欢迎来到Kernel Panic，由Lily Hay Newman 和 Matt Burgess 来自隐私和数字安全新世界的每周通讯。 每周在收件箱里收到这份通讯请在这里报名
新的研究完全与Kernel Panic 显示分享，黑客开始将AI功能添加到一个新的信息化恶意软件的菌株中，使得系统可以自动剖析受害者，并迅速浮出最高值目标及其信息。 Dubbed “Volta-Autodoxer”由于恶意软件在内部如何称呼自己，Cisco Talos研究者的调查结果揭示了商业LLMs被用于增强和增强已确立的恶意软件类型的能力的方式。
通常隐藏在假冒软件中，信息采集者被设计成符合自己的名字，抓取用户名，密码，认证信使，饼干，信用卡数据，以及更多来自感染机的。 许多近年来最大的数据漏洞——从包括AT&T和Ticketmaster在内的与Snowflake有关的广泛漏洞到窃取迪士尼数据的千兆字节——都是黑客利用信息采集者收集的登录细节访问目标造成的。 总体而言，恶意软件近年来被用来窃取数亿的资信。
“沃尔塔作为一个盗窃者相当成熟。 它为它所收集的东西投下了相当宽的网，"称 Ryan Fetterman，一位Cisco Talos的安全研究员。 “它将所有这些东西汇集在一起，最终生成一个序列化的档案，可以发送给几个LLM型号。 要求模型扮演情报分析师的角色，这就像一个优先和分析功能。
Talos使用其新的CAIRN框架标记了恶意软件，这个框架是用来识别包含AI能力的黑客工具的。 Fetterman 指出认为塔洛斯没有跟踪沃尔塔是否在野外被使用。
沃尔塔的传统信息化能力非常强大，它扫描存储在浏览器中的密码，Microsoft OAuth令牌，cookie，支付卡，以及加密钱包种子短语，但也活跃着Discord,Telegram,Steam和Roblox会话。 然后恶意软件用它的第一回合发现做了第二次更深的扫描 Volta透过查看目标Gmail或另一中央帐户
完成这一切后，恶意软件将其发现输入AI工具，使用OpenRouter进行分析，这种服务可以向多个不同的AI提供者发送提示。 Volta默认其请求为Anthropic的Claude Opus 4.6. 但显然为模型的护栏可能阻断活动做准备，沃尔塔的建造背负中国开放重量的Moonshot AI Kimi K2，如果失败，则使用Google的Gemini 2.5 Flash. 建立后退型和依靠成本效益高的老一代模式是攻击者的常见技术。
沃尔塔的创作者包括一个240字的提示，包括弹点和编号列表，作为他们对任何LLM分析所收集数据的指示的一部分。 “你是一个法医情报分析师，它指示聊天组制作关于这个人的“执行摘要 ”，详细介绍他们做什么，“他们的价值 ”，以及“他们的意见 ”。 新增认为聊天员应该“将点点连接到字段之间”，例如检查某人的Wi-Fi密码是否与其姓相符。 “深入，不宽，”即时称。
”Fetterman 称。 " 但他们正在建设中，期望在最初提出要求时有可能击中拒绝模式。 因此，他们计划失败一种级联更多允许的模型他们走下链。 使用人工智能的能力也依然有效。 AI的电话有点超乎寻常
一些低级别网络犯罪分子和诈骗犯抱怨AI slop充斥网络犯罪论坛，但安全研究者越来越多地发现其他黑客使用LLMs进行编码任务或分析被盗信息的线索。 例如，威胁情报公司Crowdstrike的研究人员最近告诉WIRED说，他们已经看到四个不同的黑客团伙，他们精通中文、西班牙文和英文、印度尼西亚文和俄文，使用AI工具损害世界各地数十个目标，包括保健、零售和旅行方面的政府实体和企业。
Cisco的Fetterman 称 Volta包含了一些线索，说明它可能是为了向一系列攻击者出售而建造的，而不是为一个特定的演员运动开发的。 而其核心的恶意软件仍然是传统的信息化工具，而AI扩展预示着未来会更加入侵和邪恶的活动。
“如果你能够更快地识别出自己的高价值目标，你可能有更多的机会使用他们的证书，“我们看到更先进的能力可以提供给低级的先进攻击者。 这真的很有趣
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New research shared exclusively with Kernel Panic shows that hackers have started adding AI functionality into a new strain of infostealer malware, making it possible for the system to automatically profile victims and quickly surface the highest value targets and their information. Dubbed “Volta-Autodoxer” because of how the malware refers to itself internally, the finding by Cisco Talos researchers sheds light on the ways that commercial LLMs are being used to augment and enhance the capabilities of established types of malware.
