List of AI Security benchmarks (with some datasets, working on a seperate repo for datasets).
THIS IS A WORK IN PROGRESS. I need to fix some of the categorizations and add more. There may be some errors and hallucinations just fyi.
Come chat about AI Security benchmarks in the AI Hacking Discord https://discord.com/channels/1422426099391922258/1422426100067471462/1469143844216897588
Total unique benchmarks: ~175 (165 core cybersecurity + 10 AI security adjacent)
| Benchmark | Year | Type | Links | Definition |
|---|---|---|---|---|
| KNOWLEDGE & Q&A | ||||
| SecEval | 2023 | Dataset | GitHub | HuggingFace | Website | 2000+ multiple-choice questions across 9 security domains, GPT-4 generated from textbooks and standards |
| SecQA | 2023 | Dataset | arXiv:2312.15838 | HuggingFace | Multiple-choice questions from "Computer Systems Security" textbook with two complexity tiers |
| CyberMetric | 2024 | Dataset | arXiv:2402.07688 | GitHub | RAG-generated MCQ datasets (80/500/2000/10000 variants) from NIST standards, research papers, and cybersecurity books |
| SECURE | 2024 | Dataset | arXiv:2405.20441 | GitHub | 6 datasets (MAET, CWET, KCV, VOOD, RERT, CPST) for ICS cybersecurity evaluation |
| SEvenLLM-Bench | 2024 | Dataset | arXiv:2405.03446 | GitHub | 1,300-sample bilingual benchmark for CTI analytical capabilities with 28 tasks |
| CS-Eval | 2024 | Dataset | arXiv:2411.16239 | GitHub | Comprehensive LLM benchmark for cybersecurity knowledge evaluation |
| SecBench | 2024 | Dataset | arXiv:2412.20787 | HuggingFace | Multi-dimensional, multi-language benchmarking dataset for LLMs in cybersecurity |
| CSEBenchmark | 2025 | Dataset | arXiv:2504.11783 | GitHub | Fine-grained cyber-security evaluation based on 345 knowledge points (IEEE S&P 2025) |
| AttackQA | 2024 | Dataset | arXiv:2408.16847 | Dataset for assisting cybersecurity operations using LLMs |
| CyberBench | 2024 | Dataset | GitHub | Multi-task benchmark over multiple cybersecurity NLP task datasets (JPMorganChase) |
| CySecBench | 2025 | Dataset | arXiv:2501.01335 | Generative AI-based cybersecurity-focused prompt dataset (12,662 prompts) |
| AthenaBench | 2025 | Dataset | arXiv:2511.01144 | CTI-focused dynamic evaluation tasks for LLMs |
| OCCULT | 2025 | Framework | arXiv:2502.15797 | Offensive tactic knowledge evaluation framework |
| MMLU Computer Security | 2021 | Dataset | HuggingFace | Standard MMLU benchmark's dedicated computer security subset |
| MMLU Security Studies | 2021 | Dataset | HuggingFace | Standard MMLU benchmark's security studies subset |
| CTF & OFFENSIVE SECURITY | ||||
| InterCode-CTF | 2023 | Environment | arXiv:2306.14898 | GitHub | Website | 100 CTF tasks from PicoCTF with containerized bash execution environment |
| NYU CTF Bench | 2024 | Environment | arXiv:2406.05590 | GitHub | Website | 200 challenges from CSAW CTF spanning crypto, forensics, web, reverse engineering, pwn |
| Cybench | 2024 | Environment | arXiv:2408.08926 | GitHub | Website | 40 professional CTF tasks from HackTheBox, SekaiCTF, Glacier, HKCert |
| 3CB | 2024 | Environment | arXiv:2410.09114 | Website | Advanced CTF challenges designed to be harder than Cybench |
| BountyBench | 2025 | Environment | Website | GitHub | Real-world vulnerability detection, exploitation, and patching with dollar impact |
| RCTF2 | 2025 | Environment | arXiv:2510.24317 | Robotics/cyber-physical sub-benchmark inside CAIBench (27 challenges) |
| CTFKnow | 2025 | Dataset | arXiv:2501.09564 | CTF technical knowledge benchmark built from CTF writeups |
| CTF-Dojo | 2025 | Environment | arXiv:2501.17535 | Large-scale executable runtime of containerized CTF challenges |
| AIRTBench | 2025 | Environment | arXiv:2506.14682 | Autonomous AI red-teaming benchmark; 70 black-box CTFs |
| Crowdsourced CTF Elicitation | 2025 | Framework | arXiv:2505.19915 | Evaluating AI cyber capabilities with crowdsourced elicitation (CTF-based) |
| PENETRATION TESTING | ||||
| PentestGPT Benchmark | 2023 | Harness | arXiv:2308.06782 | GitHub | 182 sub-tasks from HackTheBox and VulnHub for penetration testing |
| AutoPenBench | 2024 | Environment | arXiv:2410.03225 | GitHub | Benchmarking generative agents for pentesting with defined milestones |
| PentestEval | 2025 | Harness | arXiv:2512.14233 | Stage-specific evaluation across entire pentesting lifecycle |
| Vulhub Benchmark | 2024 | Environment | GitHub | Docker-based vulnerable environments for automated pentesting |
| CHECKMATE | 2025 | Framework | arXiv:2503.12735 | Planning + LLM agents for automated penetration testing |
| PenHeal | 2023 | Framework | arXiv:2312.03015 | AI cybersecurity capabilities evaluation for pentesting and healing |
| AutoAttacker | 2024 | Framework | arXiv:2403.01038 | Automated cyber-attack generation and evaluation benchmark |
| AI-Pentest-Benchmark | 2024 | Environment | arXiv:2410.17141 | GitHub | 13 VulnHub VMs with 152 subtasks ("Towards Automated Penetration Testing") |
| TermiBench | 2025 | Environment | arXiv:2509.09207 | Real-world pentesting benchmark; 510 hosts/30 CVEs; shell-focused |
| CTFTiny | 2025 | Dataset | arXiv:2508.05674 | Curated 50 representative CTF challenges for rapid evaluation of offensive-security agents |
| CVE-Bench | 2025 | Environment | arXiv:2503.17332 | GitHub | Real-world webapp vulnerability exploitation based on critical CVEs |
| XBOW Validation | 2025 | Environment | Website | 104 web security challenges for autonomous offensive tools |
| CyberGym | 2025 | Environment | arXiv:2506.02548 | HuggingFace | 1,507 instances from 188 OSS projects with ASan/UBSan validation |
| Cyberattack Capabilities Framework | 2025 | Framework | arXiv:2503.11917 | DeepMind Blog | End-to-end attack chain evaluation with representative archetypes |
