Overview Credential stuffing — the automated use of stolen username/password pairs — has been around for years. But now, attackers are enhancing these campaigns with AI-driven orchestration, making them faster, stealthier, and far more successful. By combining machine learning with… Read More ›
Overview Supply chain attacks target the weakest link in the ecosystem — and AI is making them more precise, scalable, and devastating. Attackers can now leverage AI to map dependencies, identify vulnerable vendors, and generate tailored exploits that ripple through… Read More ›
Overview Cloud misconfigurations remain one of the top causes of breaches. Now, attackers are supercharging their reconnaissance by using AI to identify, classify, and exploit cloud misconfigurations at scale. From open S3 buckets to weak IAM policies, AI-driven tools can… Read More ›
Overview Distributed Denial of Service (DDoS) attacks have long been a weapon of choice for cybercriminals. But with AI, these attacks are no longer just about brute force — they’re becoming smarter, adaptive, and harder to stop. By combining botnets… Read More ›
Overview Insider threats have always been one of the hardest problems in cybersecurity. Now, with AI at their fingertips, malicious or careless insiders can conduct reconnaissance on their own organizations with unprecedented speed and sophistication. By combining privileged access with… Read More ›
Overview Cybercrime has evolved from individuals writing malware to entire marketplaces offering Malware-as-a-Service (MaaS). Now, a new player has entered the underground economy: Adversarial LLM-as-a-Service (LLMaaS). These platforms allow attackers to rent hostile AI models — pre-tuned for phishing, malware… Read More ›
Overview Social engineering has always been one of the most effective forms of cyberattack.Now, with AI, it’s getting smarter, faster, and harder to detect. Attackers can use large language models, deepfake generators, and automated reconnaissance to craft highly convincing, personalized… Read More ›
Overview Enterprises are racing to adopt AI, but few realize they may already be running shadow models — unauthorized AI instances spun up outside IT and security oversight. Just like “shadow IT” with unsanctioned apps and cloud services, shadow models… Read More ›
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 ›
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