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AI“黑客”不到4小时在热门工业控制软件中发现4个严重漏洞AI 'hacker' finds 4 severe bugs in popular industrial control software in under 4 hours

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一个自主 AI 智能体在使用了数十年、广泛部署的 EPICS(实验物理与工业控制系统)开源软件工具包中发现了四个漏洞,其中包括一个严重缺陷,可能允许远程攻击者在用于控制粒子加速器和聚变实验的系统上执行代码。

An autonomous AI agent discovered four vulnerabilities in the decades-old, widely used EPICS (Experimental Physics and Industrial Control System) open source software toolkit, including a critical flaw that could allow remote attackers to execute code on systems used to control particle accelerators and fusion experiments.

这些漏洞包括:一个 CVSS v3.1 评分 9.8 分的严重整数溢出漏洞(CVE-2026-114595),导致攻击者可控的越界堆写入,并可能引发远程代码执行;一个评分 8.2 分的高危消息长度验证不当漏洞(CVE-2026-114596),导致越界内存写入和控制器进程崩溃;一个评分 7.5 分的高危边界检查不足漏洞(CVE-2026-114597),允许越界内存读取和进程崩溃;以及一个评分 7.5 分的高危类型混淆漏洞(CVE-2026-114598),可导致拒绝服务,并可能泄露相邻内存内容。

The bugs include a critical, 9.8-rated under CVSS v3.1 integer overflow vulnerability (CVE-2026-114595), leading to an attacker-controlled out-of-bounds heap write and potentially remote code execution; an 8.2-rated, high-severity, improper message-length validation flaw (CVE-2026-114596), causing an out-of-bounds memory write and controller-process crash; a 7.5-rated, high-severity insufficient bounds checking bug (CVE-2026-114597) that allows out-of-bounds memory reads and process crashes; and a 7.5-rated, high-severity type confusion flaw (CVE-2026-114598) that can lead to denial of service and could expose adjacent memory contents.

所有四个漏洞均影响 EPICS Base,后者被用于运行世界上一些最大的科学研究项目和设施,相关组织应更新至包含修复的 7.0.11 版本。美国网络安全和基础设施安全局(CISA)在周二发布的通报中警告称:“成功利用这些漏洞可能允许攻击者导致拒绝服务状况、破坏内存、泄露敏感信息,或潜在地执行任意代码。”

All four affect EPICS Base, which is used to operate some of the world's largest scientific research projects and facilities, and organizations should update to version 7.0.11, which includes the fixes. “Successful exploitation of these vulnerabilities could allow an attacker to cause a denial-of-service condition, corrupt memory, disclose sensitive information, or potentially execute arbitrary code,” the US Cybersecurity and Infrastructure Security Agency (CISA) warned in a Tuesday advisory.

Causal Security 联合创始人 Shubham Raj 告诉 The,名为 Cipher 的 AI 智能体独立发现了这四个此前未知的安全漏洞——对陌生的 EPICS 系统进行调查和测试,并验证了四个利用代码——耗时三小时四十九分钟。Raj 表示:“初步调查无需人工干预,随后仅需一条指令授权在安全环境中进行更深入的可利用性测试。”

An AI agent called Cipher independently found all four previously unknown security holes - investigating and testing the unfamiliar EPICS system, and validating the four exploits - in three hours and 49 minutes, Causal Security co-founder Shubham Raj told The. “The initial investigation required no human intervention, followed by one instruction authorizing deeper exploitability testing in a secure environment,” Raj said.

今年早些时候,Causal Security 的 Cipher —— Raj 将其描述为“一个能够跨技术栈进行推理的完全自主的超级黑客” —— 在北美和欧洲广泛使用的电网系统中发现了多条关键攻击路径,促使 CISA(美国网络安全和基础设施安全局)于 10 月 8 日发布安全通告。

Earlier this year, Causal Security’s Cipher, which Raj described as “a fully autonomous super hacker that can reason across the technology stack,” found multiple critical attack paths in power-grid systems used across North America and Europe, prompting an October 8 security advisory from CISA.

EPICS 最初由洛斯阿拉莫斯国家实验室和阿贡国家实验室开发,用于构建和远程控制分布式数据采集与监视控制系统(SCADA),将操作员与物理设备连接起来。它被全球约 90 个主要科研、大学和工业项目及设施使用,包括阿贡国家实验室的先进光子源和 ITER 聚变反应堆控制系统。

EPICS, originally developed by Los Alamos National Laboratory and Argonne National Laboratory, is used to build and remotely control distributed Supervisory Control and Data Acquisition (SCADA) systems, connecting operators to physical devices. It’s used in around 90 major scientific, university, and industrial projects and facilities globally including Argonne National Laboratory's Advanced Photon Source and ITER's fusion reactor control system.

