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Comparison

llm-attacks vs IB4LLMs

Verdict

Pick llm-attacks if llm-attacks: Universal and Transferable Attacks on Aligned Language Models with dependency on FastChat; pick IB4LLMs if iB4LLMs (IBProtector) is an LLM jailbreak defense method using the Information Bottleneck principle to prevent adversarial prompts while preserving key information.

Markdown twin · llm-attacks alternatives · IB4LLMs alternatives

GraphCanon updated 2w

llm-attacks logo

llm-attacks

llm-attacks/llm-attacks

★ 4.8kpushed Aug 2, 2024
vs
IB4LLMs logo

IB4LLMs

zichuan-liu/IB4LLMs

★ 25pushed Nov 7, 2024

Trust & integrity

Signalllm-attacksIB4LLMs
Maintenance
Dormant (732d since push)
As of 2w · github_public_v1
Dormant (635d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Personal account
As of 2w · github_public_v1
OSV dependency advisories
Published findings
As of 1mo · osv@v1
Published findings
As of 1mo · 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
llm-attacks trust reportIB4LLMs trust reportTrust methodology

Tagline

llm-attacks
Universal and Transferable Attacks on Aligned Language Models
IB4LLMs
Protecting Your LLMs with Information Bottleneck

Stars

llm-attacks
4.8k
IB4LLMs
25

Forks

llm-attacks
633
IB4LLMs
2

Open issues

llm-attacks
69
IB4LLMs
4

Language

llm-attacks
Python
IB4LLMs
Python

Adopt for

llm-attacks
llm-attacks: Universal and Transferable Attacks on Aligned Language Models with dependency on FastChat.
IB4LLMs
IB4LLMs (IBProtector) is an LLM jailbreak defense method using the Information Bottleneck principle to prevent adversarial prompts while preserving key information.

Persona

llm-attacks
-
IB4LLMs
-

Runtime

llm-attacks
-
IB4LLMs
-

License

llm-attacks
MIT
IB4LLMs
-

Last pushed

llm-attacks
Aug 2, 2024
IB4LLMs
Nov 7, 2024

Categories

llm-attacks
Evaluation & Observability, LLM Frameworks
IB4LLMs
Evaluation & Observability, LLM Frameworks

Trust and health

Days since push

llm-attacks
732d
IB4LLMs
635d

Open issues (now)

llm-attacks
69
IB4LLMs
4

Owner type

llm-attacks
Organization
IB4LLMs
User

Full report

llm-attacks
Trust report
IB4LLMs
Trust report

Shared compatibility

  • Python · llm-attacks: Python runtime · IB4LLMs: Python runtime

Choose llm-attacks if…

  • Tags unique to llm-attacks: alignment-testing, attacks, fastchat-dependency, language-models.
  • When you need to test the robustness of aligned language models specifically using attacks designed for these systems,
  • More GitHub stars (4.8k vs 25) - visibility, not fit.

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.
GitHubDetails

Choose IB4LLMs if…

  • Pricing: License information unavailable; specific model pricing not provided..
  • Requirements: Dependencies include datasets==2.14.5, torch==2.1.1, transformers==4.40.1 among others..
  • Tags unique to IB4LLMs: evaluation scripts, finetuning, inference, information bottleneck.
  • When you need a specialized tool for guarding against jailbreaks in your language models without losing important data.

When NOT to use IB4LLMs

  • If you require a more generalized model protection approach that does not rely strictly on the Information Bottleneck principle.
  • When your environment lacks support for specific packages like `fschat==0.2.20` which is crucial and cannot be updated due to potential conflicts.
GitHubDetails

Explore

llm-attacks trust report →IB4LLMs trust report →Evaluation & Observability category →LLM Frameworks category →All comparisonsStack workflowsTrending tools

Sources

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

GitHub stars on cards: llm-attacks 4.8k · IB4LLMs 25 (synced Aug 5, 2026).

Common questions

What is the difference between llm-attacks and IB4LLMs?
llm-attacks: Universal and Transferable Attacks on Aligned Language Models. IB4LLMs: Protecting Your LLMs with Information Bottleneck. See the comparison table for live GitHub stats and shared categories.
When should I choose llm-attacks over IB4LLMs?
Choose llm-attacks over IB4LLMs when Tags unique to llm-attacks: alignment-testing, attacks, fastchat-dependency, language-models; When you need to test the robustness of aligned language models specifically using attacks designed for these systems,; More GitHub stars (4.8k vs 25) - visibility, not fit.
When should I choose IB4LLMs over llm-attacks?
Choose IB4LLMs over llm-attacks when Pricing: License information unavailable; specific model pricing not provided.; Requirements: Dependencies include datasets==2.14.5, torch==2.1.1, transformers==4.40.1 among others.; Tags unique to IB4LLMs: evaluation scripts, finetuning, inference, information bottleneck; When you need a specialized tool for guarding against jailbreaks in your language models without losing important data.
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.
When should I avoid IB4LLMs?
If you require a more generalized model protection approach that does not rely strictly on the Information Bottleneck principle. When your environment lacks support for specific packages like fschat==0.2.20 which is crucial and cannot be updated due to potential conflicts.
Is llm-attacks or IB4LLMs more popular on GitHub?
llm-attacks has more GitHub stars (4,756 vs 25). Stars measure visibility, not whether either tool fits your constraints.
Are llm-attacks and IB4LLMs open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to llm-attacks or IB4LLMs?
GraphCanon lists graph-backed alternatives at llm-attacks alternatives and IB4LLMs alternatives (llm-attacks markdown twin, IB4LLMs 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, llm-attacks or IB4LLMs?
llm-attacks: Dormant. IB4LLMs: 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 llm-attacks and IB4LLMs?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llm-attacks trust report; IB4LLMs trust report.

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