| VULNERABILITY DETECTION | ||||
| VulDetectBench | 2024 | Dataset | arXiv:2406.07595 | GitHub | Vulnerability detection benchmark with 5 tasks (identify/classify/localize, etc.) |
| CyberSecEval v1 | 2023 | Harness | arXiv:2312.04724 | GitHub | Evaluates LLMs for insecure code generation propensity (Purple Llama) |
| CyberSecEval v2 | 2024 | Harness | arXiv:2404.13161 | GitHub | Extended benchmark with vulnerability exploitation and prompt injection tests |
| CyberSecEval v3 | 2024 | Harness | arXiv:2408.01605 | GitHub | Further advances in evaluating LLM cybersecurity risks |
| CyberSecEval v4 | 2025 | Meta-benchmark | GitHub | Website | Meta's latest suite; includes AutoPatchBench and CyberSOCEval |
| AutoPatchBench | 2025 | Dataset | Blog | Benchmark for automated repair of fuzzing-discovered vulnerabilities (part of CyberSecEval 4) |
| CyberSOCEval | 2025 | Dataset | arXiv:2509.20166 | Meta | SOC-focused benchmarks for malware analysis + threat-intelligence reasoning (part of CyberSecEval 4) |
| SecLLMHolmes | 2024 | Framework | arXiv:2405.19803 | GitHub | Fully automated framework for evaluating LLM vulnerability detection |
| SecVulEval | 2025 | Dataset | arXiv:2505.19828 | C/C++ vulnerability detection with statement-level granularity |
| VulnLLMEval | 2024 | Framework | arXiv:2401.16185 | Framework for evaluating LLMs in vulnerability detection and patching |
| LLMSecCode | 2024 | Harness | arXiv:2408.17894 | Benchmark for evaluating secure code practices in LLMs |
| eyeballvul | 2024 | Dataset | arXiv:2407.08708 | GitHub | Future-proof benchmark for vulnerability detection in the wild |
| VADER | 2025 | Framework | arXiv:2505.19395 | GitHub | Human-evaluated framework for Vulnerability Assessment, Detection, Explanation |
| SVEN | 2023 | Framework | arXiv:2302.05319 | GitHub | Security hardening & adversarial testing for code LLMs (controlled code generation) |
| PrimeVul | 2024 | Dataset | arXiv:2403.18624 | GitHub | Filtered C/C++ function-level vulnerability detection dataset (ICSE 2025) |
| ARVO | 2024 | Dataset | arXiv:2411.09278 | Project-level C/C++ vulnerability detection benchmark |
| Juliet Test Suite 1.3 | 2017 | Dataset | NIST | NIST's comprehensive test cases for C/C++ and Java vulnerability detection |
| SV-TrustEval-C | 2025 | Dataset | arXiv:2505.20630 | Structure and semantic reasoning benchmark for C vulnerability analysis |
| VulGate | 2025 | Dataset | arXiv:2508.16625 | Dataset with dedicated test sets for vulnerability detection generalization |
| Multi-Vuln Detection | 2025 | Dataset | arXiv:2512.22306 | Long-context multi-label vulnerability benchmark across languages |
| Multi-Lang SVD | 2025 | Dataset | arXiv:2503.01449 | Multi-language software vulnerability detection benchmark study |
| SECURE CODE GENERATION | ||||
| CodeSecEval | 2024 | Harness | arXiv:2407.02395 | Evaluating LLMs on secure code generation with CWE-based evaluation |
| CodeLMSec | 2024 | Harness | arXiv:2302.04012 | Systematically evaluating security vulnerabilities in black-box code LMs |
| SecurityEval | 2022 | Dataset | arXiv:2210.09263 | GitHub | Mining vulnerability examples to evaluate ML-based code generation |
| SecCodePLT | 2024 | Harness | arXiv:2410.11096 | GitHub | Unified platform for evaluating code GenAI security with 27 CWEs |
| CWEval | 2025 | Harness | arXiv:2501.08200 | GitHub | Outcome-driven evaluation for functionality and security of LLM code |
| SafeGenBench | 2025 | Dataset | arXiv:2506.05692 | 558 security-sensitive test questions covering vulnerability taxonomy (ByteDance) |
| SecRepoBench | 2025 | Dataset | arXiv:2504.21205 | Repository-level secure coding with 318 tasks across 27 repos |
| SecureAgentBench | 2025 | Environment | arXiv:2509.22097 | 105 tasks for evaluating code agents on secure code generation |
| A.S.E | 2025 | Dataset | arXiv:2508.18106 | GitHub | Repository-level benchmark using real CVEs (Tencent) |
| SEC-bench | 2025 | Environment | arXiv:2506.11791 | Automated benchmarking of LLM agents on real-world security tasks |
| CASTLE | 2025 | Dataset | arXiv:2503.09433 | GitHub | Benchmarking dataset for static code analysis with ground-truth annotations |
| MT-Sec | 2025 | Dataset | arXiv:2503.09700 | Benchmarking correctness and security in multi-turn code generation |
| DUALGUAGE | 2025 | Harness | arXiv:2511.20709 | Automated joint security-functionality benchmarking |
| BaxBench | 2025 | Environment | arXiv:2502.11844 | GitHub | 392 backend tasks validating functionality and exploits |
| SecCodeBench | 2025 | Harness | GitHub | Alibaba's 37 test cases / 16 CWEs with dynamic PoC exploits |
| AutoPatchBench | 2025 | Component | GitHub | Automated vulnerability patching (component of CyberSecEval v4) |
| PatchEval | 2025 | Harness | arXiv:2511.11019 | Multilingual benchmark for patching real-world vulnerabilities; 1,000 CVEs |
| PACEbench | 2025 | Framework | arXiv:2510.11688 | Framework for practical AI cyber-exploitation capabilities |
| VulnRepairEval | 2025 | Framework | arXiv:2509.03331 | Exploit-based evaluation for LLM vulnerability repair |
| THREAT INTELLIGENCE & CTI | ||||
| CTIBench | 2024 | Dataset | arXiv:2406.07599 | HuggingFace | Evaluating LLMs on CTI tasks: attack patterns, threat actors, APT campaigns |
| CTI-MCQ | 2024 | Dataset | arXiv:2406.07599 | Multiple-choice questions on attack patterns, APT campaigns, detection |
| CTI-RCM | 2024 | Dataset | arXiv:2406.07599 | Root cause mapping correlating CVE records with CWE entities |
| SecKnowledge-Eval | 2025 | Dataset | arXiv:2510.14113 | Evaluation datasets for complex cybersecurity tasks |
