal dependencies. | Heretic is a Python-based tool for automatic censorship removal in language models, using transformer technology. | | Persona | - | - | | Runtime | - | - | | License | MIT | Heretic is licensed under the AGPL-3.0, which requires that any derivative works be open source and distributed under the same license. | | Categories | AI Agents, LLM Frameworks | LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [datafog-python](/tools/datafog-datafog-python.md) | [heretic](/tools/p-e-w-heretic.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 2d | 12d | | Open issues (now) | 8 | 84 | | Stars delta | +6 (30d) | +4.0k (30d) | | Open issues delta | +2 (30d) | +10 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/datafog-datafog-python/trust.md) | [trust report](/tools/p-e-w-heretic/trust.md) | ## Decision facts: datafog-python - **Adopt for:** datafog-python is an offline PII firewall for AI agents and LLM apps, featuring fast local detection and redaction of PII with minimal dependencies. ## Decision facts: heretic - **Requirements:** Heretic is a Python-based tool, so Python must be installed on the system where it will be used. - **Adopt for:** Heretic is a Python-based tool for automatic censorship removal in language models, using transformer technology. - **License detail:** Heretic is licensed under the AGPL-3.0, which requires that any derivative works be open source and distributed under the same license. ## Choose when ### Choose datafog-python if… - License: datafog-python is MIT, heretic is AGPL-3.0. - Tags unique to datafog-python: agent-security, anonymization, claude-code, compliance. - Also covers AI Agents. - If you require rapid, offline detection and redaction of personally identifiable information without network calls or extensive dependencies. ### Choose heretic if… - License: heretic is AGPL-3.0, datafog-python is MIT. - Requirements: Heretic is a Python-based tool, so Python must be installed on the system where it will be used.. - Tags unique to heretic: abliteration, llm, transformer. - When you need to automatically remove censorship from language models and are comfortable with the AGPL-3.0 license, which requires that any derivative works be open source. ## When NOT to use datafog-python - When your application needs cloud-based processing capabilities beyond local pii detection and redaction offered by datafog-python. - If the need arises for advanced networked security features such as real-time threat intelligence updates, which datafog-python with its offline nature does not provide. ## When NOT to use heretic - If your project cannot comply with the AGPL-3.0 license, as it mandates that any derivative works must also be open source. - When you are looking for a tool that does not automatically remove censorship, as Heretic is specifically designed for this purpose and may not align with projects that require manual or selective de- ## Common questions ### What is the difference between datafog-python and heretic? datafog-python: Offline PII firewall for AI agents and LLM apps. heretic: Fully automatic censorship removal for language models. See the comparison table for live GitHub stats and shared categories. ### When should I choose datafog-python over heretic? Choose datafog-python over heretic when License: datafog-python is MIT, heretic is AGPL-3.0; Tags unique to datafog-python: agent-security, anonymization, claude-code, compliance; Also covers AI Agents; If you require rapid, offline detection and redaction of personally identifiable information without network calls or extensive dependencies. ### When should I choose heretic over datafog-python? Choose heretic over datafog-python when License: heretic is AGPL-3.0, datafog-python is MIT; Requirements: Heretic is a Python-based tool, so Python must be installed on the system where it will be used.; Tags unique to heretic: abliteration, llm, transformer; When you need to automatically remove censorship from language models and are comfortable with the AGPL-3.0 license, which requires that any derivative works be open source. ### When should I avoid datafog-python? When your application needs cloud-based processing capabilities beyond local pii detection and redaction offered by datafog-python. If the need arises for advanced networked security features such as real-time threat intelligence updates, which datafog-python with its offline nature does not provide. ### When should I avoid heretic? If your project cannot comply with the AGPL-3.0 license, as it mandates that any derivative works must also be open source. When you are looking for a tool that does not automatically remove censorship, as Heretic is specifically designed for this purpose and may not align with projects that require manual or selective de- ### Is datafog-python or heretic more popular on GitHub? heretic has more GitHub stars (31,738 vs 72). Stars measure visibility, not whether either tool fits your constraints. ### Are datafog-python and heretic open source? Yes - both are open-source projects on GitHub (datafog-python: MIT, heretic: AGPL-3.0). ### Where can I find alternatives to datafog-python or heretic? GraphCanon lists graph-backed alternatives at [datafog-python alternatives](/tools/datafog-datafog-python/alternatives) and [heretic alternatives](/tools/p-e-w-heretic/alternatives) ([datafog-python markdown twin](/tools/datafog-datafog-python/alternatives.md), [heretic markdown twin](/tools/p-e-w-heretic/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/datafog-datafog-python-vs-p-e-w-heretic.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, datafog-python or heretic? datafog-python: Very active. heretic: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for datafog-python and heretic? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [datafog-python trust report](/tools/datafog-datafog-python/trust); [heretic trust report](/tools/p-e-w-heretic/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=datafog-datafog-python`](/api/graphcanon/graph?tool=datafog-datafog-python) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_