CrowdStrike 于 2026 年 9 月 16 日通过官方博客发布公告，推出面向 AI Agent（AI 代理）的持续身份（Continuous Identity）能力。该公告属于厂商产品/能力发布性质，正文摘要未包含技术实现细节、检测规则、漏洞信息或攻击者归因，因此以下内容主要基于公告定位与行业背景梳理。随着企业在业务流程中引入自主或半自主 AI 代理，组织内快速涌现大量非人类身份（NHI），例如服务账号、API 密钥、OAuth 令牌、机器证书与工作负载身份。这些身份往往拥有调用内部系统、SaaS、云 API 与数据存储的权限，而其创建、授权与调用行为通常游离于以人为中心的传统 IAM 和 EDR 覆盖范围之外，形成身份治理与检测盲区。一旦代理凭证被窃取或代理被滥用，攻击者可借助“合法身份 + 合法 API 调用”的方式规避基于恶意文件的检测，实施横向移动与数据访问。CrowdStrike 宣称通过持续验证 AI 代理的身份及其运行时行为，将其纳入统一的身份安全与终端/云检测体系，以提升可见性与控制力。需注意，本条为厂商自行发布的公告与营销内容，未提供可验证的技术白皮书要点、部署方式、检测覆盖范围或第三方评测，对其实际效果应保持审慎。原文未提及任何 CVE、IOC、攻击组织或恶意软件家族；输入数据中被自动标注的“Conti”与“apt”标签与本公告主题无实质关联，疑为标签抽取噪声。

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本次输入并不包含可用的威胁情报内容。记录的标题为“京公网安备 11000002002063号”，这是中国大陆网站 ICP/公安联网备案的编号文本，来源 URL 指向 beian.gov.cn 的备案信息查询接口，而非任何安全报告正文。输入中声明的 source_name 为“360CERT 安全报告”，published_at 为 2026-09-16，tags 为 360、malware、apt、report，但正文摘要字段为空，cves 为空，未提供任何可能的攻击组织、恶意软件家族、受害行业、受害地区或 ATT&CK 技术映射，iocs_present 标记为 false。也就是说：标签暗示可能与 360 相关的恶意软件/APT 报告有关，但标题、URL 与标签三者互相矛盾，无法确认其真正指向的是哪一篇报告、哪个攻击活动或哪个漏洞。从防御视角看，该条目不具备任何可执行价值：既无法据此归因，也无法据此构造检测规则、狩猎假设或补丁优先级。建议将其视为数据采集/解析管道的噪声或抓取错误处理，回退到原始信源重新获取有效正文后再做分析。在获得有效正文之前，不应基于此条目生成任何 IOC、封禁清单或告警升级动作，避免把备案号误当成威胁指标污染内部情报库。

本条输入并非威胁情报内容，而是一个企业资质备案页面的元数据。标题“京网文〔2020〕6051-1195号”是北京市文化和旅游主管部门核发的《网络文化经营许可证》编号格式（京网文 + 年份 + 编号），说明该网页是 360 公司在其官网 360.cn 上公示经营资质与合规信息的静态页面（URL 路径 /licence1.html 亦印证这一点）。正文摘要为空，未包含任何关于攻击活动、恶意样本、漏洞、基础设施或受害者的描述。tags 中出现的 360、malware、apt、report 更可能来自采集系统的默认标签或上游分类模板，而非页面本身内容；cves 为空、iocs_present 为 false、可能攻击者、恶意软件家族、行业、地区、ATT&CK 技术全部为空，进一步说明该条目不含可操作情报。published_at 显示为 2026-09-16，与许可证 2020 年核发的时间不符，推测该时间戳是爬虫抓取或数据入库时间，而非文档发布时间，因此不具备事件时序意义。综合判断：这是一条被错误采集、错误分类进入威胁情报流的“数据源噪声”，其真实内容是企业合规公示，与网络安全攻防无任何关联。对分析团队而言，正确的处置不是从中提取 TTP 或 IOC，而是将其标记为非情报（non-intel）并从情报库、看板与告警规则中剔除或降权，同时回溯采集配置（source_url 白名单、关键词规则、标签映射逻辑），避免同类资质页、备案页、法律声明页持续污染情报管道，造成分析人力浪费与误报。

该输入标题为“（总）网出证（京）字第281号”，来源标注为“360CERT 安全报告”，但实际链接指向 360.cn 的许可证页面（licence2.html），且 summary/body excerpt 为空。标题本身是中国的网络出版服务许可证编号格式，并非安全报告标题。标签虽包含 360、malware、apt、report，但没有任何实质性的威胁情报内容，包括攻击活动描述、战术工具链、受害者特征、CVE 编号、攻击者归因、恶意软件家族、ATT&CK 技术或 IOC 数据。经分析，这很可能是一条因数据采集或标签映射错误而产生的误报条目，而非真实的威胁报告。360CERT 本身是合法的安全应急响应团队，但此条目的内容与威胁情报无关。因此，无法从中提取任何可用于防御的线索。建议安全团队不要基于此条目采取行动，并检查数据源采集管道，修正标签映射逻辑，避免类似误报消耗分析资源。若确实存在对应的 360CERT 报告，应通过官方渠道重新获取正确内容。

