AI Security
What is Training Data Poisoning
Training data poisoning corrupts an ML model's training data to plant hidden backdoors. Learn how it works, real incidents, and how to detect it.
Mar 2, 20266 min read
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Supply Chain Security, in plain English.
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.
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Slopsquatting (AI package hallucination attack)
Slopsquatting exploits AI coding assistants that hallucinate nonexistent package names, which attackers then register as real, malicious packages.
Mar 2, 20266 min read
AI Security
What is a Model Inversion Attack
Model inversion attacks reconstruct sensitive training data from a model's outputs. Learn how they work, real cases, and how to defend your ML APIs.
Mar 2, 20267 min read
AI Security
What is Adversarial Machine Learning
Adversarial machine learning exploits model decision boundaries via evasion, poisoning, extraction, and inference attacks -- here's how it works and how to defend against it.
Mar 2, 20266 min read
AI Security
What is Insecure Output Handling in LLMs
Insecure output handling lets LLM-generated text execute code, alter queries, or render unsanitized HTML — a real, exploitable OWASP LLM05:2025 risk.
Mar 2, 20267 min read
AI Security
MCP Server Inventory: Griffin AI vs Mythos
MCP servers are privileged dependencies. An inventory that tracks them like SBOM tracks packages is the minimum bar — and not every tool meets it.
Mar 1, 20265 min read
AI Security
Zero-Day Discovery ROI: CISO Board Deck
How to talk to your board about zero-day discovery without overpromising. The metrics, the framing, and the slides that hold up under follow-up questions.
Mar 1, 20267 min read
AI Security
What is Sensitive Information Disclosure in LLMs
LLM sensitive information disclosure leaks training data, prompts, and secrets through model outputs. Real incidents, causes, and defenses explained.
Mar 1, 20266 min read
AI Security
What is AI Governance
AI governance means the policies and technical controls that keep AI models, data, and agents safe, compliant, and auditable across your software supply chain.
Mar 1, 20267 min read
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