| ExCyTIn-Bench | 2025 | Environment | arXiv:2507.14201 | Microsoft's cyber threat investigation agent benchmark |
| MALWARE & SOC | ||||
| ACSE-Eval | 2025 | Dataset | arXiv:2505.11565 | AWS Cloud Security Engineering Eval for cloud threat modeling |
| LogEval | 2024 | Dataset | arXiv:2407.01896 | Benchmark suite for LLM log analysis tasks (parsing, anomaly detection, diagnosis, summarization) |
| CyberSOCEval | 2025 | Component | GitHub | Malware analysis and threat intel reasoning (component of CyberSecEval v4) |
| Sophos SOC Benchmark | 2024 | Harness | Sophos Blog | Three SOC tasks: incident investigation, summarization, severity evaluation |
| LogLLM | 2024 | Harness | arXiv:2411.08561 | Log-based anomaly detection using large language models |
| LogLM | 2024 | Dataset | arXiv:2410.09352 | Task-based to instruction-based automated log analysis benchmark |
| DefenderBench | 2025 | Harness | arXiv:2506.00739 | GitHub | Microsoft toolkit spanning offense/defense/understanding |
| PHISHING DETECTION | ||||
| PhishAgent Benchmark | 2024 | Harness | arXiv:2408.02291 | Multimodal agent evaluation for phishing webpage detection |
| MLLM Phishing Benchmark | 2025 | Dataset | arXiv:2503.01040 | Comprehensive security benchmark for multimodal LLMs |
| Open-Source LLM Phishing | 2025 | Harness | arXiv:2503.01520 | 21 LLMs evaluated with 4 prompt engineering techniques |
| SME Phishing Detection | 2025 | Dataset | arXiv:2503.08766 | LLM evaluation for small/medium enterprise phishing |
| PhishEmailLLM Dataset | 2025 | Dataset | arXiv:2503.09270 | Meta-model approach for phishing email detection |
| APOLLO | 2024 | Harness | arXiv:2402.16862 | GPT-based tool benchmark for phishing email detection |
| PROMPT INJECTION | ||||
| AgentDojo | 2024 | Environment | arXiv:2406.13352 | GitHub | Dynamic environment for prompt injection attacks & defenses |
| INJECAGENT | 2024 | Dataset | arXiv:2403.02691 | GitHub | Benchmarking indirect prompt injections in tool-using agents |
| BIPIA | 2023 | Dataset | arXiv:2312.14197 | GitHub | First benchmark for indirect prompt injection attacks |
| GenTel-Safe / GenTel-Bench | 2024 | Framework | arXiv:2404.06531 | Unified benchmark and shielding framework for prompt injection |
| NotInject | 2024 | Dataset | arXiv:2410.22770 | GitHub | Over-defense/false-positive benchmark for prompt injection detectors (from InjecGuard) |
| PINT Benchmark | 2024 | Harness | GitHub | Lakera's benchmark for prompt injection detection systems |
| Tensor Trust | 2023 | Dataset | arXiv:2311.01011 | GitHub | Website | 126K+ human-generated prompt injection attacks |
| Open-Prompt-Injection | 2024 | Harness | arXiv:2402.12138 | Standardized framework for prompt injection vulnerability evaluation |
| safe-guard-prompt-injection | 2024 | Dataset | arXiv:2402.13064 | HuggingFace | 10,296 prompt injection examples for guardrail evaluation |
| WASP | 2025 | Environment | arXiv:2504.18575 | GitHub | Web Agent Security against Prompt injection attacks (Meta) |
| WAInjectBench | 2025 | Harness | arXiv:2510.01354 | Benchmarking prompt injection detections for web agents |
| RAS-Eval | 2025 | Harness | arXiv:2506.15253 | Security eval benchmark for LLM agents with tool execution |
| JAILBREAK & RED TEAMING | ||||
| JailbreakBench | 2024 | Harness | arXiv:2404.01318 | GitHub | Website | 200 behaviors for standardized jailbreak evaluation |
| HarmBench | 2024 | Harness | arXiv:2402.04249 | GitHub | Standardized evaluation framework for automated red teaming |
| SafetyBench | 2024 | Harness | GitHub | CAIS benchmark suite for comprehensive safety testing |
| ToxiGen | 2022 | Dataset | arXiv:2203.09509 | GitHub | Microsoft dataset for toxic/harmful content detection |
| StrongREJECT | 2024 | Dataset | arXiv:2402.10260 | GitHub | 313 forbidden questions across 6 categories |
| WildJailbreak | 2024 | Dataset | arXiv:2406.18510 | GitHub | 261,534 conversations for training LLMs to be safe |
| SORRY-Bench | 2024 | Harness | arXiv:2406.14598 | GitHub | Systematically evaluating LLM safety refusal behaviors |
| ALERT | 2024 | Harness | arXiv:2404.08676 | Comprehensive benchmark for LLM safety through red teaming |
| GPTFuzzer | 2023 | Harness | arXiv:2309.10253 | GitHub | Auto-generated jailbreak prompts for red teaming LLMs |
| SG-Bench | 2024 | Harness | arXiv:2410.21965 | Evaluating LLM safety generalization across diverse tasks |
| LatentJailbreak | 2023 | Dataset | arXiv:2307.08487 | Benchmark for evaluating text safety and output robustness |
| AdvBench | 2023 | Dataset | arXiv:2307.15043 | Adversarial behaviors dataset (foundation for many jailbreak benchmarks) |
| S-Eval | 2024 | Harness | arXiv:2405.14191 | Automatic and adaptive test generation for LLM safety |
| SAFE | 2024 | Dataset | arXiv:2404.18539 | Fine-grained safety dataset for LLMs beyond binary classification |
| DoNotAnswer | 2023 | Dataset | arXiv:2308.13387 | GitHub | Evaluating safeguards in LLMs with comprehensive refusal scenarios |
| AILuminate Jailbreak v0.5 | 2025 | Harness | MLCommons | MLCommons jailbreak benchmark (industry standard) |
| SecReEvalBench | 2025 | Dataset | arXiv:2505.07584 | Multi-turn security resilience evaluation benchmark |
| HELM Safety | 2024 | Component | Stanford HELM | Safety evaluation component of Stanford's HELM |
| Agent Security Bench (ASB) | 2024 | Harness | arXiv:2410.02644 | GitHub | Formalizing attacks and defenses in LLM-based agents (ICLR 2025) |
| AgentHarm | 2024 | Dataset | arXiv:2410.09024 | HuggingFace | UK AISI's 110 harmful agent tasks |
| b3 (Backbone Breaker Benchmark) | 2025 | Dataset | arXiv:2510.22620 | Blog | Security evaluation for backbone LLMs used inside AI agents (agent-focused adversarial attacks) |