Often hidden in counterfeit software, infostealers are designed to live up to their name, grabbing usernames, passwords, authentication tokens, cookies, credit card data, and more from infected machines. Many of the biggest data breaches in recent years—from the widespread Snowflake-linked breaches that included AT&T and Ticketmaster to the theft of a terabyte of Disney data—have resulted from hackers accessing targets using login details gathered by infostealers. Overall, the malware has been used to steal hundreds of millions of credentials in recent years.
“Volta is pretty mature as a stealer. It casts a pretty wide net for what it collects,” says Ryan Fetterman, a security researcher at Cisco Talos. “It compiles all of those things together, ultimately producing a serialized dossier that it can send to a couple LLM models. It’s asking the model to act like an intelligence analyst and produce structured citation-backed assessment of the victim. It’s like a prioritization and analysis function.”
Talos flagged the malware using its new CAIRN framework, built to identify hacking tools that incorporate AI capabilities. Fetterman notes that Talos did not track whether Volta has been used in the wild.
Volta’s traditional infostealer capabilities are powerful and seem to be geared toward targeting younger internet users with robust digital lives. It sweeps for passwords stored in browsers, Microsoft OAuth tokens, cookies, payment cards, and crypto wallet seed phrases, but also active Discord, Telegram, Steam, and Roblox sessions. Then the malware does a second, deeper sweep using its first-round findings. By looking through the target’s Gmail or another central account, Volta builds a fuller picture of the victim, their location, and their habits using data like receipts and order history from services including UberEats and DoorDash.
Once all of this is done, the malware feeds its findings into AI tools for analysis using OpenRouter, a service that can send prompts to multiple different AI providers. Volta defaults its requests to Anthropic’s Claude Opus 4.6. But apparently preparing for the possibility that the model’s guardrails could block the activity, Volta is built with fallbacks to the Chinese open weight Moonshot AI Kimi K2 and, if that fails, Google’s Gemini 2.5 Flash. Building in fallbacks and relying on cost-effective, older-generation models are common techniques among attackers.
Volta’s creators included a 240-word prompt, including bullet points and a numbered list, as part of their instructions to any LLM analyzing the collected data. “You are a forensic intelligence analyst drafting a target assessment from a structured evidence bundle,” the Volta prompt says. It instructs the chatbot to produce an “executive summary” about the person, details of what they do, “what they’re worth,” and a summary of “their opsec.” It adds that the chatbot should “connect dots across fields,” for example, checking whether someone’s Wi-Fi password matches their last name. “Go deep, not wide,” the prompt says.
“The prompt is pretty carefully crafted not to imply anything overtly malicious,” Fetterman says. “But they’re building in the expectation to potentially hit model refusals at first request. And so they plan for failover kind of cascading to more permissible models as they go down the chain. And there’s also the capability to still use the implant without the AI. The AI calls are kind of above and beyond, but the malware will still work without it.”
Some low-level cybercriminals and scammers have complained about AI slop filling up cybercrime forums, but security researchers are increasingly discovering other hackers using LLMs for coding tasks or analyzing troves of stolen information. Researchers at threat intelligence firm Crowdstrike, for example, recently told WIRED they had seen four distinct hacking groups with varying sophistication—operating in Chinese, Spanish and English, Indonesian, and Russian—using AI tools to compromise dozens of targets around the world, including government entities and businesses in health care, retail, and travel.
Cisco’s Fetterman says Volta contains some clues that it may have been built to sell to a range of attackers rather than being developed for one specific actor’s campaigns. And while the malware at its core is still a traditional infostealer, the AI expansion foreshadows even more invasive and sinister activity in the future.
“If you’re able to identify your high-value targets faster, you probably have a better chance of using their credentials or authenticating using stolen tokens more often than maybe you would have if you had to do that triage yourself,” Fetterman says, referencing the fact that authentication tokens expire and passwords can be changed. “We’re seeing more advanced capabilities accessible to lower-level sophistication attackers. It’s really interesting and disturbing.”
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