| What it does | Browser fingerprint and automation detector that cross-checks JavaScript consistency against network layer signals
| AI security for chatbots, RAG systems, and agentic workflows
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| Stage | Not given
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| Founded | Not given
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| Based in | Not given
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| Pricing model | Free
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| Pricing | Not given
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| Key features | - JavaScript fingerprinting across canvas, WebGL, WebGPU, audio, fonts, navigator and screen
- Network layer analysis via Cloudflare request metadata
- Behavioral challenge to verify human interaction
- Open-source package for CI integration
- Passive automation detection via navigator properties and framework residue
- Cross-layer consistency checking between JavaScript and network signals
| - Intent envelope specification with open JSON Schema
- Multi-turn jailbreak and injection testing across web, mobile, and voice
- Deterministic execution boundary enforcing tool allowlists
- Human-in-the-loop escalation for high-impact actions
- Identity and credential separation per agent
- Supervisor check for independent action validation
- Free AI attack surface assessment tool
- Findings mapped to OWASP, MITRE ATLAS, and NIST AI RMF
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| What makes it different | - Three independent detection axes that fail separately rather than as one system
- Combines JavaScript analysis with network-layer observations that JavaScript cannot fake
- Educational and defensive tool, not a service for evading detection
- Live read-only measurement with no data storage
| - Open-source intent envelope specification implementable with own engineers
- Calibrated defenses from red team findings rather than off-the-shelf policies
- Findings carried through to runtime controls and access changes, not just reports
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 6 ● no change since last check | 1 ▲ +1 (up) since last check |
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| Trust Flow (Majestic) | 2 | 0 |
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| Citation Flow (Majestic) | 27 | 12 |
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| Referring domains (Majestic) | 42 | 1 |
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liarjs.dev
SecuredAI