| META-BENCHMARKS & FRAMEWORKS | ||||
| CAIBench | 2025 | Meta-benchmark | arXiv:2510.24317 | Meta-benchmark integrating Base, Cybench, AutoPenBench, CTIBench |
| CyberPII-Bench | 2025 | Dataset | arXiv:2510.24317 | PII anonymization evaluation in cybersecurity contexts |
| Cyber-Zero | 2025 | Framework | arXiv:2508.00910 | GitHub | Training framework with benchmark suites for EnIGMA+ |
| EnIGMA | 2024 | Environment | arXiv:2409.16165 | GitHub | Enhanced interactive generative model agent for CTF |
| NETWORK & IDS DATASETS | ||||
| NSL-KDD | 2009 | Dataset | UNB | Classic network intrusion detection dataset |
| CIC-IDS 2017 | 2017 | Dataset | UNB | Intrusion detection evaluation dataset |
| CSE-CIC-IDS 2018 | 2018 | Dataset | UNB | IDS/IPS dataset on AWS infrastructure |
| CIC-DDoS 2019 | 2019 | Dataset | UNB | DDoS attack evaluation dataset |
| CIRA-CIC-DoHBrw 2020 | 2020 | Dataset | UNB | DNS over HTTPS dataset |
| CIC-Bell DNS 2021 | 2021 | Dataset | UNB | DNS security dataset |
| CIC IoT Attack Dataset | 2023 | Dataset | UNB | IoT attack patterns dataset |
| CICIoV2024 | 2024 | Dataset | UNB | Internet of Vehicles security dataset |
| CICIoMT2024 | 2024 | Dataset | UNB | Medical IoT security dataset |
| IoT-DIAD | 2024 | Dataset | UNB | IoT intrusion detection and anomaly dataset |
| APT IIoT (CICADA) | 2024 | Dataset | UNB | Industrial IoT APT attack dataset |
| Datasense IIoT | 2025 | Dataset | UNB | Industrial IoT sensor data security dataset |
| BCCC-CIC-IDS2017 | 2017 | Dataset | UNB BCCC | Large-scale intrusion detection dataset |
| BCCC-CSE-CIC-IDS2018 | 2018 | Dataset | UNB BCCC | Extended large-scale IDS dataset |
| BCCC-VulSCs-2023 | 2023 | Dataset | UNB BCCC | Vulnerable smart contracts dataset |
| BCCC-SCsVuls-2024 | 2024 | Dataset | UNB BCCC | Smart contract vulnerabilities dataset |
| BCCC-cPacket-Cloud-DDoS-2024 | 2024 | Dataset | UNB BCCC | Cloud DDoS attacks dataset |
| BCCC-IoT-IDS-Zwave-2025 | 2025 | Dataset | UNB BCCC | Large-scale IoT-Zwave intrusion detection dataset |
| BCCC-DeFiFraudTrans-2025 | 2025 | Dataset | UNB BCCC | DeFi fraud transactions dataset |
| BCCC-Mal-NetMem-2025 | 2025 | Dataset | UNB BCCC | Multisource malware analysis using network traffic and memory |
| UNSW-NB15 | 2015/2024 | Dataset | UNSW | Network intrusion detection dataset (updated 2024) |
| MITRE ATLAS | 2023 | Knowledge Base | MITRE | Attack success rates for AI models (knowledge base) |
| AI SECURITY ADJACENT: ADVERSARIAL ML & ROBUSTNESS | ||||
| CIFAR-10 Adversarial | 2019 | Dataset | IBM ART | IBM ART benchmark for attack success rates |
| ADDC | 2024 | Dataset | ⚠️ Unable to verify - Mahalle et al. | Adversarial Diversity-Driven Dataset |
| DCA | 2024 | Harness | ⚠️ Unable to verify - Mahalle et al. | Aggressive events simulation for benchmark datasets |
| REA | 2024 | Harness | ⚠️ Unable to verify - Mahalle et al. | AI model threat handling evaluation |
| VMA | 2024 | Framework | ⚠️ Unable to verify - Mahalle et al. | AI model vulnerability identification benchmark |
| RobustBench | 2021 | Harness | arXiv:2010.09670 | GitHub | Website | Adversarial robustness leaderboard for image classifiers |
| AdversarialNLI (ANLI) | 2020 | Dataset | arXiv:1910.14599 | GitHub | Meta's adversarial robustness in NLI |
| AI SECURITY ADJACENT: DEEPFAKE & MEDIA | ||||
| Faceswap-GAN | 2018 | Dataset | GitHub | Deepfake detection methods evaluation |
| VidTIMIT | 2012 | Dataset | ConvAI | Video-based deepfake detection benchmark |
| FaceForensics++ | 2019 | Dataset | arXiv:1901.08971 | GitHub | Large-scale deepfake detection benchmark |
| MISCELLANEOUS | ||||
| AI Cyber Risk Benchmark | 2024 | Harness | arXiv:2412.09878 | Evaluating automated exploitation capabilities |
| ITBench | 2025 | Environment | arXiv:2502.03969 | Evaluating AI agents across IT automation tasks |
| SandboxEval | 2025 | Environment | arXiv:2504.00018 | Test suite for LLM assessment environment safety |
| CyberLLMInstruct | 2025 | Dataset | arXiv:2503.09144 | Dataset for analyzing safety of fine-tuned LLMs |
| DebugBench | 2024 | Harness | arXiv:2401.08420 | Evaluating debugging capability of LLMs |
| AttackER | 2024 | Dataset | arXiv:2408.05866 | Named entity recognition dataset for cyber-attack attribution |
| Hackphyr | 2024 | Environment | arXiv:2409.11276 | Local fine-tuned LLM agent for network security |
| CyberPal.AI | 2024 | Dataset | arXiv:2408.09304 | Expert-driven cybersecurity instructions benchmark |
| Truth Seeker Dataset | 2023 | Dataset | UNB | Misinformation detection in cybersecurity context |
| BinMetric | 2025 | Harness | arXiv:2505.07360 | Binary analysis metrics and evaluation benchmark |
| OS-Harm | 2025 | Environment | arXiv:2506.14866 | Safety of computer use agents with GUIs (150 tasks) |
| AgentThreatBench | UK AISI / inspect_evals | 2026 | Benchmark | OWASP Top 10 Agentic |
| Category | Count |
|---|---|
| Knowledge & Q&A | 15 |
| CTF & Offensive | 10 |
| Penetration Testing | 13 |
| Vulnerability Detection | 19 |
| Secure Code Generation | 20 |
| Threat Intelligence & CTI | 5 |
| Malware & SOC | 7 |
| Phishing Detection | 6 |
| Prompt Injection | 12 |
| Jailbreak & Red Teaming | 20 |
| Meta-Benchmarks | 4 |
| Network & IDS Datasets | 22 |
| Miscellaneous | 12 |
| Core Cybersecurity Benchmarks | ~165 |
| AI Security Adjacent: Adversarial ML | 7 |
| AI Security Adjacent: Deepfake & Media | 3 |
| TOTAL (incl. adjacent) | ~175 |
https://github.com/ethiack/ethibench
https://x.com/AISecHub/status/2077481328950292544
https://www.cotool.ai/research/aws-cloud-intrusion - multiple links from this one
List of AI Security benchmarks (with some datasets, working on a seperate repo for datasets).