本次输入不构成一篇可用的威胁情报文章。所提供的“标题”内容为“京ICP证080047号[京ICP备08010314号-6]”，这是中国大陆工业和信息化部ICP备案/许可证编号，属于网站合规备案信息，而非安全事件标题；source_url 指向 https://beian.miit.gov.cn/，即工信部备案管理系统官网，并非威胁情报发布页面；正文/摘要字段为空，未提供任何事件描述、攻击链、样本信息或技术分析。元数据中虽然带有 360、malware、apt、report 等标签，并标注来源为“360CERT 安全报告”，但这些标签与标题、正文、URL 之间完全无法互相印证，缺乏可支撑分析的最小信息量。同时，published_at 标注为 2026-09-16，属于未来时间戳，进一步提示该条记录很可能是采集流水线中的脏数据、模板占位记录或抓取错位（例如抓取到了备案页面的页脚文本），而非真实发布的安全报告。由于原文既未提及任何攻击组织、恶意软件家族、受害行业与地区，也未给出 CVE 编号、IOC 或 ATT&CK 技术编号，本条目无法用于归因、影响面评估或检测规则编写。任何基于该条目的推论（例如“360 发布了某 APT 报告”）都属于无依据的臆测，不应写入情报库或工单。建议将此条目标记为数据质量问题并回退到采集环节修复，重新获取真实的 360CERT 报告原文后再行分析。

该论文关注大规模网络环境下防御高级持续性威胁（APT）的决策理论问题。作者基于近期提出的布尔动力系统（Boolean Dynamical Systems）框架展开研究，该框架能自然刻画 APT 的四个第一性原理要素：攻击的隐蔽性、来自入侵检测系统等自动化手段的信息有限且含噪声、攻击者渗透后在内网中的横向移动、以及防御者在任何时刻只能加固部分主机且需付出系统可用性等资源代价。核心难题在于：在该模型下进行最优或启发式控制时，涌现出的值函数随网络规模增长而计算不可解，导致无法以可处理的方式求解防御策略。针对此，作者提出一种受平均场分析（mean-field analysis）启发的启发式值函数，并证明：当底层状态估计分布最大化熵时，该启发式恰好等于值函数的精确计算值，从而为近似方法提供了理论依据。随后，作者通过数值实验评估该启发式在不同熵假设违反程度下的表现质量，即参数化地衡量近似偏差。主要贡献包括：一是为 APT 防御决策提供计算可处理的近似值函数；二是在特定熵假设下给出精确性证明；三是通过数值分析量化熵假设被破坏时启发式质量的退化趋势。该工作适合网络攻防博弈、防御决策理论、网络安全建模与自动化防御策略研究者阅读，为大规模网络下的 APT 防御资源调度与策略优化提供了新的理论基础与可扩展分析方法。

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Microsoft examines an AI-assisted business email compromise campaign that used executive impersonation and fake invoices to target finance teams with ACH payment fraud. The post Protecting organizations from AI-assisted executive impersonation and invoice fraud appeared first on Microsoft Security Blog.

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这篇文章由微软安全博客发布，针对AI向客户自有环境及边缘设备下沉的趋势，提出了系统化的安全建议。主体观点认为，在客户拥有且可物理接触的硬件环境中部署Edge AI时，传统云端信任边界已不适用，需要在保护敏感数据、凭据和模型之前，先对底层的系统、软件和AI资产进行可信验证。文章内容很可能涉及基于硬件信任根和远程证明所构建的信任链，用于验证主机固件、操作系统、容器、微服务以及模型文件的完整性；同时建议通过模型签名、模型来源追踪、差分检测等方式来防范AI资产在实际运行环境中被篡改或替换。文章还强调在数据流入模型前应通过API鉴权、加密、脱敏或端侧策略隔离敏感数据与凭据，并对边缘节点施行基于零信任的访问控制与持续监视，将安全事件响应能力延伸至无人值守的远端。而且需要针对边缘AI设计不可变日志、异常行为和模型输出对比等功能，以应对物理侧信道和供应链定向攻击。原文并未披露具体漏洞名称、恶意软件家族或威胁组织，也未附上IOC，更多属于基础设施架构与信任模型建设指导。本文总结仅基于文章公开摘要，未能覆盖全部细节，但可帮助安全团队把握方向。

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Using autonomous AI agents, an attacker breached an enterprise network in a matter of hours. Understand how to address and defend against agentic attacks. The post An AI-Assisted Cyber Attack: Inside a Unit 42 Investigation appeared first on Unit 42.

