Comparison
datafog-python vs heretic
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.
Markdown twin · datafog-python alternatives · heretic alternatives
GraphCanon updated Sep 20, 2026
8views this month
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Trust & integrity
| Signal | datafog-python | heretic |
|---|---|---|
| Maintenance | Very active (2d since push) As of Sep 13, 2026 · github_public_v1 | Active (12d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 13, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No published findings from this source as of 2026-07-15 As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- datafog-python
- Offline PII firewall for AI agents and LLM apps
- heretic
- Fully automatic censorship removal for language models
Stars
- datafog-python
- 72
- heretic
- 32k
Forks
- datafog-python
- 14
- heretic
- 3.5k
Open issues
- datafog-python
- 8
- heretic
- 84
Language
- datafog-python
- Python
- heretic
- Python
Adopt for
- datafog-python
- 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
- Heretic is a Python-based tool for automatic censorship removal in language models, using transformer technology.
Persona
- datafog-python
- -
- heretic
- -
Runtime
- datafog-python
- -
- heretic
- -
License
- datafog-python
- MIT
- heretic
- Heretic is licensed under the AGPL-3.0, which requires that any derivative works be open source and distributed under the same license.
Last pushed
- datafog-python
- Sep 10, 2026
- heretic
- Sep 5, 2026
Categories
- datafog-python
- AI Agents, LLM Frameworks
- heretic
- LLM Frameworks
Trust and health
Maintenance
- datafog-python
- Very active (96%)
- heretic
- Active (82%)
Days since push
- datafog-python
- 2d
- heretic
- 12d
Open issues (now)
- datafog-python
- 8
- heretic
- 84
Stars delta
- datafog-python
- +6 (30d)
- heretic
- +4.0k (30d)
Open issues delta
- datafog-python
- +2 (30d)
- heretic
- +10 (30d)
Owner type
- datafog-python
- Organization
- heretic
- User
OSV dependency advisories
- datafog-python
- No published findings from this source as of 2026-07-15
- heretic
- No lockfile (source not queried)
Full report
- datafog-python
- Trust report
- heretic
- Trust report
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.
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.
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 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-
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (DataFog/datafog-python) · observed Sep 20, 2026
- GitHub forks (DataFog/datafog-python) · observed Sep 20, 2026
- Last push (DataFog/datafog-python) · observed Sep 10, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (p-e-w/heretic) · observed Sep 20, 2026
- GitHub forks (p-e-w/heretic) · observed Sep 20, 2026
- Last push (p-e-w/heretic) · observed Sep 5, 2026
- License file (AGPL-3.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: datafog-python 72 · heretic 32k (synced Sep 20, 2026).
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 and heretic alternatives (datafog-python markdown twin, heretic markdown twin), 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 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; heretic trust report.