THIS IS A WORK IN PROGRESS. I need to fix some of the categorizations and add more. There may be some errors and hallucinations just fyi.
Come chat about AI Security benchmarks in the AI Hacking Discord https://discord.com/channels/1422426099391922258/1422426100067471462/1469143844216897588
Total unique benchmarks: ~175 (165 core cybersecurity + 10 AI security adjacent)
| Benchmark | Year | Type | Links | Definition |
|---|---|---|---|---|
| KNOWLEDGE & Q&A | ||||
| SecEval | 2023 | Dataset | GitHub | HuggingFace | Website | 2000+ multiple-choice questions across 9 security domains, GPT-4 generated from textbooks and standards |
| SecQA | 2023 | Dataset | arXiv:2312.15838 | HuggingFace | Multiple-choice questions from "Computer Systems Security" textbook with two complexity tiers |
| CyberMetric | 2024 | Dataset | arXiv:2402.07688 | GitHub | RAG-generated MCQ datasets (80/500/2000/10000 variants) from NIST standards, research papers, and cybersecurity books |
| SECURE | 2024 | Dataset | arXiv:2405.20441 | GitHub | 6 datasets (MAET, CWET, KCV, VOOD, RERT, CPST) for ICS cybersecurity evaluation |
| SEvenLLM-Bench | 2024 | Dataset | arXiv:2405.03446 | GitHub | 1,300-sample bilingual benchmark for CTI analytical capabilities with 28 tasks |
| CS-Eval | 2024 | Dataset | arXiv:2411.16239 | GitHub | Comprehensive LLM benchmark for cybersecurity knowledge evaluation |
| SecBench | 2024 | Dataset | arXiv:2412.20787 | HuggingFace | Multi-dimensional, multi-language benchmarking dataset for LLMs in cybersecurity |
| CSEBenchmark | 2025 | Dataset | arXiv:2504.11783 | GitHub | Fine-grained cyber-security evaluation based on 345 knowledge points (IEEE S&P 2025) |
| AttackQA | 2024 | Dataset | arXiv:2408.16847 | Dataset for assisting cybersecurity operations using LLMs |
| CyberBench | 2024 | Dataset | GitHub | Multi-task benchmark over multiple cybersecurity NLP task datasets (JPMorganChase) |
| CySecBench | 2025 | Dataset | arXiv:2501.01335 | Generative AI-based cybersecurity-focused prompt dataset (12,662 prompts) |
| AthenaBench | 2025 | Dataset | arXiv:2511.01144 | CTI-focused dynamic evaluation tasks for LLMs |
| OCCULT | 2025 | Framework | arXiv:2502.15797 | Offensive tactic knowledge evaluation framework |
| MMLU Computer Security | 2021 | Dataset | HuggingFace | Standard MMLU benchmark's dedicated computer security subset |
| MMLU Security Studies | 2021 | Dataset | HuggingFace | Standard MMLU benchmark's security studies subset |
| CTF & OFFENSIVE SECURITY | ||||
| InterCode-CTF | 2023 | Environment | arXiv:2306.14898 | GitHub | Website | 100 CTF tasks from PicoCTF with containerized bash execution environment |
| NYU CTF Bench | 2024 | Environment | arXiv:2406.05590 | GitHub | Website | 200 challenges from CSAW CTF spanning crypto, forensics, web, reverse engineering, pwn |
| Cybench | 2024 | Environment | arXiv:2408.08926 | GitHub | Website | 40 professional CTF tasks from HackTheBox, SekaiCTF, Glacier, HKCert |
| 3CB | 2024 | Environment | arXiv:2410.09114 | Website | Advanced CTF challenges designed to be harder than Cybench |
| BountyBench | 2025 | Environment | Website | GitHub | Real-world vulnerability detection, exploitation, and patching with dollar impact |
| RCTF2 | 2025 | Environment | arXiv:2510.24317 | Robotics/cyber-physical sub-benchmark inside CAIBench (27 challenges) |
| CTFKnow | 2025 | Dataset | arXiv:2501.09564 | CTF technical knowledge benchmark built from CTF writeups |
| CTF-Dojo | 2025 | Environment | arXiv:2501.17535 | Large-scale executable runtime of containerized CTF challenges |
| AIRTBench | 2025 | Environment | arXiv:2506.14682 | Autonomous AI red-teaming benchmark; 70 black-box CTFs |
| Crowdsourced CTF Elicitation | 2025 | Framework | arXiv:2505.19915 | Evaluating AI cyber capabilities with crowdsourced elicitation (CTF-based) |
| PENETRATION TESTING | ||||
| PentestGPT Benchmark | 2023 | Harness | arXiv:2308.06782 | GitHub | 182 sub-tasks from HackTheBox and VulnHub for penetration testing |
| AutoPenBench | 2024 | Environment | arXiv:2410.03225 | GitHub | Benchmarking generative agents for pentesting with defined milestones |
| PentestEval | 2025 | Harness | arXiv:2512.14233 | Stage-specific evaluation across entire pentesting lifecycle |
| Vulhub Benchmark | 2024 | Environment | GitHub | Docker-based vulnerable environments for automated pentesting |
| CHECKMATE | 2025 | Framework | arXiv:2503.12735 | Planning + LLM agents for automated penetration testing |
| PenHeal | 2023 | Framework | arXiv:2312.03015 | AI cybersecurity capabilities evaluation for pentesting and healing |
| AutoAttacker | 2024 | Framework | arXiv:2403.01038 | Automated cyber-attack generation and evaluation benchmark |
| AI-Pentest-Benchmark | 2024 | Environment | arXiv:2410.17141 | GitHub | 13 VulnHub VMs with 152 subtasks ("Towards Automated Penetration Testing") |
| TermiBench | 2025 | Environment | arXiv:2509.09207 | Real-world pentesting benchmark; 510 hosts/30 CVEs; shell-focused |
| CTFTiny | 2025 | Dataset | arXiv:2508.05674 | Curated 50 representative CTF challenges for rapid evaluation of offensive-security agents |
| CVE-Bench | 2025 | Environment | arXiv:2503.17332 | GitHub | Real-world webapp vulnerability exploitation based on critical CVEs |
| XBOW Validation | 2025 | Environment | Website | 104 web security challenges for autonomous offensive tools |
| CyberGym | 2025 | Environment | arXiv:2506.02548 | HuggingFace | 1,507 instances from 188 OSS projects with ASan/UBSan validation |
| Cyberattack Capabilities Framework | 2025 | Framework | arXiv:2503.11917 | DeepMind Blog | End-to-end attack chain evaluation with representative archetypes |