这是一篇来自 CrowdStrike 官方博客的公告，介绍 CrowdStrike 与 Zscaler 达成合作，旨在将持续身份（Continuous Identity）能力引入零信任访问（Zero Trust Access）。文章核心内容是两家公司将 CrowdStrike 的端点检测与响应（EDR）所获得的终端风险信号、身份威胁检测能力，与 Zscaler 的零信任网络访问策略相结合，实现基于用户身份和上下文风险的实时、动态访问控制。这种集成意味着当用户设备存在可疑行为或身份风险升高时，Zscaler 可以自动收紧或阻断访问权限，从而降低因凭证窃取、内部威胁或横向移动带来的安全风险。文章提到的价值在于打破传统只基于静态身份验证的边界防护，而是以持续评估的方式在每一次访问请求中确认用户设备安全和行为可信度。CrowdStrike 作为 EDR 厂商提供终端侧的高保真检测信号，Zscaler 则作为云安全接入点执行策略。两者结合在一定程度上缩短了从检测到响应的闭环时间。需要注意的是，这篇博客并未涉及任何具体的攻击事件、漏洞利用链、恶意软件样本或真实受害者信息；它更偏重产品功能和合作理念的说明。输入元数据中标记了可能的恶意软件家族为 Conti，但正文内容没有提及，也没有相关证据，因此不应据此推断该合作与 Conti 有关。本文对蓝队而言属于生态合作与安全能力演进参考，而非即时威胁预警。

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An active campaign is impersonating legitimate software vendors to deliver malware through look-alike download pages and regenerated installer archives. Microsoft Defender Experts shares observed attack techniques, Defender XDR detections, indicators of compromise, and practical mitigations to help organizations identify, block, and respond to this threat. The post Counterfeit installers to system

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It’s getting cheaper and easier for cybercriminals to research potential victims. Here’s what’s still in your control.

Microsoft Threat Intelligence examines attacks on exposed AI workloads, including LiteLLM gateway exploitation, credential harvesting, persistence, and cryptomining activity. The post When AI infrastructure becomes the target: Securing gateways and control points appeared first on Microsoft Security Blog.

随着高级持续性威胁（APT）的日益普及，APT 恶意软件组织分类问题近年来受到更多关注。然而，以往的方法大多采用简单的分类器进行组织分类，忽略了两个关键问题：一是已披露的恶意软件样本数量稀疏导致分类偏差，二是大多数组织在恶意软件功能分布上存在差异，简单分类器难以适应这种分布不平衡。针对这些挑战，本文提出了一种基于元学习架构的预测引导原型网络（PGPNet），能够利用有限的监督样本快速适应新的分类任务。该网络的核心创新在于：将恶意软件功能分类作为辅助任务，通过多任务学习增强特征表示能力；同时，通过将辅助任务的预测结果介入组分类器的决策过程，消除由于功能分布差异引起的分类偏差。具体而言，PGPNet 在元学习框架下学习一个原型空间，并在该空间中执行样本与类原型的距离度量，从而完成组织分类。辅助任务提供了丰富的上下文信息，使得特征学习更具判别性。在 APT 恶意软件数据集上的实验结果表明，PGPNet 成功利用了辅助任务的上下文信息和预测结果，达到了当前最优的性能。该研究为在数据稀缺且分布多样的场景下进行恶意软件组织识别提供了新的思路，对威胁情报分析和 APT 追踪具有潜在的应用价值。

Organizations need protection that operates in the gap between discovery and remediation. The post The patch window is collapsing: Why security needs a new control plane appeared first on Microsoft Security Blog.

Explore Unit 42 research on AI-enabled malware. Learn how existing behavioral detection and endpoint analytics stop AI-authored code before execution. The post The State of AI-Enabled Malware August 2026: From Brand Abuse to Agentic Execution appeared first on Unit 42.

Attackers are targeting CI/CD pipelines and developer tools instead of application code, requiring total SDLC visibility and strict security controls The post Connecting the Dots: Securing the Overlooked Corners of the Software Development Lifecycle (SDLC) Supply Chain appeared first on Unit 42.

