AI Security
Hypothesis Quality: Griffin AI vs Mythos
Two AI bug hunters can both generate hypotheses. Only one can defend them. A field study of grounded versus ungrounded hypothesis generation in zero-day discovery.
Jan 12, 20266 min read
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Vulnerability Scanning for AI Models: A New Frontier
AI models ship with dependencies, use vulnerable libraries, and introduce novel attack surfaces. Traditional scanning is not enough.
Jan 12, 20266 min read
AI Security
Securing Claude Code MCP Server Deployments
Claude Code MCP servers run with the privileges of the developer who invoked them. That makes deployment posture the entire security model.
Jan 12, 20267 min read
AI Security
Air-Gapped Environments: Griffin AI vs Mythos
Air-gapped AI is not a feature flag. It is an architectural commitment, and it separates serious enterprise products from consumer-grade assistants.
Jan 11, 20267 min read
AI Security
Per-Scan Token Cost: Griffin AI vs Mythos
Tiered models and a deterministic engine cut token consumption to the moments that need reasoning. Pure-LLM tools pay full price for every trivial check.
Jan 11, 20266 min read
AI Security
Griffin AI vs xAI Grok for Security
Jan 11, 20267 min read
AI Security
Enterprise AI Security Rollout: The Governance Gap
Most enterprises rolled out AI-for-security tools faster than their governance processes could keep up. The resulting gap is where most of the pain from 2025 deployments lives.
Jan 10, 20267 min read
AI Security
Griffin AI vs Llama 3 for Security Workflows
Llama 3 is a powerful open-weight foundation model, but security workflows demand more than raw inference. Here is how Griffin AI compares.
Jan 10, 20267 min read
AI Security
Remediation PR Quality: Griffin AI vs Mythos
Griffin AI produces draft PRs with taint paths, exploit hypotheses, and disproof attempts. Mythos-class pure-LLM tools skip those anchors, and PR quality suffers.
Jan 10, 20267 min read
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