Artificial Analysis Cyber Index
Aggregator index (Artificial Analysis) measuring a model's ability to discover vulnerabilities in a codebase, reproduce and validate them, and patch them without breaking existing functionality, without unnecessary refusals. Blog: ML4 scores 51%.
Category
Composite
Score type
percent
Scale
100%
higher is better
Models tested
1
What is Artificial Analysis Cyber Index?
Artificial Analysis Cyber Index is a benchmark for an aggregated index computed from several underlying benchmarks. The official description says: "Aggregator index (Artificial Analysis) measuring a model's ability to discover vulnerabilities in a codebase, reproduce and validate them, and patch them without breaking existing functionality, without unnecessary refusals". Below we describe in simple words what benchmarks of this type generally examine.
What does it test?
Artificial Analysis Cyber Index measures an aggregated index computed from several underlying benchmarks. In detail, it checks:
- a weighted synthesis of many individual evaluations
- coverage (how many different skills the model performed on)
- recency (favouring newly released models)
- none of the weaknesses that a single narrow benchmark would hide
How to read the score
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.
Official methodology note: Aggregator index (Artificial Analysis) measuring a model's ability to discover vulnerabilities in a codebase, reproduce and validate them, and patch them without breaking existing functionality, without unnecessary refusals. Blog: ML4 scores 51%.
Frequently asked questions
What is the Artificial Analysis Cyber Index benchmark?
Artificial Analysis Cyber Index is a benchmark for an aggregated index computed from several underlying benchmarks. The official description says: 'Aggregator index (Artificial Analysis) measuring a model's ability to discover vulnerabilities in a codebase, reproduce and validate them, and patch them without breaking existing functionality, without unnecessary refusals'. Below we describe in simple words what benchmarks of this type generally examine.
What does Artificial Analysis Cyber Index test?
Artificial Analysis Cyber Index mainly measures an aggregated index computed from several underlying benchmarks. Concretely, it checks: a weighted synthesis of many individual evaluations; coverage (how many different skills the model performed on); recency (favouring newly released models).
How is the Artificial Analysis Cyber Index score calculated?
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.
Where do I get Artificial Analysis Cyber Index data and scores?
The official source is https://mistral.ai/news/mistral-large-4-oss/. The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/aa-cyber-index/scores) or pull it directly from the Open LLM Radar API with any HTTP client.
Benchmark data & downloads
Where to get, inspect and reuse the data behind this benchmark.
Official benchmark page / paper
The benchmark maintainer's website, paper or leaderboard
Benchmark metadata (JSON)
This page's benchmark record from the Open LLM Radar API
All model scores (JSON download)
Full score table as JSON; paginate with limit/offset params
Open LLM Radar API docs
Swagger UI to explore and reuse all radar API endpoints
Model scores 1 model tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
Mistral Large 4
Mistral AI
|
51%
|
— | Mistral blog: Artificial Analysis Cyber Index 51% | Verified |