CrowdStrike Named an Innovation and Growth Leader in the 2026 Frost Radar™: Cloud and Application Runtime Security

本文提出并实现了一个名为 NODLINK 的在线 APT 攻击检测系统，旨在解决现有在线溯源图检测系统为了降低计算复杂度而牺牲检测粒度，导致生成的溯源图包含超过 10 万个节点、难以被安全运维人员解读的问题。作者的核心洞察是：在线溯源图检测中的 APT 攻击检测过程可以被建模为斯坦纳树问题（Steiner Tree Problem, STP），该问题存在具有理论上界误差的高效在线近似算法，能够恢复出简洁且与攻击相关的溯源子图。为了将 STP 近似算法框架应用到 APT 检测中，文章提出了内存缓存设计、高效的攻击筛选方法，以及一种新的 STP 近似算法，该算法在保持相同复杂度的同时比传统算法更适用于 APT 检测场景。作者在真实生产环境中评估了 NODLINK，开放世界实验表明，与两种最先进的在线溯源分析系统相比，NODLINK 在检测精度和调查精度上均高出数量级，同时保持相同或更高的吞吐量。该研究的主要贡献在于首次实现了不牺牲检测粒度的在线检测系统，同时保持高精度和高效率，为 APT 攻击的实时检测与调查提供了一种可行方案。适合从事系统安全、溯源分析、在线检测研究的学者及需要理解 APT 检测前沿技术的蓝队安全工程师阅读。

Unit 42 details how attackers exploit enterprise collaboration tools for identity phishing and credential theft. Discover key defense strategies. The post Identity Abuse Through Trusted Communication Channels appeared first on Unit 42.

Microsoft is named a visionary leader in the 2026 Frost Radar for Cloud Workload Protection Platforms, recognized for unified runtime security with Microsoft Defender for Cloud. The post Microsoft named a Leader in the Frost Radar™: Cloud Workload Protection Platforms, 2026 appeared first on Microsoft Security Blog.

CrowdStrike Services and Agentic MDR Put the Agentic SOC in Reach

Expanding AI Benchmarks in Cybersecurity Beyond Vulnerability DiscoveryAug 06, 2026

In August 2026, the actor TheHatman claimed to have stolen large volume of credentials from organizations' Microsoft Entra tenants. We provide guidance on mitigating large-scale credential attacks. The post Threat Brief: Mitigating Large-Scale Credential Attacks (Updated August 18) appeared first on Unit 42.

MacSync Stealer rapidly rotates domains to evade detection, but its behavior remains consistent. Learn how Microsoft uncovered 30+ related domains using durable hunting pivots. The post Hunting MacSync Stealer infrastructure through behavioral pivots appeared first on Microsoft Security Blog.

Secure Agent Harness Execution: Preventing EscapeAug 04, 2026

高级持续性威胁（APT）攻击者越来越多地利用复杂技术在企业网络的不同子网间进行横向移动。及时的检测与防御依赖于跨子网的协调，但维持全局态势感知会产生大量的通信开销。为了平衡这一权衡，需要灵活的监控和可适应的遏制策略。本文提出了ADAPTD，一个通信与计算高效、基于决策论的框架，包含三个核心组件：(i) 紧凑型杀伤链，用于识别多样的攻击向量；(ii) 即时阻断机制，用于及时遏制攻击；(iii) 预测性驱逐策略，以恢复系统安全。作者通过实验验证了ADAPTD在多种威胁场景下的有效性。首先，他们提出的去中心化信念更新方案优于最先进的扩散隐马尔可夫模型（HMM）。其次，与基于Transformer的检测方法相比，ADAPTD显著减少了误驱逐。第三，在噪声环境下，自适应阻断能够遏制攻击者，同时最小化不必要的干扰。最后，消融研究证实，结合两种防御动作能够显著降低防御者的总成本。该框架面向安全运营中心（SOC）和网络防御者，提供了一种在通信开销与检测精度之间取得平衡的实用方法。

本文提出一种基于大语言模型（LLM）的两阶段框架，用于从异构安全日志中进行零样本内部威胁和高级持续性威胁（APT）检测。该方法首先将用户活动建模为按时间顺序排列的时间线，并引入检索增强生成（RAG）技术，从用户历史行为中提取个性化上下文，以增强对异常行为的理解。与直接从原始日志进行端到端分类不同，该框架首先生成结构化、可解释的威胁特定风险指标集合，随后在时间序列上对这些指标进行联合分类，从而捕获跨多个时间窗口的攻击模式。作者在CERT r5.2（内部威胁检测）和PicoDomain（APT检测）两个基准数据集上进行了实验，结合两种开放权重LLM、在检索与非检索设置下共四种配置。结果显示，所有配置均优于已有的基于LLM的最先进框架GABM，最佳配置在CERT r5.2上将F1分数提升11.40个百分点，在PicoDomain上提升31.50个百分点。进一步分析表明，检索主要对较弱的LLM有益，能够生成更具区分度的风险指标，而较强的模型在无检索上下文时也能达到相当性能。此外，两阶段中LLM的最优分配取决于具体数据集。研究得出结论：生成的风险指标质量是决定零样本网络威胁检测性能的关键因素。该工作为利用LLM进行可解释、零样本安全日志分析提供了新思路，并强调了结构化中间表示的重要性。适合安全研究人员、SOC分析师及LLM应用开发者阅读。

And will today’s surge in AI-driven vulnerability discovery eventually make tomorrow’s software safer?