| VULNERABILITY DETECTION | ||||
| VulDetectBench | 2024 | Dataset | arXiv:2406.07595 | GitHub | Vulnerability detection benchmark with 5 tasks (identify/classify/localize, etc.) |
| CyberSecEval v1 | 2023 | Harness | arXiv:2312.04724 | GitHub | Evaluates LLMs for insecure code generation propensity (Purple Llama) |
| CyberSecEval v2 | 2024 | Harness | arXiv:2404.13161 | GitHub | Extended benchmark with vulnerability exploitation and prompt injection tests |
| CyberSecEval v3 | 2024 | Harness | arXiv:2408.01605 | GitHub | Further advances in evaluating LLM cybersecurity risks |
| CyberSecEval v4 | 2025 | Meta-benchmark | GitHub | Website | Meta's latest suite; includes AutoPatchBench and CyberSOCEval |
| AutoPatchBench | 2025 | Dataset | Blog | Benchmark for automated repair of fuzzing-discovered vulnerabilities (part of CyberSecEval 4) |
| CyberSOCEval | 2025 | Dataset | arXiv:2509.20166 | Meta | SOC-focused benchmarks for malware analysis + threat-intelligence reasoning (part of CyberSecEval 4) |
| SecLLMHolmes | 2024 | Framework | arXiv:2405.19803 | GitHub | Fully automated framework for evaluating LLM vulnerability detection |
| SecVulEval | 2025 | Dataset | arXiv:2505.19828 | C/C++ vulnerability detection with statement-level granularity |
| VulnLLMEval | 2024 | Framework | arXiv:2401.16185 | Framework for evaluating LLMs in vulnerability detection and patching |
| LLMSecCode | 2024 | Harness | arXiv:2408.17894 | Benchmark for evaluating secure code practices in LLMs |
| eyeballvul | 2024 | Dataset | arXiv:2407.08708 | GitHub | Future-proof benchmark for vulnerability detection in the wild |
| VADER | 2025 | Framework | arXiv:2505.19395 | GitHub | Human-evaluated framework for Vulnerability Assessment, Detection, Explanation |
| SVEN | 2023 | Framework | arXiv:2302.05319 | GitHub | Security hardening & adversarial testing for code LLMs (controlled code generation) |
| PrimeVul | 2024 | Dataset | arXiv:2403.18624 | GitHub | Filtered C/C++ function-level vulnerability detection dataset (ICSE 2025) |
| ARVO | 2024 | Dataset | arXiv:2411.09278 | Project-level C/C++ vulnerability detection benchmark |
| Juliet Test Suite 1.3 | 2017 | Dataset | NIST | NIST's comprehensive test cases for C/C++ and Java vulnerability detection |
| SV-TrustEval-C | 2025 | Dataset | arXiv:2505.20630 | Structure and semantic reasoning benchmark for C vulnerability analysis |
| VulGate | 2025 | Dataset | arXiv:2508.16625 | Dataset with dedicated test sets for vulnerability detection generalization |
| Multi-Vuln Detection | 2025 | Dataset | arXiv:2512.22306 | Long-context multi-label vulnerability benchmark across languages |
| Multi-Lang SVD | 2025 | Dataset | arXiv:2503.01449 | Multi-language software vulnerability detection benchmark study |
| SECURE CODE GENERATION | ||||
| CodeSecEval | 2024 | Harness | arXiv:2407.02395 | Evaluating LLMs on secure code generation with CWE-based evaluation |
| CodeLMSec | 2024 | Harness | arXiv:2302.04012 | Systematically evaluating security vulnerabilities in black-box code LMs |
| SecurityEval | 2022 | Dataset | arXiv:2210.09263 | GitHub | Mining vulnerability examples to evaluate ML-based code generation |
| SecCodePLT | 2024 | Harness | arXiv:2410.11096 | GitHub | Unified platform for evaluating code GenAI security with 27 CWEs |
| CWEval | 2025 | Harness | arXiv:2501.08200 | GitHub | Outcome-driven evaluation for functionality and security of LLM code |
| SafeGenBench | 2025 | Dataset | arXiv:2506.05692 | 558 security-sensitive test questions covering vulnerability taxonomy (ByteDance) |
| SecRepoBench | 2025 | Dataset | arXiv:2504.21205 | Repository-level secure coding with 318 tasks across 27 repos |
| SecureAgentBench | 2025 | Environment | arXiv:2509.22097 | 105 tasks for evaluating code agents on secure code generation |
| A.S.E | 2025 | Dataset | arXiv:2508.18106 | GitHub | Repository-level benchmark using real CVEs (Tencent) |
| SEC-bench | 2025 | Environment | arXiv:2506.11791 | Automated benchmarking of LLM agents on real-world security tasks |
| CASTLE | 2025 | Dataset | arXiv:2503.09433 | GitHub | Benchmarking dataset for static code analysis with ground-truth annotations |
| MT-Sec | 2025 | Dataset | arXiv:2503.09700 | Benchmarking correctness and security in multi-turn code generation |
| DUALGUAGE | 2025 | Harness | arXiv:2511.20709 | Automated joint security-functionality benchmarking |
| BaxBench | 2025 | Environment | arXiv:2502.11844 | GitHub | 392 backend tasks validating functionality and exploits |
| SecCodeBench | 2025 | Harness | GitHub | Alibaba's 37 test cases / 16 CWEs with dynamic PoC exploits |
| AutoPatchBench | 2025 | Component | GitHub | Automated vulnerability patching (component of CyberSecEval v4) |
| PatchEval | 2025 | Harness | arXiv:2511.11019 | Multilingual benchmark for patching real-world vulnerabilities; 1,000 CVEs |
| PACEbench | 2025 | Framework | arXiv:2510.11688 | Framework for practical AI cyber-exploitation capabilities |
| VulnRepairEval | 2025 | Framework | arXiv:2509.03331 | Exploit-based evaluation for LLM vulnerability repair |
| THREAT INTELLIGENCE & CTI | ||||
| CTIBench | 2024 | Dataset | arXiv:2406.07599 | HuggingFace | Evaluating LLMs on CTI tasks: attack patterns, threat actors, APT campaigns |
| CTI-MCQ | 2024 | Dataset | arXiv:2406.07599 | Multiple-choice questions on attack patterns, APT campaigns, detection |
| CTI-RCM | 2024 | Dataset | arXiv:2406.07599 | Root cause mapping correlating CVE records with CWE entities |
| SecKnowledge-Eval | 2025 | Dataset | arXiv:2510.14113 | Evaluation datasets for complex cybersecurity tasks |
