Probably Secure: A Look At The Security Concerns Of Deterministic Vs Probabilistic Systems
Learn why deterministic security remains essential in an AI-driven world and how GitGuardian combines probability and proof for safe, auditable development.
Agent-Based AI and the Machine Identity Revolution Are Reshaping Security
Is agentic AI the productivity revolution we've been waiting for, or a security nightmare in the making? With AI agents now outnumbering humans and secrets proliferating across enterprise systems, the answer isn't simple. Read our insights from SecDays {France} 2025.
Operationalizing the OWASP AI Testing Guide with GitGuardian: Building Secure AI Foundations Through NHI Governance
Align your AI pipelines with OWASP AI Testing principles using GitGuardian’s identity-based insights to monitor, enforce, and audit secrets and token usage.
Automated Guard Rails for Vibe Coding
Vibe coding might sound like a trendy term, but it's really just developing software without automated checks and quality gates. Traditional engineering disciplines have always relied on safety measures and quality controls, so vibe coding should be no different in my honest opinion.
Building a Secure LLM Gateway (and an MCP Server) with GitGuardian & AWS Lambda
How I wrapped large-language-model power in a safety blanket of secrets-detection, chunking, and serverless scale.
A Look Into the Secrets of MCP: The New Secret Leak Source
MCP rapidly enhances AI capabilities but introduces security challenges through its distributed architecture. Especially, the distributed nature of MCP requires a lot of NHIs and their secrets. Our research shows that MCP is a new source of leaks that already discloses real-world secrets.
Secrets Sprawl and AI: Why Your Non-Human Identities Need Attention Before You Deploy That LLM
Your RAG implementation can expose secrets in some unexpected ways. Secure your LLM deployments and scrub knowledge bases to prevent your secrets from leaking.
GitHub Copilot Security and Privacy Concerns: Understanding the Risks and Best Practices
Worried about GitHub Copilot’s security and privacy concerns? Learn about potential risks and best practices to protect yourself and your organization while leveraging AI.
Yes, GitHub's Copilot can Leak (Real) Secrets
Researchers successfully extracted valid hard-coded secrets from Copilot and CodeWhisperer, shedding light on a novel security risk associated with the proliferation of secrets.
MLOps Done Right: GitGuardian's Battle-Tested Open-Source Stack
Our stack to go from experimenting to production won't have any more secrets for you.
The Quest to Minimize False Positives Reaches Another Significant Milestone
Our breakthrough ML model FP Remover V2 slashes false positives by 80%, setting a new industry standard for secrets detection. Discover how we're helping security teams focus on real threats instead of chasing phantom alerts.
Balancing AI Performance and Safety: Lessons from PyData Berlin
Would you trust AI to call 911? GitGuardian's ML engineer Nicolas posed this question at PyData Berlin, sparking a discussion on integrating ML into critical systems, debunking AI myths, and balancing innovation with safety in AI deployment.