Google is a Leader in the Forrester Wave™: Cybersecurity Incident Response Services, Q2 2024Read the report

Google is a Leader in the IDC MarketScape: Worldwide Cybersecurity Consulting Services 2024 Vendor AssessmentRead the report

Discover how Kimwolf v7 targets Android IoT devices with HTTP/2 DDoS fingerprinting, Ethereum ENS C2 resolution and Tor backup routing. The post Kimwolf v7: An Evolution of the Kimwolf Botnet appeared first on Unit 42.

Analysis of the Aeternum botnet loader, a threat leveraging Polygon blockchain smart contracts for decentralized C2 infrastructure and payload execution. The post The Permanent Threat: Analyzing Aeternum’s Blockchain-Based C2 Operations and Communications appeared first on Unit 42.

Microsoft is named a Leader in the 2026 IDC MarketScape for MDR services. Discover how Microsoft Defender Experts MDR combines AI, threat intelligence, and human expertise. The post Microsoft named a Leader in the 2026 IDC MarketScape for MDR/MXDR for the Enterprise  appeared first on Microsoft Security Blog.

Microsoft Threat Intelligence examines DeadLock ransomware, an emerging financially motivated operation distinguished by its use of decentralized infrastructure to support victim communications, negotiations, and data leak operations alongside double extortion tactics used to pressure victims. The post DeadLock ransomware: Breaking down a Rust-based encryptor with decentralized recovery infrastruc

Identity-based attacks drive 90% of incidents. Learn how modern attackers exploit identities and what SOC leaders can do to respond. The post Inside the Modern SOC: The Identity Front Door appeared first on Unit 42.

5 High-Impact Use Cases for Falcon Onum

Falcon AIDR Now Protects Copilot Studio Agents and Claude CodeJul 30, 2026

Analysis of ChainDrop, an npm supply chain worm extracting GitHub Actions runner secrets and using Ethereum smart contracts for C2 routing. The post ChainDrop: Inside a Self-Propagating npm Worm appeared first on Unit 42.

Discover how attackers hijack AI tokens to fuel gray market transfer stations by stealing developer API keys. The post Token Jacking: Cybercriminals Could Be Stealing Your AI Resources appeared first on Unit 42.

Learn why KuppingerCole named Microsoft a Leader in its Leadership Compass: Cloud Native Application Protection Platforms report. The post ​​Microsoft named a Leader in the KuppingerCole Leadership Compass for Cloud Native Application Protection Platforms (CNAPP) appeared first on Microsoft Security Blog.

A credential-stealing worm hidden in more than 400 compromised npm packages automatically spread across software ecosystems by republishing malicious updates. This analysis details the attack chain, affected environments, and practical guidance for detection, hunting, and remediation. The post ChainDrop supply chain compromise: Anatomy of a self-propagating worm appeared first on Microsoft Securit

Microsoft expands its Zero Trust for AI strategy to enhance security for AI and DevSecOps environments with new tools and guidance. The post Advance Zero Trust for AI: New tools and guidance to secure AI agents and DevSecOps appeared first on Microsoft Security Blog.

Microsoft Defender automatically isolated a compromised QNET endpoint in 128 seconds, stopping a multi-stage attack before the payload could persist or spread. The post 128 Seconds to disruption: Microsoft Defender stops ransomware at QNET  appeared first on Microsoft Security Blog.

Frontier AI is reshaping vulnerability discovery. Learn how our NOVA system found 14,000+ unknown vulnerabilities across the open-source software supply chain. The post The Frontier AI Vulnerability Burst: Industrializing Autonomous Zero-Day Discovery in Open-Source Software appeared first on Unit 42.

Nearly half of C2 malware bypasses DNS by connecting directly to IP addresses. Zero trust IP enforcement secures networks against these threats. The post Almost Half of Malware Samples Communicate Direct to IP appeared first on Unit 42.

本文提出 MAGIC，一种基于掩码图表示学习的自监督高级持续性威胁（APT）检测方法。现有基于数据起源图分析的 APT 检测方法存在三个主要缺陷：一是依赖包含攻击的数据和先验知识，难以应对未知攻击；二是无法充分提取起源图中丰富的上下文信息；三是计算开销和内存消耗过大，实际部署困难。MAGIC 通过掩码图表示学习对正常系统实体和行为进行建模，在起源图上执行高效的深度特征提取和结构抽象，从而在不依赖攻击样本的情况下学习正常行为模式。检测阶段，MAGIC 利用异常检测方法识别偏离正常模式的系统行为，支持系统实体级和批量日志级两种粒度的 APT 检测。此外，MAGIC 专门设计了模型自适应机制以应对概念漂移，提高在动态环境中的鲁棒性，适用于多种检测场景。作者在三个广泛使用的数据集（包含真实攻击和模拟攻击）上进行了评估，结果显示 MAGIC 在所有场景下均取得了有竞争力的检测效果，并且在性能开销上显著优于现有的最先进 APT 检测方法。该研究的核心贡献包括：提出一种灵活的自监督 APT 检测框架，无需攻击样本；利用掩码图表示学习捕获深层语义；支持多粒度检测和概念漂移适应；在多个数据集上验证了有效性和高效性。适合安全研究人员、SOC 分析师以及对 APT 检测和溯源分析感兴趣的从业者阅读。

Explore how passkey implementation gaps undermine security when relying parties fail to validate the User Verified flag, reducing MFA to a single factor. The post Pass the Passkey: A Novel Attack Surface in Passwordless Authentication appeared first on Unit 42.

