SiliconANGLE: Cutting both ways: AI sharpens systems protection while opening new exploits for malicious actors
The cybersecurity industry is discovering that powerful frontier AI models are a double-edged sword. Companies can use models to identify vulnerabilities in source code and system configurations faster than ever before. As it turns out, malicious actors can do this as well. A prime example of how AI models have shifted cybersecurity into a new […] The post Cutting both ways: AI sharpens systems protection while opening new exploits for malicious actors appeared first on SiliconANGLE.
AI models are now being used both by cybersecurity researchers to find vulnerabilities in software and by malicious actors to exploit those same weaknesses. Recent incidents with a widely-used programming language demonstrated that attackers can discover and weaponize vulnerabilities faster than organizations can patch them. Organizations are responding by emphasizing data protection, recovery capabilities, and resilience as foundational layers of enterprise security, since AI systems depend entirely on the integrity of the data supporting them. Additionally, enterprises face an emerging threat from quantum computing, which could break current encryption methods, yet most organizations have not yet deployed quantum-safe cryptography.
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An AI model said it wouldn’t use any tools, then tried to send something to a server in Beijing anyway, and while researchers say it’s probably a training quirk and not espionage, the whole thing has people asking how much to trust free Chinese AI.

OpenAI is now training its most advanced AI models without internet access following a string of rogue hacking incidents. In a blog post on Friday, OpenAI says it built an offline testing environment where AI models can interact with indexed and cached web content "without risk of affecting external systems." OpenAI paused training its frontier AI models in September, after disclosing several incidents in which its AI agents broke out of their testing environments to hack third
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External auditors from METR and Redwood Research spent three weeks on-site at OpenAI examining the company's internal monitoring system for AI agents and found significant gaps, with up to 25 percent of agent traffic from models at the GPT-5.5 class and above going unmonitored. OpenAI redacted large portions of the 61-page report, and only a summary is publicly available. The article Three-week on-site audit at OpenAI reveals major gaps in AI safety monitoring appeared first on The Deco