ai-security
Safeguard articles tagged "ai-security" — guides, analysis, and best practices for software supply chain and application security.
593 articles
Griffin AI vs DeepSeek Coder for Security Review
DeepSeek Coder has become a favourite for code-focused workloads. This is how it compares to Griffin AI when the job is security review, not code generation.
Exploit Path Synthesis: Griffin AI vs Mythos
Finding a bug is not the same as proving it is exploitable. How Griffin AI synthesises concrete exploit paths and why pure-LLM scanners rarely get past the sketch stage.
RAG Pipeline Supply Chain Attacks: Vector DBs and More
RAG pipelines have six or seven supply chain surfaces, and most teams are only watching one. Here is how the attacks actually look in production.
SEvenLLM Design And Coverage
SEvenLLM set out to measure how well LLMs handle Security Event analysis, the unglamorous day-to-day work of SOCs and IR teams. A design review of what the benchmark covers, how it was built, and where the coverage maps or does not map to real operations.
Griffin AI vs Claude Haiku for Bulk Scanning
Claude Haiku is the cost-efficient model Griffin uses for high-volume scan interpretation. Here's how raw Haiku compares to Haiku inside Griffin's bulk pipeline.
LLM Prompt Injection: The New Supply Chain Attack Vector
Prompt injection attacks against large language models represent a dangerous new frontier in software supply chain security. Here's what defenders need to know.
Griffin AI vs OpenAI o1 for Security Reasoning
Deep reasoning models are transformative for hard logical problems. Security reasoning is only partially a logic problem—the rest is grounding, policy, and workflow.
Small-Model Distillation For Security Workflows
Distillation compresses the capability of a large model into a small one for a narrow task. For high-volume security workflows, it is often the difference between a working pipeline and an unaffordable one.
Training Data Opacity As A Trust Limit
You cannot audit what you cannot see. Frontier model training corpora are effectively opaque to their users, and that opacity is not incidental. It shapes what kinds of trust you can extend to the outputs.
Griffin AI vs Gemini Long Context for Codebases
Gemini's million-token context window is a genuinely new capability. For security analysis of large codebases, is it enough on its own?
Agent Security: Enterprise Adoption Patterns
Enterprise agent deployments have moved past pilot phase. The security patterns that have survived contact with production look different from the ones the industry was selling a year ago.
Claude Code Coding Agent: Security Posture Review
A working review of Claude Code's security posture, sandboxing model, and the practical controls enterprises need to deploy it safely at scale.
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