Now Live: The CrowdStrike 2026 Financial Services Threat Landscape Report

Storm-2945, a sub-cluster of the Russian threat actor Midnight Blizzard, has been observed compromising the sign-in portals of hospitality-related organizations such as hotels since May 2026 in order to deliver malware to travelers and steal credentials in an operation we call CaptiveCrunch. The post CaptiveCrunch: Midnight Blizzard targets travelers worldwide for malware delivery and credential t

Analysis of XCSSET v40 reveals a macOS malware targeting developers via Xcode. Unit 42 used advanced pattern matching and AI to decode its logic. The post The Xcode Assassin Returns: A Deep Dive Into the Latest XCSSET Version appeared first on Unit 42.

Falcon Next-Gen SIEM Supports Third-Party EDR Tools, Starting with Microsoft Defender

CrowdStrike Named a Leader in the First-Ever Gartner® Magic Quadrant™ for Cyberthreat Intelligence Technologies

Falcon AIDR Detects Threats at the Prompt Layer in Kubernetes AI Applications

Denying the Worm: Detecting SANDWORM_MODE and the Emerging Class of AI Toolchain Supply Chain AttacksJul 21, 2026

CrowdStrike Joins the Open Secure AI Alliance to Advance AI Safety and SecurityJul 27, 2026

CrowdStrike Falcon Platform Helps Meet U.S. Government Mandates for CISA BOD-26-04Jul 22, 2026

Learn how better questions, trusted AI, and human judgment help security leaders make confident decisions and build resilient systems. The post ​​Better security starts with better questions appeared first on Microsoft Security Blog.

The physics of cybersecurity are changing. Introducing security's new cyber stack: Project Perception. The post Rethinking security for the age of AI appeared first on Microsoft Security Blog.

Microsoft's External Red Team Alliance (EXTRA) is a global AI security initiative designed to advance AI safety research and red teaming. By partnering with universities, researchers, and regional experts, EXTRA helps identify emerging AI risks, improve security testing, and strengthen the resilience of frontier AI systems. The post Enhancing AI security through global AI red teaming appeared firs

企业网络持续面临高级持续性威胁（APT）的攻击，攻击者利用软件漏洞逐步渗透关键资产。随着披露的漏洞数量增长，资源受限的组织必须优先修补哪些漏洞。现有的漏洞优先级标准（如CVSS）对每个漏洞独立评分，无法评估修补策略在对抗随时间在网络中推进的攻击者时的实际效果。先前的模拟工具采用强化学习（RL）模拟攻击活动，但要么忽略了漏洞管理（即攻击者不受防御阻碍），要么依赖与真实威胁数据脱节的合成网络，因此无法评估策略对抗真实攻击者的表现。为填补这一空白，本文提出了VulnGym，一个用于评估漏洞管理策略的仿真工具。VulnGym模拟一个由RL训练的攻击者，其行为基于真实的APT配置文件（如攻击模式、速度、目标选择），同时防御者执行可配置的修补策略（如基于CVSS分数、资产重要性等）。两者在一个共享且持续演化的网络表示上行动，攻击者的进展直接受防御者修补活动的影响，从而能够对给定策略进行压力测试。实验基于真实世界的漏洞数据（如CVE）和两个APT案例（例如APT29、APT41等，摘要未明确但提及两个APT），结果显示漏洞管理必须根据组织环境、对手行为、网络拓扑和资产关键性进行定制化调整。该工具可帮助安全团队在部署前比较不同修补策略的效果，优化资源分配。

Falcon Next-Gen SIEM Simplifies Onboarding with Sensor-Native Log Collection

AIDR: How CrowdStrike Is Defining the Next Era of CybersecurityJul 15, 2026

CrowdStrike Falcon Platform Helps Meet U.S. Government Mandates for CISA BOD-26-04Jul 22, 2026

In the second quarter of 2026, the continuing effects of Microsoft’s disruption of the Tycoon2FA phishing platform contributed to sustained declines in several major phishing techniques, while threat actors expanded into Teams-based social engineering and employed increasingly automated and multi-stage attack chains. The post Email threat landscape: Q2 2026 trends and insights appeared first on Mi

Unit 42 details a Russian cyberespionage campaign targeting Zimbra webmail servers using JavaScript injection to steal credentials. The post Russian Global Webmail Espionage appeared first on Unit 42.

