Comparison
datafog-python vs autoguardrails
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 autoguardrails if autoguardrails is an evaluation and development framework for AI policy creation and review. It enables the iterative adjustment and testing of guardrail policies in alignment research through a controlled workflow.
Markdown twin · datafog-python alternatives · autoguardrails alternatives
GraphCanon updated Sep 20, 2026
11views this month
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Trust & integrity
| Signal | datafog-python | autoguardrails |
|---|---|---|
| Maintenance | Very active (2d since push) As of Sep 13, 2026 · github_public_v1 | Active (11d since push) As of Sep 12, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 13, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 12, 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 Jul 15, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Published findings As of Sep 20, 2026 · openssf-scorecard@v1 |
Tagline
- datafog-python
- Offline PII firewall for AI agents and LLM apps
- autoguardrails
- Alignment-research scaffold for LLM guardrails involving policy evaluation and content moderation
Stars
- datafog-python
- 72
- autoguardrails
- 130
Forks
- datafog-python
- 14
- autoguardrails
- 36
Open issues
- datafog-python
- 8
- autoguardrails
- 2
Language
- datafog-python
- Python
- autoguardrails
- 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.
- autoguardrails
- Autoguardrails is an evaluation and development framework for AI policy creation and review. It enables the iterative adjustment and testing of guardrail policies in alignment research through a controlled workflow.
Persona
- datafog-python
- -
- autoguardrails
- -
Runtime
- datafog-python
- -
- autoguardrails
- -
License
- datafog-python
- MIT
- autoguardrails
- Apache-2.0
Last pushed
- datafog-python
- Sep 10, 2026
- autoguardrails
- Sep 1, 2026
Categories
- datafog-python
- AI Agents, LLM Frameworks
- autoguardrails
- Evaluation & Observability, LLM Frameworks
Trust and health
Maintenance
- datafog-python
- Very active (96%)
- autoguardrails
- Active (82%)
Days since push
- datafog-python
- 2d
- autoguardrails
- 11d
Open issues (now)
- datafog-python
- 8
- autoguardrails
- 2
Stars delta
- datafog-python
- +6 (30d)
- autoguardrails
- +2 (30d)
Open issues delta
- datafog-python
- +2 (30d)
- autoguardrails
- 0 (30d)
OSV dependency advisories
- datafog-python
- No published findings from this source as of 2026-07-15
- autoguardrails
- No lockfile (source not queried)
OpenSSF Scorecard
- datafog-python
- Not queried
- autoguardrails
- Published findings
Full report
- datafog-python
- Trust report
- autoguardrails
- Trust report
Shared compatibility
- Python · datafog-python: Python runtime · autoguardrails: Python runtime
Choose datafog-python if…
- License: datafog-python is MIT, autoguardrails is Apache-2.0.
- 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 autoguardrails if…
- License: autoguardrails is Apache-2.0, datafog-python is MIT.
- Requirements: Requires Python 3.10 or higher.; No third-party runtimes; it is built completely on the standard Python library..
- Tags unique to autoguardrails: ai-safety, alignment, autoresearch, content-moderation.
- Also covers Evaluation & Observability.
- When you are conducting alignment research that requires systematic iteration on LLM safeguard policies.
When NOT to use autoguardrails
- Autoguardrails may not suit needs requiring real-time or dynamic policy adjustments outside its autoresearch workflow.
- Avoid using Autoguardrails if you cannot accept offline operation as it is built on the Python standard library and runs without third-party runtime dependencies.
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 (SantanderAI/autoguardrails) · observed Sep 20, 2026
- GitHub forks (SantanderAI/autoguardrails) · observed Sep 20, 2026
- Last push (SantanderAI/autoguardrails) · observed Sep 1, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: datafog-python 72 · autoguardrails 130 (synced Sep 20, 2026).
Common questions
- What is the difference between datafog-python and autoguardrails?
- datafog-python: Offline PII firewall for AI agents and LLM apps. autoguardrails: Alignment-research scaffold for LLM guardrails involving policy evaluation and content moderation. See the comparison table for live GitHub stats and shared categories.
- When should I choose datafog-python over autoguardrails?
- Choose datafog-python over autoguardrails when License: datafog-python is MIT, autoguardrails is Apache-2.0; 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 autoguardrails over datafog-python?
- Choose autoguardrails over datafog-python when License: autoguardrails is Apache-2.0, datafog-python is MIT; Requirements: Requires Python 3.10 or higher.; No third-party runtimes; it is built completely on the standard Python library.; Tags unique to autoguardrails: ai-safety, alignment, autoresearch, content-moderation; Also covers Evaluation & Observability; When you are conducting alignment research that requires systematic iteration on LLM safeguard policies.
- 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 autoguardrails?
- Autoguardrails may not suit needs requiring real-time or dynamic policy adjustments outside its autoresearch workflow. Avoid using Autoguardrails if you cannot accept offline operation as it is built on the Python standard library and runs without third-party runtime dependencies.
- Is datafog-python or autoguardrails more popular on GitHub?
- autoguardrails has more GitHub stars (130 vs 72). Stars measure visibility, not whether either tool fits your constraints.
- Are datafog-python and autoguardrails open source?
- Yes - both are open-source projects on GitHub (datafog-python: MIT, autoguardrails: Apache-2.0).
- Where can I find alternatives to datafog-python or autoguardrails?
- GraphCanon lists graph-backed alternatives at datafog-python alternatives and autoguardrails alternatives (datafog-python markdown twin, autoguardrails 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 autoguardrails?
- datafog-python: Very active. autoguardrails: 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 autoguardrails?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: datafog-python trust report; autoguardrails trust report.