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Alternatives hub · graph-backed

llm-attacks alternatives

In short

Top alternatives to llm-attacks are GPTFuzz and IB4LLMs, ranked by typed graph edges - evaluation-observability.

Not a popularity vote. Each alternative is a typed graph neighbor of llm-attacks in Evaluation & Observability, LLM Frameworks - ranked by edge type and constraint overlap, with live GitHub stats shown for context.

llm-attacks trust report - maintenance, provenance, and scan signals for llm-attacks.

GraphCanon updated 2w · GitHub pushed 2y · 26 views this month

llm-attacks alternatives (markdown)

Constraints24 of 24 match
GPTFuzz logo
GPTFuzzrelated

Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts

Pythonevaluation-observabilityllm-frameworks
604
stars
IB4LLMs logo
IB4LLMsrelated

Protecting Your LLMs with Information Bottleneck

Pythonevaluation-observabilityllm-frameworks
25
stars
Open-Prompt-Injection logo
Open-Prompt-Injectionrelated

Benchmark and toolkit for prompt injection attacks and defenses in LLMs

Pythonevaluation-observabilityllm-frameworks
470
stars
trap logo
traprelated

TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification

Jupyter Notebookevaluation-observabilityllm-frameworks
15
stars
ALERT logo
ALERTrelated

A Comprehensive Benchmark for Assessing Large Language Models' Safety Through Red Teaming

Pythonevaluation-observability
59
stars
AutoDefense logo
AutoDefenserelated

Multi-Agent LLM Defense against Jailbreak Attacks

Pythonevaluation-observability
68
stars
awesome-llm-security logo
awesome-llm-securityrelated

A curation of tools, documents and projects about LLM Security

Freemiumevaluation-observability
1.7k
stars
awesome-llms-fine-tuning logo
awesome-llms-fine-tuningrelated

A comprehensive collection of resources for fine-tuning Large Language Models.

llm-frameworks
525
stars
baseline-defenses logo
baseline-defensesrelated

Research code for evaluating defenses against adversarial attacks on aligned language models

Pythonevaluation-observability
34
stars
BIPIA logo
BIPIArelated

Benchmark for evaluating LLM robustness to indirect prompt injection attacks.

Pythonevaluation-observability
149
stars
CipherChat logo
CipherChatrelated

A framework to assess safety alignment generalization in LLMs for non-natural languages

Pythonevaluation-observability
628
stars
circle-guard-bench logo
circle-guard-benchrelated

AI benchmark for evaluating LLM guard systems

Pythonevaluation-observability
72
stars
Confidence_Elicitation_Attacks logo
Confidence_Elicitation_Attacksrelated

Confidence Elicitation Attacks on Large Language Models

Pythonevaluation-observability
6
stars
deepeval logo
deepevalrelated

LLM Evaluation Framework.

Pythonevaluation-observability
17k
stars
DeepInception logo
DeepInceptionrelated

Develops techniques to influence large language model behavior

FreemiumPythonllm-frameworks
177
stars
do-not-answer logo
do-not-answerrelated

A Dataset for Evaluating Safeguards in LLMs

Jupyter Notebookevaluation-observability
339
stars
embedguard logo
embedguardrelated

Cross-Layer Detection and Provenance Attestation for Adversarial Embedding Attacks in RAG Systems

Pythonevaluation-observability
0
stars
fast-llm-security-guardrails logo
fast-llm-security-guardrailsrelated

The fastest Trust Layer for AI Agents

Pythonevaluation-observability
154
stars
FuzzyAI logo
FuzzyAIrelated

A tool for automated LLM fuzzing to detect and mitigate jailbreaks

Jupyter Notebookevaluation-observability
1.5k
stars
hallucination-index logo
hallucination-indexrelated

Initiative to evaluate and rank popular LLMs based on hallucination propensity

evaluation-observability
116
stars
instruct-eval logo
instruct-evalrelated

Quantitative evaluation for instruction-tuned language models

Pythonevaluation-observability
552
stars
jailbreakbench logo
jailbreakbenchrelated

An Open Robustness Benchmark for Jailbreaking Language Models

Pythonevaluation-observability
645
stars
langevals logo
langevalsrelated

Provides a platform for evaluating and benchmarking LLM models using various evaluators

evaluation-observability
72
stars
last_layer logo
last_layerrelated

Ultra-fast low latency LLM prompt injection jailbreak detection

Pythonevaluation-observability
131
stars

When NOT to use llm-attacks

Constraint-first guidance from category fit and live maintenance signals - not marketing copy.

  • 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.

Related alternatives hubs

High-intent OSS-vs-OSS alternatives pages elsewhere in the graph (including vector-DB picks for Pinecone-style queries).

Head-to-head comparisons

Common questions

What are the best alternatives to llm-attacks?
Graph-backed alternatives to llm-attacks include GPTFuzz, IB4LLMs, Open-Prompt-Injection, trap, ALERT. GraphCanon ranks them by typed relationship edges and constraint overlap from decision_facts - not marketing votes or raw star sort.
How does GraphCanon rank llm-attacks alternatives?
Direct alternative and successor edges from the knowledge graph come first, ordered by edge type and shared constraint facets (persona, runtime, hosting). Category neighbours fill the list only after curated edges. Stars are shown for context, not as the primary sort.
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 llm-attacks open source?
Yes. llm-attacks is an open-source project on GitHub under the MIT license, with 4,756 stars.
What is llm-attacks used for?
A repository focusing on attacks targeting aligned language models with dependencies on FastChat.
What category is llm-attacks in?
llm-attacks is categorized under Evaluation & Observability, LLM Frameworks in the GraphCanon knowledge graph.
How do llm-attacks alternatives compare head-to-head?
Each alternative has a neutral compare page against llm-attacks, for example GPTFuzz vs llm-attacks, IB4LLMs vs llm-attacks, Open-Prompt-Injection vs llm-attacks. Stats come from live GitHub metadata.
Is there a machine-readable alternatives list?
Yes. The markdown twin at llm-attacks alternatives lists direct alternatives and same-category tools with internal links to each tool markdown page.
Where are other high-intent alternatives hubs?
Related P0 OSS-vs-OSS hubs: LangChain alternatives, LlamaIndex alternatives, Qdrant alternatives, FinRobot alternatives, free-llm-api-resources alternatives, caveman alternatives, rtk alternatives, unsloth alternatives, ollama alternatives. Vector-database intent (including Pinecone-style queries) is covered at Qdrant alternatives.
Where can I see maintenance and security signals for llm-attacks?
GraphCanon publishes a sourced trust report for llm-attacks at llm-attacks trust report - maintenance posture, fork provenance, and dependency/MCP scan status with methodology tags. Not a safety grade.

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