July 2026 Patch Tuesday: Microsoft Patches 622 Vulnerabilities Including Two Exploited Zero-DaysJul 14, 2026

本论文提出了一种名为 CAPTAIN（Context-Augmented Perplexity-based Threat Activity log detectIoN）的 APT 检测方法。研究背景是高级持续性威胁（APT）检测的难点在于大规模日志中仅有极小部分事件是恶意的，传统方法依赖大量人工标注和复杂的预处理管道，工程成本高。CAPTAIN 利用预训练的语言模型，通过最小化领域无关的预处理，基于困惑度（perplexity）对日志条目进行评分。该方法的核心创新在于引入上下文增强机制：使用编码器模型和 Q-Former 风格的桥接结构对近期历史日志进行编码，生成紧凑的上下文令牌，注入到解码器输入中，使困惑度评分能够反映时间上下文信息。此外，CAPTAIN 还通过平滑滤波器对困惑度时间序列进行稳定化处理。在多个 APT 基准测试上，CAPTAIN 与强基线方法性能相当，且对非精细化预处理输入具有鲁棒性，从而显著降低了日志预处理的发展与运维成本。该工作表明，无需复杂的数据清洗即可实现有效的 APT 检测，为安全运营团队提供了一种轻量级、可扩展的解决方案。

Our collaboration with AXA XL brings Microsoft Incident Response services directly to cyber insurance policyholders, helping organizations coordinate technical, business, and insurance decisions. The post Real world incident response: Microsoft and AXA XL strengthen cyber resilience appeared first on Microsoft Security Blog.

The Architecture of Agentic Defense: Inside the Falcon Platform

Why AI Governance Without Guardrails Is TheaterJul 09, 2026

本文首次从工业界视角系统评估了基于溯源的端点检测与响应（P-EDR）系统的有效性与局限性。研究通过一对一的专家访谈、在线问卷调查、相关文献调研以及系统性的测量实验四部分展开。结果显示，所有工业界专家均认为P-EDR系统比传统EDR更有效，但普遍担忧其运营成本。研究进一步揭示了学术界与工业界之间的三大鸿沟：（1）忽视客户端开销；（2）告警分类成本与解释成本不平衡；（3）服务端内存消耗过高。论文提供了P-EDR系统有效性的客观数据，并指出了工业界部署所需的关键改进方向。适合安全运维团队、EDR产品开发者和APT防御研究人员阅读。

Join Microsoft Security at Black Hat USA 2026 for supply chain research, hands-on security experiences, expert conversations, and our reception. The post Microsoft at Black Hat USA 2026: Defending trust in the age of AI and supply chain attacks appeared first on Microsoft Security Blog.

A technical analysis of three chained zero-day vulnerabilities in Siemens ROX II OT switches that allow privilege escalation and persistent root access. The post Three Steps to the Terminal: A Siemens ROX II Zero-Day Trilogy appeared first on Unit 42.

From late April 2026 to mid-June 2026, Microsoft Defender Experts observed increased ACR Stealer activity across customer environments. These campaigns are successfully using ClickFix lures to steal browser credentials, authentication tokens, and sensitive documents from enterprise environments. The post ACR Stealer: Two observed intrusion chains amid increased threat activity appeared first on Mi

Explore Unit 42's perspectives on AI's impact on cybersecurity, including key updates since the 2026 Incident Response Report. The post AI, Automation and Attacks: Unpacking the Unit 42 2026 Global Incident Response Report appeared first on Unit 42.

As AI agents become more autonomous, strong identity, access, and auditing controls are critical to keeping them secure. The post Least privilege for AI agents: Identity, access, and tool binding appeared first on Microsoft Security Blog.

CrowdStrike Uncovers New Prompt Injection TechniquesJul 07, 2026

Threat actors compromised AsyncAPI packages and weaponized trusted CI/CD workflows to distribute malware through npm. This analysis breaks down the attack chain, payload delivery, and recommended defenses. The post Unpacking the AsyncAPI npm supply chain compromise and import-time payload delivery appeared first on Microsoft Security Blog.

