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Tools, model specs and courses for LLM engineers-VRAM calculator, benchmarks and model directory-with free and paid tiers.
Security platform that guards GenAI apps and AI agents against prompt injection, data leaks and misuse for enterprise teams.
Developer-first security platform unifying code, cloud, runtime and AI pentesting with noise reduction and autofix.
AI/ML bug-bounty platform where researchers bypass LLM guardrails in timed challenges to win cash prizes.
Compliance automation platform that continuously monitors controls and evidence to help companies achieve SOC 2, ISO 27001, and HIPAA.
No public pricing
Free trial available
Free trial available
No public pricing
No public pricing
- ✦VRAM/GPU-memory calculator for LLMs
- ✦LLM performance rankings and benchmarks
- ✦Model directory and comparison
- ✦AI/ML courses and learning roadmap
- ✦Calculator API and exportable cost reports
- ✦Engineering blog and guides
- ✦Runtime protection for AI agents and apps
- ✦Prompt-injection and jailbreak prevention
- ✦Data-leakage detection in prompts
- ✦Shadow-AI discovery across apps and browsers
- ✦Policy controls by user, app and action
- ✦AI red-teaming and adversarial testing
- ✦SAST, SCA and secrets scanning
- ✦Cloud misconfiguration (CSPM) and container scanning
- ✦AI-powered autonomous pentesting
- ✦AutoFix pull requests and auto-triage
- ✦Runtime and bot protection (Zen)
- ✦SOC 2 and ISO compliance support
- ✦Timed AI-hacking challenges with cash pots
- ✦Public leaderboard and rankings
- ✦Guardrail-bypass and jailbreak objectives
- ✦Hacktivity feed of activity
- ✦Community via Discord
- ✦Blog on LLM exploits and AI security
- ✦Continuous automated compliance monitoring across frameworks
- ✦Automated evidence collection and audit preparation
- ✦Personnel access and permissions management
- ✦Vendor and third-party risk assessment workflows
- ✦Automated security questionnaire responses
- ✦Public-facing trust center for compliance status
- ✦400+ tool integrations and an API for custom workflows
- →Estimating GPU memory before training or inference
- →Comparing and selecting LLMs
- →Learning ML and LLM engineering
- →Modeling production deployment costs
- →Securing conversational and RAG agents
- →Governing employee use of AI tools
- →Adversarial testing before deploying GenAI
- →Meeting AI compliance requirements
- →Finding and fixing code vulnerabilities
- →Securing cloud and containers
- →Running continuous pentests
- →Automating compliance evidence
- →Red-teaming and jailbreaking LLMs
- →Earning bounties for AI exploits
- →Learning AI attack techniques
- →Competing against other researchers
- →Preparing for and maintaining SOC 2 or ISO 27001 certification
- →Automating responses to customer security questionnaires
- →Managing vendor security reviews at scale
- →Centralizing risk management across a growing company