A Russian-speaking threat actor known as “Trim” has reportedly transformed Anthropic’s Claude Opus into the central component of an automated, AI-powered penetration testing platform.
This development highlights the rapid repurposing of advanced AI models for offensive security operations. According to research by Cato CTRL, Trim progressed from sharing jailbreak instructions on a Russian cybercrime forum in March 2023 to marketing a completed web vulnerability scanning product called “AI Pentest Checker” by June 2023.
Claude Opus Into Automated AI Penetration Testing Platform
Trim first appeared on the forum on March 13, 2023, offering a detailed guide that claimed to explain methods for bypassing the safety controls of Claude Opus. The actor laid out several purported prompt-manipulation techniques aimed at framing harmful requests as legitimate auditing or code-analysis tasks.
The research indicates that these techniques were shared as part of a reputation-building exercise rather than a direct commercial offer. This strategy allowed Trim to establish credibility among forum users and gather feedback on methods for circumventing model restrictions.
Trim’s later product exemplifies how AI models can be integrated with existing offensive security tools. AI Pentest Checker allegedly combines an AI decision-making layer with popular reconnaissance and web-scanning utilities, such as Nuclei, ffuf, katana, subfinder, and gitleaks.
This integration enables operators to automate various phases of the penetration-testing workflow, including asset discovery, endpoint enumeration, vulnerability prioritization, credential exposure checks, and report generation.
Cato Networks noted that Claude Opus was used in the platform’s critical vulnerability escalation pipeline, while GLM-5 was reportedly employed to prepare exploitation reports.
Trim also claimed to use a modified system prompt derived from an alleged leaked “Fable 5” configuration. System prompts shape a model’s behavior before a user submits a query, often defining safety policies, task boundaries, and response limitations.
If attackers can obtain or infer such instructions, they may be better positioned to create prompts that target gaps, conditional logic, or edge cases in a model’s guardrails.
According to Trim’s forum post, the reported platform can assess a target domain and generate a polished PDF report in under ten minutes. While automated scanners are not new, the incorporation of advanced language models could lower the expertise needed to interpret scan results, link multiple findings, prioritize attack paths, and create actionable reports.
This capability may reduce the operational barrier for less-skilled cybercriminals while enabling experienced operators to scale their targeting efforts.
This case also underscores the risk posed by grey-market access to commercial AI services. Cato’s researchers noted that Trim did not need to breach AI-provider infrastructure or steal model weights.
Instead, the actor allegedly relied on publicly available models, third-party API access, and local uncensored alternatives. Such access can significantly enhance capabilities when paired with established open-source offensive tools.
Defenders should watch for unusual automated reconnaissance, high-volume scanning activity, and quick transitions from discovery to targeted exploitation attempts.
Organizations should strengthen their internet-facing assets, continuously manage exposed secrets, restrict unnecessary endpoints, and ensure that web application controls can detect common automated tools.
The shift from jailbreak tutorials to a commercial offensive platform in just three months illustrates how quickly AI-abuse techniques can evolve from experimentation to criminal services.
ALERT: 20+ government sites delivered malware to businesses and citizens. See full attack research to check your own exposure
