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AI Security

Tool-Call Audit: The Missing AI Observability Layer

Most AI observability stacks log prompts and completions. The actual security signal is in the tool calls. Here is how to capture it.

Mar 30, 20267 min read
AI Security

AI Coding Assistant Data Leak Incidents Trend

AI coding assistants are now standard developer tooling. The incident data from 2025 and early 2026 shows a recurring pattern of source code, credential, and customer data leaking through them.

Mar 30, 20267 min read
AI Security

Transitive Dependency Fix Cascades, Managed

Fixing a transitive dependency is rarely a single bump. It is a cascade. Here is how to manage those cascades without flooding reviewers or breaking builds.

Mar 29, 20267 min read
AI Security

MCP Protocol Security: What the Model Context Protocol Means for Supply Chains

Anthropic's Model Context Protocol standardizes how AI models interact with external tools. The security implications for software supply chains are significant.

Mar 28, 20266 min read
AI Security

MCP Server Lifecycle Management Patterns

Patterns for managing MCP servers through development, staging, rollout, and deprecation — with an eye on the security gaps that appear at each transition.

Mar 28, 20268 min read
AI Security

Scaling Across Repos: Griffin AI vs Mythos

Multi-repo security reasoning is a graph problem, not a retrieval problem. How Griffin AI's engine scales where pure-LLM products flatten into guesswork.

Mar 28, 20266 min read
AI Security

Fine-Tune Backdoor Insertion: Academic Research

A senior engineer's review of academic research on fine-tune backdoor insertion, from BadNets to sleeper agents, and how the findings translate to production ML.

Mar 28, 20267 min read
AI Security

AI Cybersecurity Companies and Vendors: The Landscape

AI cybersecurity companies split into three distinct groups doing very different work, and confusing them is the fastest way to buy the wrong tool.

Mar 27, 20265 min read
AI Security

Engine-Plus-LLM vs Pure-LLM Bug Hunters

The difference between an engine-plus-LLM bug hunter and a pure-LLM one is not a tuning detail. It is a structural divide that determines whether the findings are usable.

Mar 26, 20267 min read
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