Comparison
vigil-llm vs autoguardrails
Verdict
Pick vigil-llm if vigil-llm is designed for users who need robust security measures to protect against prompt injections and jailbreak attempts in LLMs; 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 · vigil-llm alternatives · autoguardrails alternatives
GraphCanon updated Sep 20, 2026
11views this month
Trust & integrity
| Signal | vigil-llm | autoguardrails |
|---|---|---|
| Maintenance | Dormant (962d since push) As of Sep 20, 2026 · github_public_v1 | Active (11d since push) As of Sep 12, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 12, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 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
- vigil-llm
- Detect prompt injections and other risky inputs in LLMs
- autoguardrails
- Alignment-research scaffold for LLM guardrails involving policy evaluation and content moderation
Stars
- vigil-llm
- 496
- autoguardrails
- 130
Forks
- vigil-llm
- 56
- autoguardrails
- 36
Open issues
- vigil-llm
- 16
- autoguardrails
- 2
Language
- vigil-llm
- Python
- autoguardrails
- Python
Adopt for
- vigil-llm
- Vigil-llm is designed for users who need robust security measures to protect against prompt injections and jailbreak attempts in LLMs.
- 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
- vigil-llm
- -
- autoguardrails
- -
Runtime
- vigil-llm
- -
- autoguardrails
- -
License
- vigil-llm
- Apache-2.0
- autoguardrails
- Apache-2.0
Last pushed
- vigil-llm
- Jan 31, 2024
- autoguardrails
- Sep 1, 2026
Categories
- vigil-llm
- Evaluation & Observability
- autoguardrails
- Evaluation & Observability, LLM Frameworks
Trust and health
Maintenance
- vigil-llm
- Dormant (18%)
- autoguardrails
- Active (82%)
Days since push
- vigil-llm
- 962d
- autoguardrails
- 11d
Open issues (now)
- vigil-llm
- 16
- autoguardrails
- 2
Stars delta
- vigil-llm
- +5 (30d)
- autoguardrails
- +2 (30d)
Owner type
- vigil-llm
- User
- autoguardrails
- Organization
OpenSSF Scorecard
- vigil-llm
- Not queried
- autoguardrails
- Published findings
Full report
- vigil-llm
- Trust report
- autoguardrails
- Trust report
Shared compatibility
- Python · vigil-llm: Python runtime · autoguardrails: Python runtime
Choose vigil-llm if…
- Tags unique to vigil-llm: adversarial-attacks, large-language-models, llm-security, prompt-injection.
- vigil-llm ships Docker support for self-hosted deployment.
- When deploying large language models that require high levels of input security, vigil-llm can be employed to detect maliciously crafted inputs intended to manipulate model behavior.
When NOT to use vigil-llm
- If your application does not require high security against malicious inputs or if the risks of prompt injection are minimal due to controlled input sources, vigil-llm might be unnecessary.
- For projects that focus on optimizing output speed rather than input robustness, other tools might be more appropriate as vigil-llm could add significant processing overhead.
Choose autoguardrails if…
- 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 LLM Frameworks.
- 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 (deadbits/vigil-llm) · observed Sep 20, 2026
- GitHub forks (deadbits/vigil-llm) · observed Sep 20, 2026
- Last push (deadbits/vigil-llm) · observed Jan 31, 2024
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 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: vigil-llm 496 · autoguardrails 130 (synced Sep 20, 2026).
Common questions
- What is the difference between vigil-llm and autoguardrails?
- vigil-llm: Detect prompt injections and other risky inputs in LLMs. 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 vigil-llm over autoguardrails?
- Choose vigil-llm over autoguardrails when Tags unique to vigil-llm: adversarial-attacks, large-language-models, llm-security, prompt-injection; vigil-llm ships Docker support for self-hosted deployment; When deploying large language models that require high levels of input security, vigil-llm can be employed to detect maliciously crafted inputs intended to manipulate model behavior.
- When should I choose autoguardrails over vigil-llm?
- Choose autoguardrails over vigil-llm when 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 LLM Frameworks; When you are conducting alignment research that requires systematic iteration on LLM safeguard policies.
- When should I avoid vigil-llm?
- If your application does not require high security against malicious inputs or if the risks of prompt injection are minimal due to controlled input sources, vigil-llm might be unnecessary. For projects that focus on optimizing output speed rather than input robustness, other tools might be more appropriate as vigil-llm could add significant processing overhead.
- 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 vigil-llm or autoguardrails more popular on GitHub?
- vigil-llm has more GitHub stars (496 vs 130). Stars measure visibility, not whether either tool fits your constraints.
- Are vigil-llm and autoguardrails open source?
- Yes - both are open-source projects on GitHub (vigil-llm: Apache-2.0, autoguardrails: Apache-2.0).
- Where can I find alternatives to vigil-llm or autoguardrails?
- GraphCanon lists graph-backed alternatives at vigil-llm alternatives and autoguardrails alternatives (vigil-llm 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, vigil-llm or autoguardrails?
- vigil-llm: Dormant. 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 vigil-llm and autoguardrails?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: vigil-llm trust report; autoguardrails trust report.