AI
Exposed AI Model Servers: Secure Your Endpoints and APIs
Unprotected model endpoints leak training data and proprietary logic through simple inference requests that bypass traditional network firewalls.
ai security
Everything Sandbox Gazette has reported about ai security: 15 stories, newest first. Part of our AI coverage.
AI
How Exposed AI Model Servers Work: A Step-by-Step Breakdown
Attackers exploit open inference endpoints to extract training data or inject malicious prompts, bypassing traditional network perimeters through standard API calls.
AI
Access Controls for AI Agents: A Practical Implementation Checklist
Standard identity systems fail AI agents because they cannot verify intent, requiring policy engines that inspect reasoning traces before granting resource permissions.
AI
Why is Microsoft CEO Nadella calling AI 'super intelligence' and targeting rivals?
Microsoft CEO Satya Nadella adopts the term super intelligence to describe AI models as potential insider threats, signaling a shift in corporate security framing.
AI
Synthetic Media Definition: How Generated Content Works and What to Verify
Synthetic media mimics reality through algorithmic reconstruction, making traditional source verification obsolete and requiring new trust frameworks for digital evidence.
AI
Secure AI Plugins and Agents: Prevention Checklist for Ops
External AI agents bypass standard network controls, creating blind spots where data exfiltration occurs without triggering traditional security alerts.
AI
Prevent Training Data Leakage in Small Business AI Deployments
Small teams face unique data leakage risks because their limited datasets make each record statistically unique and easier for models to memorize.
AI
Stop Sensitive Data Leaks Through AI Chatbots: Technical Controls
Most data leaks occur not through model theft but via unfiltered input prompts that bypass application-layer security checks and expose context windows to external processing.
AI
AI-Assisted Threat Detection: 8 Best Practices for Accuracy
Machine learning amplifies existing data flaws, turning minor noise into catastrophic false positives if you ignore model drift and feedback loops.
AI
Retrieval-Augmented Generation Security: Benefits and Limitations
RAG shifts data risk from model weights to the retrieval layer, creating a new attack surface that traditional model hardening cannot address.
AI
AI in Security Ops: 7 Common Mistakes and Fixes
Most AI security failures stem from treating models as black boxes rather than integrating them into existing control frameworks with strict data boundaries.
AI
AI Risk Management Checklist for Secure Deployment
Model drift and prompt injection bypass traditional perimeter defenses, requiring continuous validation of data lineage and input sanitization at every inference stage.
AI
AI Model Theft Myths: Why Standard Security Fails to Protect Your Weights
Adversaries do not need source code to steal your model. They extract proprietary weights through statistical inference on the output interface alone.
AI
How MITRE ATLAS Prevents AI Model Supply Chain Failures
Map your machine learning lifecycle to known attack patterns to stop data poisoning and model theft before deployment.
AI
How does Canto Incognito turn compromised AI servers into scanners for expansion?
The Canto Incognito campaign uses PoeLLM malware to compromise thousands of AI servers, turning them into scanners for further expansion.