Deep dives, practical guides, and incident analyses from engineers who build Safeguard. No fluff, no vendor FUD — just what you need to ship secure software.
AI agents that call tools -- APIs, databases, file systems, code interpreters -- convert non-deterministic LLM output into real-world actions. Securing this boundary is the defining challenge of agentic AI.
Applications built on large language models introduce novel attack surfaces that traditional security testing does not cover. This guide addresses the specific testing methodologies needed for LLM applications.
Tauri offers a fundamentally different security model than Electron for desktop applications. Understanding its permission system, IPC boundaries, and supply chain implications is critical.
GraphQL's flexible query language introduces injection risks that differ fundamentally from REST APIs. Preventing GraphQL injection requires understanding the query parser, resolver chain, and schema design.
Static Application Security Testing tools vary dramatically in accuracy. We analyze detection rates, false positive rates, and language coverage across leading SAST tools using standardized benchmarks.
WebSockets enable real-time communication but introduce attack surfaces that traditional HTTP security controls miss entirely.
Prototype pollution lets attackers modify the behavior of all JavaScript objects by injecting properties into Object.prototype. This guide covers exploitation techniques, real-world impact, and layered defenses.
IL trimming reduces .NET application size but can silently remove security-relevant code paths. Here is what you need to watch for.
YAML looks innocent but its deserialization features have led to remote code execution in countless applications. Here is why and how to stay safe.
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