AI-driven threats are accelerating as attackers exploit hallucinated domains, remote code execution flaws, and agent manipulation to bypass defenses. Today’s coverage highlights urgent patching needs, risks with AI automation, and the policy whiplash impacting global model deployment.
Overview Synthetic data — artificially generated datasets used to train AI models — is becoming a popular way to avoid privacy issues and expand training material.But attackers are now targeting synthetic data generation pipelines to inject malicious patterns, bias, or… Read More ›
Overview In traditional cybersecurity, stealing source code is bad.In AI security, stealing model weights is catastrophic.The weights are the learned parameters that make your AI valuable — the result of millions in compute, proprietary data, and R&D.If an attacker exfiltrates… Read More ›
Overview The evolution of AI has shifted from simple chat interfaces to autonomous agents — LLM-powered systems capable of planning, acting, and adapting without direct human input. While powerful for productivity, these agents also introduce a new class of security… Read More ›
Overview Open-source LLMs offer transparency and innovation — but they also create new risks when adversaries fine-tune these models for malicious purposes.This isn’t about prompt engineering or jailbreaking. It’s about retraining models to embed bias, backdoors, or harmful capabilities directly… Read More ›
Overview As LLMs become more capable and widely deployed, attackers are turning their attention to jailbreaking them — crafting prompts that bypass built-in safety restrictions. But what was once a fringe curiosity is now a full-fledged underground market: LLM jailbreaks… Read More ›
Overview Shadow IT has long been a concern in cybersecurity — now it has a new form:Shadow AI models. Across enterprises, well-meaning employees are training or deploying large language models (LLMs) on internal data without authorization, oversight, or security review…. Read More ›
Overview In the race to deploy powerful AI systems, many organizations have overlooked a growing threat:Model theft — the unauthorized access, copying, or extraction of proprietary large language models (LLMs). These models represent millions of dollars in training costs, intellectual… Read More ›
Overview Large Language Models (LLMs) were never designed to write malware — but with the right prompting, many of them can. Despite built-in safety filters and ethical guardrails, attackers are finding ways to bypass restrictions and use AI to generate… Read More ›
Overview APIs are the backbone of modern SaaS. They expose data, business logic, and workflows to users, apps, and integrations. But now, attackers are using AI to reverse engineer API behavior, endpoints, and internal functionality — often without access to… Read More ›