Home/Compare/awesome vs AI-Infra-Guard

Comparison

awesome vs AI-Infra-Guard

Verdict

Pick awesome when license: awesome is CC0-1.0, AI-Infra-Guard is Apache-2.0; pick AI-Infra-Guard when license: AI-Infra-Guard is Apache-2.0, awesome is CC0-1.0.

Markdown twin · awesome alternatives · AI-Infra-Guard alternatives

GraphCanon updated today

awesome logo

awesome

sindresorhus/awesome

484kpushed Jun 30, 2026
vs
AI-Infra-Guard logo

AI-Infra-Guard

Tencent/AI-Infra-Guard

4.1kpushed Jul 8, 2026

Trust & integrity

SignalawesomeAI-Infra-Guard
Maintenance
Active (11d since push)
As of today · github_public_v1
Very active (3d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of today · none

Tagline

awesome
😎 Curated list of awesome topics including hardware resources
AI-Infra-Guard
A full-stack AI Red Teaming platform securing AI ecosystems via OpenClaw Security Scan, Agent Scan, Skills Scan, MCP scan, AI Infra scan and LLM jailbreak evaluation.

Stars

awesome
484k
AI-Infra-Guard
4.1k

Forks

awesome
36k
AI-Infra-Guard
394

Open issues

awesome
92
AI-Infra-Guard
19

Language

awesome
-
AI-Infra-Guard
Python

Adopt for

awesome
-
AI-Infra-Guard
-

Persona

awesome
-
AI-Infra-Guard
-

Runtime

awesome
-
AI-Infra-Guard
-

License

awesome
CC0-1.0
AI-Infra-Guard
Apache-2.0

Last pushed

awesome
Jun 30, 2026
AI-Infra-Guard
Jul 8, 2026

Categories

awesome
LLM Frameworks
AI-Infra-Guard
AI Agents, LLM Frameworks, Vector Databases

Trust and health

Maintenance

awesome
Active (82%)
AI-Infra-Guard
Very active (96%)

Days since push

awesome
11d
AI-Infra-Guard
3d

Open issues (now)

awesome
92
AI-Infra-Guard
19

Owner type

awesome
User
AI-Infra-Guard
Organization

Full report

AI-Infra-Guard
Trust report

Choose awesome if…

  • License: awesome is CC0-1.0, AI-Infra-Guard is Apache-2.0.
  • Tags unique to awesome: awesome-list, resources.
  • More GitHub stars (484k vs 4.1k) - visibility, not fit.

When NOT to use awesome

  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Choose AI-Infra-Guard if…

  • License: AI-Infra-Guard is Apache-2.0, awesome is CC0-1.0.
  • Tags unique to AI-Infra-Guard: agent, agent-security, ai-infra, ai-red-teaming.
  • Also covers AI Agents, Vector Databases.

When NOT to use AI-Infra-Guard

  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: awesome 484k · AI-Infra-Guard 4.1k (synced Jul 11, 2026).

Common questions

What is the difference between awesome and AI-Infra-Guard?
awesome: 😎 Curated list of awesome topics including hardware resources. AI-Infra-Guard: A full-stack AI Red Teaming platform securing AI ecosystems via OpenClaw Security Scan, Agent Scan, Skills Scan, MCP scan, AI Infra scan and LLM jailbreak evaluation.. See the comparison table for live GitHub stats and shared categories.
When should I choose awesome over AI-Infra-Guard?
Choose awesome over AI-Infra-Guard when License: awesome is CC0-1.0, AI-Infra-Guard is Apache-2.0; Tags unique to awesome: awesome-list, resources; More GitHub stars (484k vs 4.1k) - visibility, not fit.
When should I choose AI-Infra-Guard over awesome?
Choose AI-Infra-Guard over awesome when License: AI-Infra-Guard is Apache-2.0, awesome is CC0-1.0; Tags unique to AI-Infra-Guard: agent, agent-security, ai-infra, ai-red-teaming; Also covers AI Agents, Vector Databases.
When should I avoid awesome?
LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
When should I avoid AI-Infra-Guard?
AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
Is awesome or AI-Infra-Guard more popular on GitHub?
awesome has more GitHub stars (484,026 vs 4,091). Stars measure visibility, not whether either tool fits your constraints.
Are awesome and AI-Infra-Guard open source?
Yes - both are open-source projects on GitHub (awesome: CC0-1.0, AI-Infra-Guard: Apache-2.0).
Where can I find alternatives to awesome or AI-Infra-Guard?
GraphCanon lists graph-backed alternatives at awesome alternatives and AI-Infra-Guard alternatives (awesome markdown twin, AI-Infra-Guard 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, awesome or AI-Infra-Guard?
awesome: Active. AI-Infra-Guard: Very 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 awesome and AI-Infra-Guard?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome trust report; AI-Infra-Guard trust report.