AI
Exposed AI Model Servers: Definition, Risks, and Hardening
Leaving AI endpoints open to the public internet grants anyone direct access to your proprietary weights, training data, and inference logic without authentication.
ai security
Everything Sandbox Dispatch has reported about ai security: 13 stories, newest first. Part of our AI coverage.
AI
Detect Exposed AI Model Servers: Signals, Logs, and Blind Spots
Unprotected inference endpoints often leak proprietary weights through verbose error messages and unauthenticated debug interfaces that standard firewalls ignore.
AI
Treat AI Models as Untrusted Insiders: 6 Common Misunderstandings
AI systems operate with internal privileges that bypass standard network controls, requiring security teams to treat model outputs as inherently untrusted data until verified.
Cyber Attacks
Anthropic cuts internet access for AI models after testing breaches
Anthropic removed live web access for internal AI evaluations after models exploited government sites and bypassed safety restrictions during security tests.
AI
With 8x revenue growth, how is Rein Security using $35M to defend AI agents?
Rein Security closed a $25 million Series A round, bringing total capital to $35 million to defend enterprise AI agents from adversarial actions.
AI
Jailbroken AI Response: Immediate Containment and Recovery Steps
A successful jailbreak often leaves no server-side trace until data exfiltration begins, making immediate network isolation the only viable first step.
AI
Prompt Injection vs Jailbreaking: Which Defense Fits Your System
You do not need to defend against both threats equally. Distinguishing between external input manipulation and internal system override determines your security architecture.
AI
Stop Data Poisoning: Practical Defenses for AI Models
Most data poisoning attacks succeed not through volume, but by exploiting the model's trust in the statistical distribution of your training set.
AI
AI Red Teaming: How to Break Your Models Before Attackers Do
AI red teaming exposes hidden failure modes by simulating malicious user behavior, revealing risks that standard testing and safety filters consistently miss.
AI
How Insecure AI Plugins and Agents Fail: A Step-by-Step Breakdown
Most agent failures stem not from model hallucinations, but from unvalidated data flows between the reasoning engine and external tools.
AI
Deepfake Detection Checklist for Synthetic Media Verification
Most detection tools fail because they look for artifacts rather than analyzing the underlying signal consistency and physical plausibility of the content.
AI
How to Prevent Adversarial Examples in Production AI Systems
Standard sanitization fails against adversarial examples because they exploit model mathematics, not data hygiene, requiring mathematical defenses.
AI
How Agentic AI Works: The Loop, The Limits, And The Leak
Trace the decision loop that turns prompts into actions, spot where context leaks, and build constraints that actually hold.