Author Archives
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Weaponizing AI for Vulnerability Research — When Attackers Use LLMs to Find and Exploit Bugs
Overview Security researchers use AI to enhance vulnerability discovery — but so do attackers. The same tools that help defenders audit code and infrastructure are being repurposed by threat actors to discover exploitable bugs at scale. Welcome to the rise… Read More ›
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LLM-Powered Phishing — How AI Writes Convincing Lures at Scale
Overview Phishing has evolved from misspelled scams to socially engineered masterpieces, thanks to large language models (LLMs). Modern threat actors now use AI to generate hyper-personalized, convincing phishing messages in seconds — at a scale and quality previously impossible. With… Read More ›
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Hijacking AI Agents — From Helpful Assistant to Autonomous Threat
Overview AI agents are no longer static models — they are autonomous systems that plan, reason, and act across digital environments. Whether managing emails, deploying code, or navigating internal tools, these agents are often given privileged access and decision-making capabilities…. Read More ›
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Exfiltration via AI Channels — Hiding Data in AI Prompts and Outputs
Overview Modern security teams monitor emails, file uploads, and network traffic for signs of exfiltration — but AI models open up a new covert channel. By embedding data inside prompts or manipulating model outputs, attackers can sneak information out of… Read More ›
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AI in Malware — LLMs Embedded in Payloads and Toolchains
Overview AI was once a tool for defenders — helping classify malware, detect anomalies, and improve SOC workflows. But now, attackers are embedding language models directly into malware, enabling dynamic payloads, evasive scripting, and autonomous decision-making during intrusions. This new… Read More ›
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Autonomous Reconnaissance — How AI Agents Scout for Vulnerabilities Without Human Help
Overview Reconnaissance is the first phase of nearly every cyberattack — gathering information about systems, users, and infrastructure. Traditionally, this required a human attacker. But now, AI agents can automate and accelerate reconnaissance at scale, with alarming precision. Autonomous reconnaissance… Read More ›
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Synthetic Identity Fraud Powered by AI — Faking People with Language and Pixels
Overview Identity fraud is nothing new — but AI has made it terrifyingly scalable. From fake resumes to deepfake selfies, synthetic identities are now being crafted by generative models that produce convincing, fully fabricated humans: names, photos, voice, and background… Read More ›
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Model Denial of Service (MoDoS) — Overloading AI with Adversarial Input
Overview Denial-of-service attacks are a classic threat to servers and web infrastructure — but as AI models are deployed across APIs, apps, and agents, they too have become targets of disruption. Model Denial of Service (MoDoS) refers to attacks that… Read More ›
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Prompt Injection Supply Chains — Exploiting AI Plugins, Extensions, and Integrations
Overview Prompt injection attacks are no longer limited to chat windows. As AI becomes embedded into **complex systems — through plugins, APIs, extensions, and automation layers — prompt injection becomes a *supply chain threat*. Attackers can now manipulate AI behavior… Read More ›
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Model Theft — How Attackers Clone Your AI via Query APIs
Overview Deploying an AI model through a public or private API can deliver massive value — enabling chatbots, recommendation engines, fraud detection, and countless other services. But exposing your model through an API also creates a tempting attack surface. Model… Read More ›