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This incident demonstrates how removing safety guardrails from open-source models like DeepSeek enables autonomous agents to systematically exploit routine misconfigurations at machine speed. The case highlights a critical shift where standard security gaps, once manageable, can now be weaponized by AI-driven automation for large-scale credential harvesting and extortion. For the industry, it underscores the urgent need for robust alignment protocols and continuous monitoring of deployed AI agents to prevent them from becoming uncontrolled attack vectors.
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BlackHatSect0r Uses DeepSeek-Powered AI Agent to Automate Attacks and Harvest 16,834 Credentials

Cybersecurity News4 min read

BlackHatSect0r && DXQRTXX has been linked to an automated cybercrime operation that used an AI agent connected to a DeepSeek model to scan for exposed secrets, test stolen access, and feed results into a custom control platform. The activity shows how common security gaps can be abused at machine speed.An exposed operation server contained 4.9 […] The post BlackHatSect0r Uses DeepSeek-Powered AI Agent to Automate Attacks and Harvest 16,834 Credentials appeared first on Cyber Security News.

BlackHatSect0r && DXQRTXX has been linked to an automated cybercrime operation that used an AI agent connected to a DeepSeek model to scan for exposed secrets, test stolen access, and feed results into a custom control platform. The activity shows how common security gaps can be abused at machine speed.An exposed operation server contained 4.9 GB of material across 9,299 files, including the DXSCAN platform, phishing tools, extortion material and a…

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