这四个漏洞无一不说明,AI 智能体在发现工业与运营技术漏洞方面极为擅长 —— 这些系统和设备过去曾能依靠“默默无闻”来躲避黑客攻击 —— 并加剧了防御者的担忧:自主网络攻击瘫痪电网、供水系统等关键服务,似乎只是时间问题。这类数字入侵可能造成实体伤害。

All four of these flaws illustrate how AI agents are really good at finding vulnerabilities in industrial and operational technologies - systems and equipment that used to be able to rely on obscurity to protect them from hackers - and add to defenders' concerns that it's only a matter of time until an autonomous cyberattack shuts down critical services, like power grids or water systems. These are the types of digital intrusions that can cause physical harm.

Raj 指着 CVE-2026-114595 这个关键的整数溢出漏洞举例说:“它允许攻击者控制的网络数据导致越界堆内存写入,具有远程代码执行的潜在风险。”他接着表示:“EPICS 控制器位于操作员与物理设备之间,负责处理测量、命令和控制功能。从运营角度看:设想一个正在进行昂贵实验的粒子加速器。攻击者有可能使控制器崩溃,中断关键测量或控制功能,迫使操作员叫停实验。”

Raj points to CVE-2026-114595, the critical integer-overflow vulnerability, as an example. “It allows attacker-controlled network data to cause an out-of-bounds heap memory write, with potential for remote code execution,” he told us. “EPICS controllers sit between operators and physical equipment, handling measurements, commands, and control functions,” he continued. “Operationally: Imagine a particle accelerator in the middle of an expensive experiment. An attacker could potentially crash a controller, interrupt critical measurements or control functions, and force operators to halt the experiment. That could mean lost experimental work, significant downtime, and expensive recovery.”

这可能意味着实验工作丢失、长时间停机以及高昂的恢复成本。”此外,拉杰表示,如果攻击者能够开发出远程代码执行漏洞利用,这可能使他们能够“控制受影响的进程、操纵读数、干扰控制功能,或破坏与其连接的设备”。在真实的科学设施中利用这些漏洞的前提是能够访问设施控制网络上存在漏洞的EPICS服务。但如果网络分段不充分,或者另一个系统能够访问存在漏洞的EPICS网络,这种情况就可能发生。

Plus, if an attacker was able to develop an RCE exploit, this could allow them to “take control of the affected process, manipulate readings, interfere with control functions, or disrupt the equipment connected to it,” Raj said. The prerequisite for exploiting these vulns in a real scientific facility is being able to reach the vulnerable EPICS services on a facility's control network. But this could occur if the networks weren’t sufficiently segmented, or another system had access to the vulnerable EPICS network.

拉杰说:“一旦攻击者能够找到一个配置错误或他们能够访问的网络,实施攻击就相当容易了。”他补充说,利用漏洞不需要深厚的OT知识,也不需要了解粒子加速器或聚变反应堆的工作原理。“具备常规漏洞利用技能的人就可以对它们进行研究,而能力日益强大的AI系统可以帮助开发漏洞利用,无需专门的OT专业知识。”

“Once an attacker is able to find a network, which is either misconfigured or they are able to reach, it’s pretty easy to carry out the attacks,” Raj said, adding that exploitation wouldn’t require deep OT knowledge, or understanding of how particle accelerators or fusion reactors work. “Someone with conventional exploitation skills could investigate them, and increasingly capable AI systems could help develop exploits without requiring specialized OT expertise.”

他补充说,操纵特定的物理过程确实需要额外的知识。“但攻击者不需要了解粒子加速器的物理学原理就能破坏控制它的软件。使关键进程崩溃或中断监控和控制就已经可能造成严重的运营后果。正在发生变化的是,攻击者可能不再需要多年的专业知识就能发现这些弱点。”®

Manipulating specific physical processes does require additional knowledge, he added. “But an attacker doesn't need to understand the physics of a particle accelerator to disrupt the software controlling it. Crashing critical processes or interrupting monitoring and control can already have serious operational consequences. What's changing is that attackers may no longer need years of specialized expertise just to discover these weaknesses.” ®

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