| ExCyTIn-Bench | 2025 | Environment | arXiv:2507.14201 | Microsoft's cyber threat investigation agent benchmark |
| MALWARE & SOC | ||||
| ACSE-Eval | 2025 | Dataset | arXiv:2505.11565 | AWS Cloud Security Engineering Eval for cloud threat modeling |
| LogEval | 2024 | Dataset | arXiv:2407.01896 | Benchmark suite for LLM log analysis tasks (parsing, anomaly detection, diagnosis, summarization) |
| CyberSOCEval | 2025 | Component | GitHub | Malware analysis and threat intel reasoning (component of CyberSecEval v4) |
| Sophos SOC Benchmark | 2024 | Harness | Sophos Blog | Three SOC tasks: incident investigation, summarization, severity evaluation |
| LogLLM | 2024 | Harness | arXiv:2411.08561 | Log-based anomaly detection using large language models |
| LogLM | 2024 | Dataset | arXiv:2410.09352 | Task-based to instruction-based automated log analysis benchmark |
| DefenderBench | 2025 | Harness | arXiv:2506.00739 | GitHub | Microsoft toolkit spanning offense/defense/understanding |
| PHISHING DETECTION | ||||
| PhishAgent Benchmark | 2024 | Harness | arXiv:2408.02291 | Multimodal agent evaluation for phishing webpage detection |
| MLLM Phishing Benchmark | 2025 | Dataset | arXiv:2503.01040 | Comprehensive security benchmark for multimodal LLMs |
| Open-Source LLM Phishing | 2025 | Harness | arXiv:2503.01520 | 21 LLMs evaluated with 4 prompt engineering techniques |
| SME Phishing Detection | 2025 | Dataset | arXiv:2503.08766 | LLM evaluation for small/medium enterprise phishing |
| PhishEmailLLM Dataset | 2025 | Dataset | arXiv:2503.09270 | Meta-model approach for phishing email detection |
| APOLLO | 2024 | Harness | arXiv:2402.16862 | GPT-based tool benchmark for phishing email detection |
| PROMPT INJECTION | ||||
| AgentDojo | 2024 | Environment | arXiv:2406.13352 | GitHub | Dynamic environment for prompt injection attacks & defenses |
| INJECAGENT | 2024 | Dataset | arXiv:2403.02691 | GitHub | Benchmarking indirect prompt injections in tool-using agents |
| BIPIA | 2023 | Dataset | arXiv:2312.14197 | GitHub | First benchmark for indirect prompt injection attacks |
| GenTel-Safe / GenTel-Bench | 2024 | Framework | arXiv:2404.06531 | Unified benchmark and shielding framework for prompt injection |
| NotInject | 2024 | Dataset | arXiv:2410.22770 | GitHub | Over-defense/false-positive benchmark for prompt injection detectors (from InjecGuard) |
| PINT Benchmark | 2024 | Harness | GitHub | Lakera's benchmark for prompt injection detection systems |
| Tensor Trust | 2023 | Dataset | arXiv:2311.01011 | GitHub | Website | 126K+ human-generated prompt injection attacks |
| Open-Prompt-Injection | 2024 | Harness | arXiv:2402.12138 | Standardized framework for prompt injection vulnerability evaluation |
| safe-guard-prompt-injection | 2024 | Dataset | arXiv:2402.13064 | HuggingFace | 10,296 prompt injection examples for guardrail evaluation |
| WASP | 2025 | Environment | arXiv:2504.18575 | GitHub | Web Agent Security against Prompt injection attacks (Meta) |
| WAInjectBench | 2025 | Harness | arXiv:2510.01354 | Benchmarking prompt injection detections for web agents |
| RAS-Eval | 2025 | Harness | arXiv:2506.15253 | Security eval benchmark for LLM agents with tool execution |
| JAILBREAK & RED TEAMING | ||||
| JailbreakBench | 2024 | Harness | arXiv:2404.01318 | GitHub | Website | 200 behaviors for standardized jailbreak evaluation |
| HarmBench | 2024 | Harness | arXiv:2402.04249 | GitHub | Standardized evaluation framework for automated red teaming |
| SafetyBench | 2024 | Harness | GitHub | CAIS benchmark suite for comprehensive safety testing |
| ToxiGen | 2022 | Dataset | arXiv:2203.09509 | GitHub | Microsoft dataset for toxic/harmful content detection |
| StrongREJECT | 2024 | Dataset | arXiv:2402.10260 | GitHub | 313 forbidden questions across 6 categories |
| WildJailbreak | 2024 | Dataset | arXiv:2406.18510 | GitHub | 261,534 conversations for training LLMs to be safe |
| SORRY-Bench | 2024 | Harness | arXiv:2406.14598 | GitHub | Systematically evaluating LLM safety refusal behaviors |
| ALERT | 2024 | Harness | arXiv:2404.08676 | Comprehensive benchmark for LLM safety through red teaming |
| GPTFuzzer | 2023 | Harness | arXiv:2309.10253 | GitHub | Auto-generated jailbreak prompts for red teaming LLMs |
| SG-Bench | 2024 | Harness | arXiv:2410.21965 | Evaluating LLM safety generalization across diverse tasks |
| LatentJailbreak | 2023 | Dataset | arXiv:2307.08487 | Benchmark for evaluating text safety and output robustness |
| AdvBench | 2023 | Dataset | arXiv:2307.15043 | Adversarial behaviors dataset (foundation for many jailbreak benchmarks) |
| S-Eval | 2024 | Harness | arXiv:2405.14191 | Automatic and adaptive test generation for LLM safety |
| SAFE | 2024 | Dataset | arXiv:2404.18539 | Fine-grained safety dataset for LLMs beyond binary classification |
| DoNotAnswer | 2023 | Dataset | arXiv:2308.13387 | GitHub | Evaluating safeguards in LLMs with comprehensive refusal scenarios |
| AILuminate Jailbreak v0.5 | 2025 | Harness | MLCommons | MLCommons jailbreak benchmark (industry standard) |
| SecReEvalBench | 2025 | Dataset | arXiv:2505.07584 | Multi-turn security resilience evaluation benchmark |
| HELM Safety | 2024 | Component | Stanford HELM | Safety evaluation component of Stanford's HELM |
| Agent Security Bench (ASB) | 2024 | Harness | arXiv:2410.02644 | GitHub | Formalizing attacks and defenses in LLM-based agents (ICLR 2025) |
| AgentHarm | 2024 | Dataset | arXiv:2410.09024 | HuggingFace | UK AISI's 110 harmful agent tasks |
| b3 (Backbone Breaker Benchmark) | 2025 | Dataset | arXiv:2510.22620 | Blog | Security evaluation for backbone LLMs used inside AI agents (agent-focused adversarial attacks) |
