CWE-Bench-AA Benchmark Leaderboard
CWE-Bench-AA pass@1
スコア
CWE-Bench-AA
CWE-Bench-AA:スコア vs. タスクあたりのコスト
トークン使用量
CWE-Bench-AA:タスクあたりの出力トークン
コスト
CWE-Bench-AA:タスクあたりのコスト
速度
CWE-Bench-AA:タスクあたりの時間
スコア vs. リリース日
CWE-Bench-AA:スコア vs. リリース日
よくある質問
CWE-Bench-AA は、Collinear AI の防御的サイバーセキュリティベンチマーク CWE-bench を Artificial Analysis が実装したものです。各タスクでコーディングエージェントは実在するオープンソースリポジトリのチェックアウトと、コードを監査して見つけた問題を修正するという 1 つの指示を受け取ります。懸念される領域は示されますが正確な場所は明かされず、exploit の作成も求められません。評価セットは 120 の非公開タスクで、OWASP Top 10(2025)の全 10 カテゴリを網羅し、C/C++、Go、Java、JavaScript/TypeScript、Python、Rust を対象とします。
各タスクには、エージェント終了後に実行される決定的なプログラム検証があります。exploit が機能しなくなり、正当な動作が引き続き機能する場合のみ解決となります。検証結果は 1 または 0 です。主要スコア pass@1 は、120 タスクのうち 1 回の試行で解決した割合です。
どちらも同じ非公開タスクと同じ決定的な検証を使いますが、実行方法には 3 つの違いがあります。Collinear AI は Claude Code や Codex、オープンウェイトモデル向けの Terminus-2 など、各ベンダーのエージェント製品でモデルを実行し、タスクごとに 4 回試行して pass@1 と pass@4 を報告します。さらに LLM が評価する部分点のトラックも記録します。CWE-Bench-AA はすべてのモデルを当社のオープンソース Stirrup エージェントハーネスと同じエージェント prompt で実行し、各タスクを 1 回だけ試して、決定的な検証のみを採点します。そのため、このページのスコアは Collinear AI の公開結果と直接比較できません。
いいえ。120 タスクの評価セットは Collinear AI と Artificial Analysis が非公開で保持し、外部組織には提供していません。これは学習データ汚染のリスクを減らすのに役立ちます。Collinear AI は評価セットと重複しない 1,000 件以上のタスクからなる学習用コーパスを別途提供しています。
はい。CWE-Bench-AA は Artificial Analysis Cyber Index を構成する 3 つの評価の 1 つで、DeepsecBench-AA および CyberGym-E2E-AA と同じ重みです。Artificial Analysis Intelligence Index には含まれません。
評価を探す
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