| What it does | Fraud detection and prevention for web apps that detects account abuse and bots under any masking
| Make your software secure itself with autonomous security workers
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| Stage | Startup
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| Founded | 2025
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| Based in | US
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| Pricing model | Freemium
| Freemium
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| Pricing | Free tier with 5,000 identifications. Paid plans: Starter $99/month for 25,000 identifications (monthly billing) or $79/month billed yearly; Growth $399/month for 150,000 identifications (monthly) or $319/month billed yearly; Scale $999/month for 500,000 identifications (monthly) or $799/month bille
| Open source: free with unlimited usage. Private repositories: Free ($0), Starter ($499/month, 500 credits/month), Growth ($1,499/month, 2,000 credits/month), Scale (starts at $3,999/month, 6,000 credits/month). Annual plans include 20% more credits. Credits cost varies by security worker: PR Securit
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| Key features | - Device fingerprinting to recognize devices and detect headless browsers and tampering
- Multi-accounting detection starting at three accounts per visitor
- Risk scoring from 0 to 100 with signal breakdown
- Bot and AI traffic detection with browser automation signals
- IP geolocation and real IP address revelation behind masking
- Traffic quality scoring by source, channel, referrer, and UTM campaign
- Dashboard, API, and webhooks for results delivery
- Five-minute integration with JavaScript snippet or supported SDKs
| - PR Security to stop risky code and untrusted contributors before they merge
- Secure Dependency Updates to turn vulnerable dependencies into tested, merge-ready pull requests
- Red Team to find exploit paths attackers would use before they do
- Agent Guardrails to let agents run without leaking secrets or breaking policy
- Security-One 27B decision model for always-on security triage
- Integration with existing tools and workflows without replacement
- Self-learning loop that improves security over time
- Protects applications, repositories, agents, and infrastructure
- API and MCP access across all plans
- Agent-to-agent remediation
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| What makes it different | - 99.9% identification accuracy and 99.9% risk signal detection accuracy across 300+ signals
- Ready-made High-Risk Event detection requires no custom fraud model training
- Explainable risk scores showing which signals fired and their weights
- Self-serve five-minute onboarding with no procurement or sales cycle required
| - Free for open source with unlimited usage across 3,000+ GitHub projects
- Security workers that each own one security job end to end
- Integrates seamlessly with existing tools without replacement needed
- Self-learning system that improves with each run
- Built by founders with 15+ years together and experience at Google, Klarna, and Trustly
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 39 ▼ −1 (down) since last check | 64 ● no change since last check |
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| Trust Flow (Majestic) | 15 | 9 |
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| Citation Flow (Majestic) | 37 | 40 |
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| Referring domains (Majestic) | 240 | 609 |
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ShieldLabs