| META-BENCHMARKS & FRAMEWORKS | ||||
| CAIBench | 2025 | Meta-benchmark | arXiv:2510.24317 | Meta-benchmark integrating Base, Cybench, AutoPenBench, CTIBench |
| CyberPII-Bench | 2025 | Dataset | arXiv:2510.24317 | PII anonymization evaluation in cybersecurity contexts |
| Cyber-Zero | 2025 | Framework | arXiv:2508.00910 | GitHub | Training framework with benchmark suites for EnIGMA+ |
| EnIGMA | 2024 | Environment | arXiv:2409.16165 | GitHub | Enhanced interactive generative model agent for CTF |
| NETWORK & IDS DATASETS | ||||
| NSL-KDD | 2009 | Dataset | UNB | Classic network intrusion detection dataset |
| CIC-IDS 2017 | 2017 | Dataset | UNB | Intrusion detection evaluation dataset |
| CSE-CIC-IDS 2018 | 2018 | Dataset | UNB | IDS/IPS dataset on AWS infrastructure |
| CIC-DDoS 2019 | 2019 | Dataset | UNB | DDoS attack evaluation dataset |
| CIRA-CIC-DoHBrw 2020 | 2020 | Dataset | UNB | DNS over HTTPS dataset |
| CIC-Bell DNS 2021 | 2021 | Dataset | UNB | DNS security dataset |
| CIC IoT Attack Dataset | 2023 | Dataset | UNB | IoT attack patterns dataset |
| CICIoV2024 | 2024 | Dataset | UNB | Internet of Vehicles security dataset |
| CICIoMT2024 | 2024 | Dataset | UNB | Medical IoT security dataset |
| IoT-DIAD | 2024 | Dataset | UNB | IoT intrusion detection and anomaly dataset |
| APT IIoT (CICADA) | 2024 | Dataset | UNB | Industrial IoT APT attack dataset |
| Datasense IIoT | 2025 | Dataset | UNB | Industrial IoT sensor data security dataset |
| BCCC-CIC-IDS2017 | 2017 | Dataset | UNB BCCC | Large-scale intrusion detection dataset |
| BCCC-CSE-CIC-IDS2018 | 2018 | Dataset | UNB BCCC | Extended large-scale IDS dataset |
| BCCC-VulSCs-2023 | 2023 | Dataset | UNB BCCC | Vulnerable smart contracts dataset |
| BCCC-SCsVuls-2024 | 2024 | Dataset | UNB BCCC | Smart contract vulnerabilities dataset |
| BCCC-cPacket-Cloud-DDoS-2024 | 2024 | Dataset | UNB BCCC | Cloud DDoS attacks dataset |
| BCCC-IoT-IDS-Zwave-2025 | 2025 | Dataset | UNB BCCC | Large-scale IoT-Zwave intrusion detection dataset |
| BCCC-DeFiFraudTrans-2025 | 2025 | Dataset | UNB BCCC | DeFi fraud transactions dataset |
| BCCC-Mal-NetMem-2025 | 2025 | Dataset | UNB BCCC | Multisource malware analysis using network traffic and memory |
| UNSW-NB15 | 2015/2024 | Dataset | UNSW | Network intrusion detection dataset (updated 2024) |
| MITRE ATLAS | 2023 | Knowledge Base | MITRE | Attack success rates for AI models (knowledge base) |
| AI SECURITY ADJACENT: ADVERSARIAL ML & ROBUSTNESS | ||||
| CIFAR-10 Adversarial | 2019 | Dataset | IBM ART | IBM ART benchmark for attack success rates |
| ADDC | 2024 | Dataset | ⚠️ Unable to verify - Mahalle et al. | Adversarial Diversity-Driven Dataset |
| DCA | 2024 | Harness | ⚠️ Unable to verify - Mahalle et al. | Aggressive events simulation for benchmark datasets |
| REA | 2024 | Harness | ⚠️ Unable to verify - Mahalle et al. | AI model threat handling evaluation |
| VMA | 2024 | Framework | ⚠️ Unable to verify - Mahalle et al. | AI model vulnerability identification benchmark |
| RobustBench | 2021 | Harness | arXiv:2010.09670 | GitHub | Website | Adversarial robustness leaderboard for image classifiers |
| AdversarialNLI (ANLI) | 2020 | Dataset | arXiv:1910.14599 | GitHub | Meta's adversarial robustness in NLI |
| AI SECURITY ADJACENT: DEEPFAKE & MEDIA | ||||
| Faceswap-GAN | 2018 | Dataset | GitHub | Deepfake detection methods evaluation |
| VidTIMIT | 2012 | Dataset | ConvAI | Video-based deepfake detection benchmark |
| FaceForensics++ | 2019 | Dataset | arXiv:1901.08971 | GitHub | Large-scale deepfake detection benchmark |
| MISCELLANEOUS | ||||
| AI Cyber Risk Benchmark | 2024 | Harness | arXiv:2412.09878 | Evaluating automated exploitation capabilities |
| ITBench | 2025 | Environment | arXiv:2502.03969 | Evaluating AI agents across IT automation tasks |
| SandboxEval | 2025 | Environment | arXiv:2504.00018 | Test suite for LLM assessment environment safety |
| CyberLLMInstruct | 2025 | Dataset | arXiv:2503.09144 | Dataset for analyzing safety of fine-tuned LLMs |
| DebugBench | 2024 | Harness | arXiv:2401.08420 | Evaluating debugging capability of LLMs |
| AttackER | 2024 | Dataset | arXiv:2408.05866 | Named entity recognition dataset for cyber-attack attribution |
| Hackphyr | 2024 | Environment | arXiv:2409.11276 | Local fine-tuned LLM agent for network security |
| CyberPal.AI | 2024 | Dataset | arXiv:2408.09304 | Expert-driven cybersecurity instructions benchmark |
| Truth Seeker Dataset | 2023 | Dataset | UNB | Misinformation detection in cybersecurity context |
| BinMetric | 2025 | Harness | arXiv:2505.07360 | Binary analysis metrics and evaluation benchmark |
| OS-Harm | 2025 | Environment | arXiv:2506.14866 | Safety of computer use agents with GUIs (150 tasks) |
| AgentThreatBench | UK AISI / inspect_evals | 2026 | Benchmark | OWASP Top 10 Agentic |
| Category | Count |
|---|---|
| Knowledge & Q&A | 15 |
| CTF & Offensive | 10 |
| Penetration Testing | 13 |
| Vulnerability Detection | 19 |
| Secure Code Generation | 20 |
| Threat Intelligence & CTI | 5 |
| Malware & SOC | 7 |
| Phishing Detection | 6 |
| Prompt Injection | 12 |
| Jailbreak & Red Teaming | 20 |
| Meta-Benchmarks | 4 |
| Network & IDS Datasets | 22 |
| Miscellaneous | 12 |
| Core Cybersecurity Benchmarks | ~165 |
| AI Security Adjacent: Adversarial ML | 7 |
| AI Security Adjacent: Deepfake & Media | 3 |
| TOTAL (incl. adjacent) | ~175 |
https://github.com/ethiack/ethibench
https://x.com/AISecHub/status/2077481328950292544
https://www.cotool.ai/research/aws-cloud-intrusion - multiple links from this one