Home/Compare/awesome-llm-security vs llm-attacks

Comparison

awesome-llm-security vs llm-attacks

Verdict

Pick awesome-llm-security if awesome LLM Security is a curated list of resources related to the security aspects of large language models. It covers various attack methodologies, defenses, and platform security through papers, benchmarks, tools, and; pick llm-attacks if llm-attacks: Universal and Transferable Attacks on Aligned Language Models with dependency on FastChat.

Markdown twin · awesome-llm-security alternatives · llm-attacks alternatives

GraphCanon updated Oct 4, 2026

15views this month

awesome-llm-security logo

awesome-llm-security

corca-ai/awesome-llm-security

★ 1.7kpushed Aug 20, 2025
vs
llm-attacks logo

llm-attacks

llm-attacks/llm-attacks

★ 4.8kpushed Aug 2, 2024

Trust & integrity

Signalawesome-llm-securityllm-attacks
Maintenance
Dormant (382d since push)
As of Sep 6, 2026 · github_public_v1
Dormant (792d since push)
As of Oct 4, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 6, 2026 · github_public_v1
Not a fork · Organization account
As of Oct 4, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
Published findings
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

awesome-llm-security
A curation of tools, documents and projects about LLM Security
llm-attacks
Universal and Transferable Attacks on Aligned Language Models

Stars

awesome-llm-security
1.7k
llm-attacks
4.8k

Forks

awesome-llm-security
347
llm-attacks
641

Open issues

awesome-llm-security
207
llm-attacks
69

Language

awesome-llm-security
-
llm-attacks
Python

Adopt for

awesome-llm-security
Awesome LLM Security is a curated list of resources related to the security aspects of large language models. It covers various attack methodologies, defenses, and platform security through papers, benchmarks, tools, and
llm-attacks
llm-attacks: Universal and Transferable Attacks on Aligned Language Models with dependency on FastChat.

Persona

awesome-llm-security
-
llm-attacks
-

Runtime

awesome-llm-security
-
llm-attacks
-

License

awesome-llm-security
-
llm-attacks
MIT

Last pushed

awesome-llm-security
Aug 20, 2025
llm-attacks
Aug 2, 2024

Categories

awesome-llm-security
Evaluation & Observability
llm-attacks
Evaluation & Observability, LLM Frameworks

Trust and health

Days since push

awesome-llm-security
382d
llm-attacks
792d

Open issues (now)

awesome-llm-security
207
llm-attacks
69

Stars delta

awesome-llm-security
+20 (30d)
llm-attacks
+58 (30d)

Open issues delta

awesome-llm-security
+34 (30d)
llm-attacks
0 (30d)

OSV dependency advisories

awesome-llm-security
No lockfile (source not queried)
llm-attacks
Published findings

Full report

awesome-llm-security
Trust report
llm-attacks
Trust report

Choose awesome-llm-security if…

  • Pricing: As an open-source project without defined pricing models, its use is generally free under the terms of its license (license details are not provided)..
  • Tags unique to awesome-llm-security: awesome-list, llm, security.
  • When you are specifically looking for detailed information on both white-box and black-box attacks targeted at Large Language Models (LLMs), which 'awesome-llm-security' comprehensively catalogs.

When NOT to use awesome-llm-security

  • When your primary interest is in general software security or vulnerabilities unrelated to language models, since 'awesome-llm-security' zeroes in on attack vectors specifically for LLMs.
  • If you are solely interested in tools and methods that are not publicly discussed or peer-reviewed; the repository focuses on documented approaches within reputable academic publications.

Choose llm-attacks if…

  • Tags unique to llm-attacks: alignment-testing, attacks, fastchat-dependency, language models.
  • Also covers LLM Frameworks.
  • When you need to test the robustness of aligned language models specifically using attacks designed for these systems,

When NOT to use llm-attacks

  • Do not use if you are evaluating generic or unaligned language models without a need for alignment-specific attack testing,
  • Avoid when FastChat is not used in your project as llm-attacks explicitly depends on it.

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-llm-security 1.7k · llm-attacks 4.8k (synced Sep 20, 2026).

Common questions

What is the difference between awesome-llm-security and llm-attacks?
awesome-llm-security: A curation of tools, documents and projects about LLM Security. llm-attacks: Universal and Transferable Attacks on Aligned Language Models. See the comparison table for live GitHub stats and shared categories.
When should I choose awesome-llm-security over llm-attacks?
Choose awesome-llm-security over llm-attacks when Pricing: As an open-source project without defined pricing models, its use is generally free under the terms of its license (license details are not provided).; Tags unique to awesome-llm-security: awesome-list, llm, security; When you are specifically looking for detailed information on both white-box and black-box attacks targeted at Large Language Models (LLMs), which 'awesome-llm-security' comprehensively catalogs.
When should I choose llm-attacks over awesome-llm-security?
Choose llm-attacks over awesome-llm-security when Tags unique to llm-attacks: alignment-testing, attacks, fastchat-dependency, language models; Also covers LLM Frameworks; When you need to test the robustness of aligned language models specifically using attacks designed for these systems,.
When should I avoid awesome-llm-security?
When your primary interest is in general software security or vulnerabilities unrelated to language models, since 'awesome-llm-security' zeroes in on attack vectors specifically for LLMs. If you are solely interested in tools and methods that are not publicly discussed or peer-reviewed; the repository focuses on documented approaches within reputable academic publications.
When should I avoid llm-attacks?
Do not use if you are evaluating generic or unaligned language models without a need for alignment-specific attack testing, Avoid when FastChat is not used in your project as llm-attacks explicitly depends on it.
Is awesome-llm-security or llm-attacks more popular on GitHub?
llm-attacks has more GitHub stars (4,814 vs 1,692). Stars measure visibility, not whether either tool fits your constraints.
Are awesome-llm-security and llm-attacks open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to awesome-llm-security or llm-attacks?
GraphCanon lists graph-backed alternatives at awesome-llm-security alternatives and llm-attacks alternatives (awesome-llm-security markdown twin, llm-attacks 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-llm-security or llm-attacks?
awesome-llm-security: Dormant. llm-attacks: Dormant. 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-llm-security and llm-attacks?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-llm-security trust report; llm-attacks trust report.

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