Researchers from Google Threat Intelligence Group (GTIG) have revealed that a recently identified zero-day exploit aimed at a widely used open-source web administration platform was likely created with the help of artificial intelligence.
The vulnerability, which targeted the platform’s two-factor authentication (2FA) mechanism, could have allowed attackers to bypass critical security protections. While the software involved has not been publicly identified, researchers confirmed that the attack was stopped before it reached large-scale exploitation.
According to GTIG, analysis of the Python-based exploit strongly indicates the involvement of AI tools during the vulnerability discovery and weaponization process. The team noted that the coding style, educational explanations within the script, and even fabricated technical details closely resembled outputs commonly produced by large language models (LLMs).
“For example, the script contains an abundance of educational docstrings, including a hallucinated CVSS score, and uses a structured, textbook Pythonic format highly characteristic of LLMs training data,” GTIG says in a report today.
Researchers also stated that the flaw itself appeared to be a semantic logic issue — an area where AI systems tend to perform effectively — rather than traditional vulnerabilities like memory corruption or poor input sanitization that are usually identified through fuzzing or static analysis techniques.
Google informed the affected software developer about the issue, allowing security measures to be implemented quickly and the attack to be disrupted before wider abuse occurred.
“For the first time, GTIG has identified a threat actor using a zero-day exploit that we believe was developed with AI,” GTIG researchers say.
The report additionally highlights the increasing role of AI in cybercrime operations. Google observed threat groups linked to China and North Korea — including APT27, APT45, UNC2814, UNC5673, and UNC6201 — using AI systems for exploit development and vulnerability research.
Meanwhile, Russia-associated threat actors were reportedly using AI-generated decoy code to conceal malware strains such as CANFAIL and LONGSTREAM. Google also referenced a Russian campaign known as “Overload,” where AI voice cloning technology was allegedly used to imitate journalists in fabricated videos spreading anti-Ukraine narratives.
The report further examined the Android malware PromptSpy, previously documented by ESET, for its integration with Gemini APIs to automate interactions on infected devices.
Investigators identified an autonomous component called “GeminiAutomationAgent,” which reportedly relies on a hardcoded prompt to help the malware evade AI safety mechanisms. Researchers explained that the prompt assigns the malware a harmless persona, enabling it to calculate interface geometry and interact with device functions more effectively.
Google researchers also warned that the malware appears capable of replaying authentication methods, including PINs and lock patterns, using AI-assisted techniques.
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