Comparison
circle-guard-bench vs AutoDefense
Verdict
Pick circle-guard-bench if circle-guard-bench is a Python-based AI benchmark tool for evaluating large language model guard systems under various protection scenarios; pick AutoDefense if autoDefense uses a multi-agent framework to mitigate jailbreak attacks on LLMs, installed via Python.
Markdown twin · circle-guard-bench alternatives · AutoDefense alternatives
GraphCanon updated Sep 20, 2026
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Trust & integrity
| Signal | circle-guard-bench | AutoDefense |
|---|---|---|
| Maintenance | Slowing (185d since push) As of Sep 9, 2026 · github_public_v1 | Slowing (231d since push) As of Sep 4, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 9, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 4, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 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
- circle-guard-bench
- AI benchmark for evaluating LLM guard systems
- AutoDefense
- Multi-Agent LLM Defense against Jailbreak Attacks
Stars
- circle-guard-bench
- 75
- AutoDefense
- 68
Forks
- circle-guard-bench
- 5
- AutoDefense
- 20
Open issues
- circle-guard-bench
- 1
- AutoDefense
- 1
Language
- circle-guard-bench
- Python
- AutoDefense
- Python
Adopt for
- circle-guard-bench
- circle-guard-bench is a Python-based AI benchmark tool for evaluating large language model guard systems under various protection scenarios.
- AutoDefense
- AutoDefense uses a multi-agent framework to mitigate jailbreak attacks on LLMs, installed via Python.
Persona
- circle-guard-bench
- -
- AutoDefense
- -
Runtime
- circle-guard-bench
- -
- AutoDefense
- -
License
- circle-guard-bench
- Apache-2.0
- AutoDefense
- MIT
Last pushed
- circle-guard-bench
- Mar 7, 2026
- AutoDefense
- Jan 15, 2026
Categories
- circle-guard-bench
- Evaluation & Observability
- AutoDefense
- AI Agents, Evaluation & Observability
Trust and health
Days since push
- circle-guard-bench
- 185d
- AutoDefense
- 231d
Stars delta
- circle-guard-bench
- +3 (30d)
- AutoDefense
- 0 (30d)
Open issues delta
- circle-guard-bench
- +1 (30d)
- AutoDefense
- 0 (30d)
Owner type
- circle-guard-bench
- Organization
- AutoDefense
- User
Full report
- circle-guard-bench
- Trust report
- AutoDefense
- Trust report
Shared compatibility
- Python · circle-guard-bench: Python runtime · AutoDefense: Python runtime
Choose circle-guard-bench if…
- License: circle-guard-bench is Apache-2.0, AutoDefense is MIT.
- Tags unique to circle-guard-bench: ai, benchmarking, guardrail, llm-evaluation.
- Use circle-guard-bench when you need to evaluate the effectiveness of guardrails and safeguards in your LLM environment, as it offers an unparalleled set of scenarios specific to these protections.
When NOT to use circle-guard-bench
- Avoid circle-guard-bench if your primary focus is on benchmarking the performance aspects like speed and latency of LLMs, as it specializes in evaluating protections rather than performance.
- Do not use this tool when you intend to conduct general purpose evaluations or comparisons between different LLM models that do not specifically involve security-related guard systems.
Choose AutoDefense if…
- License: AutoDefense is MIT, circle-guard-bench is Apache-2.0.
- Tags unique to AutoDefense: defense-mechanism, jailbreak prevention, llm-defense, multi-agent.
- Also covers AI Agents.
- Implementing robust defenses for enterprise-level AI projects with high-security requirements
When NOT to use AutoDefense
- Projects requiring light-weight solutions where multi-agent systems might introduce complexity overhead
- Environments without access to Python and its ecosystem, as AutoDefense depends on specific Python packages
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (whitecircle/circle-guard-bench) · observed Sep 20, 2026
- GitHub forks (whitecircle/circle-guard-bench) · observed Sep 20, 2026
- Last push (whitecircle/circle-guard-bench) · observed Mar 7, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (XHMY/AutoDefense) · observed Sep 20, 2026
- GitHub forks (XHMY/AutoDefense) · observed Sep 20, 2026
- Last push (XHMY/AutoDefense) · observed Jan 15, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: circle-guard-bench 75 · AutoDefense 68 (synced Sep 20, 2026).
Common questions
- What is the difference between circle-guard-bench and AutoDefense?
- circle-guard-bench: AI benchmark for evaluating LLM guard systems. AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks. See the comparison table for live GitHub stats and shared categories.
- When should I choose circle-guard-bench over AutoDefense?
- Choose circle-guard-bench over AutoDefense when License: circle-guard-bench is Apache-2.0, AutoDefense is MIT; Tags unique to circle-guard-bench: ai, benchmarking, guardrail, llm-evaluation; Use circle-guard-bench when you need to evaluate the effectiveness of guardrails and safeguards in your LLM environment, as it offers an unparalleled set of scenarios specific to these protections.
- When should I choose AutoDefense over circle-guard-bench?
- Choose AutoDefense over circle-guard-bench when License: AutoDefense is MIT, circle-guard-bench is Apache-2.0; Tags unique to AutoDefense: defense-mechanism, jailbreak prevention, llm-defense, multi-agent; Also covers AI Agents; Implementing robust defenses for enterprise-level AI projects with high-security requirements.
- When should I avoid circle-guard-bench?
- Avoid circle-guard-bench if your primary focus is on benchmarking the performance aspects like speed and latency of LLMs, as it specializes in evaluating protections rather than performance. Do not use this tool when you intend to conduct general purpose evaluations or comparisons between different LLM models that do not specifically involve security-related guard systems.
- When should I avoid AutoDefense?
- Projects requiring light-weight solutions where multi-agent systems might introduce complexity overhead Environments without access to Python and its ecosystem, as AutoDefense depends on specific Python packages
- Is circle-guard-bench or AutoDefense more popular on GitHub?
- circle-guard-bench has more GitHub stars (75 vs 68). Stars measure visibility, not whether either tool fits your constraints.
- Are circle-guard-bench and AutoDefense open source?
- Yes - both are open-source projects on GitHub (circle-guard-bench: Apache-2.0, AutoDefense: MIT).
- Where can I find alternatives to circle-guard-bench or AutoDefense?
- GraphCanon lists graph-backed alternatives at circle-guard-bench alternatives and AutoDefense alternatives (circle-guard-bench markdown twin, AutoDefense 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, circle-guard-bench or AutoDefense?
- circle-guard-bench: Slowing. AutoDefense: Slowing. 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 circle-guard-bench and AutoDefense?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: circle-guard-bench trust report; AutoDefense trust report.