Palo Alto Networks Unit 42 团队发布了关于 npm 生态系统威胁态势的更新分析报告。报告指出，自 Shai Hulud 事件后，npm 供应链攻击持续演进，出现了可蠕虫化的恶意软件、CI/CD 持久化机制以及多阶段攻击等新型威胁。攻击者利用 npm 包的广泛分发特性，通过恶意包注入、依赖混淆、typosquatting 等手段渗透开发环境，进而横向移动至生产系统。报告重点分析了 CI/CD 管道中的持久化技术，攻击者可在构建过程中植入后门，导致每次部署都携带恶意代码。此外，蠕虫化恶意软件能够自动感染相关联的包，引发连锁反应。尽管报告未给出具体的攻击组织、恶意软件家族或 CVE 编号，但提供了详细的攻击面分析和缓解措施，帮助安全团队理解当前 npm 威胁格局并制定防御策略。目前尚未发现大规模在野利用的证据，但攻击手法日益复杂，开发者和安全团队需保持警惕。

Security teams have never had more visibility, yet rarely have they felt more uncertain. Signal pours in from endpoints, identities, cloud workloads, and a sprawling mix of third-party tools. The post Turning threat intelligence into decisive action with Defender Experts appeared first on Microsoft Security Blog.

TuxBot v3 Evolution, an IoT botnet framework built with LLMs. Read our analysis of its cross-compiled binaries, C2 architecture and bugs. The post TuxBot v3: Inside an IoT Botnet Framework With LLM-Assisted Development appeared first on Unit 42.

Microsoft Threat Intelligence identified threat actor activity with overlapping tradecraft commonly associated with ShinyHunters, including voice phishing (vishing), supply-chain compromise, and misconfigured guest access targeting SaaS-based applications. The post Defending SaaS-based applications against ShinyHunters OAuth abuse appeared first on Microsoft Security Blog.

Microsoft Entra ID makes passkeys the default sign-in experience and introduces a new model for SMS and voice authentication. Read about how to prepare. The post Microsoft Entra ID security updates: Passkeys are the default authentication method in Entra ID appeared first on Microsoft Security Blog.

Unit 42 explores The Gentlemen ransomware operations, revealing the affiliate model driving its rapid growth. Learn more here. The post No Manners Here: The Ruthless Rise of The Gentlemen Ransomware appeared first on Unit 42.

Microsoft’s latest Secure Future Initiative report outlines progress on secure foundations, AI-powered defense, and future-ready cybersecurity. The post Securing our future: July 2026 progress report on Microsoft’s Secure Future Initiative appeared first on Microsoft Security Blog.

GigaWiper is a destructive backdoor that combines multiple wiping and ransomware-like capabilities into a single operational platform. This blog analyzes how the malware incorporates code from several previously separate malware families and provides guidance to help defenders detect and defend against similar threats. The post GigaWiper: Anatomy of a destructive backdoor assembled from multiple m

How to Stop AI-Driven Data Loss

微软于2026年7月8日发布博文，介绍其安全未来计划（Secure Future Initiative, SFI）如何利用AI速度主动加固云服务。SFI将威胁知识、运营框架与安全需求相结合，定义了完善云服务的防御标准。文章强调，满足这些标准需要持续以AI速度对在线服务进行评估。该计划旨在提前发现和缓解潜在威胁，而非事后响应。博文未提及具体攻击活动或漏洞，重点在于微软自身的安全架构和实践。

A cybercrime campaign combined a loader-as-a-service framework and DLL sideloading via a Go-compiled fake MpClient.dll, a novel evasion layer combination. The post Vidar Stealer Unmasked: Code Signing Abuse, Go Loaders and File Inflation appeared first on Unit 42.

4 Ways Businesses Use CrowdStrike Charlotte AI to Transform Security Operations

该文章基于Frost & Sullivan发布的2025年云安全态势管理（CSPM）Frost Radar™报告，提炼了五项关键洞察。报告指出，CSPM正从传统的“时间点合规”工具向“持续风险管理”平台演进。核心变化包括：1）CSPM不再仅检查配置错误，而是集成实时威胁情报，主动发现攻击路径；2）机器学习模型用于异常行为检测，减少误报；3）跨云环境（AWS、Azure、GCP）的统一视图成为标配；4）自动化修复能力（如自动回滚、策略实施）显著提升；5）与DevOps流程的深度集成，支持“安全即代码”。文章强调，现代CSPM需要同时处理基础设施即代码（IaC）的静态分析和运行时动态风险。虽然文章未披露具体漏洞或攻击事件，但这为安全团队选择或优化云安全工具提供了战略方向。附录中的Frost Radar排名显示微软、Palo Alto Networks、Check Point等厂商处于领导者象限。整体内容属于行业趋势分析，不涉及恶意活动。

A look inside the reverse-engineering journey of building the first RDP client outside of Windows to support WebAuthn redirection. The post How We Added WebAuthn to a Browser-Based RDP Client appeared first on Unit 42.

Frost & Sullivan names Microsoft a leader as cloud and application security converge into unified, runtime risk reduction. The post Microsoft named a leader in the Frost Radar for cloud and application runtime security appeared first on Microsoft Security Blog.

CrowdStrike Named a Leader in 2026 Gartner® Magic Quadrant™ for Endpoint Protection for Seventh Consecutive Time

Attackers can exploit LLM domain hallucinations through phantom squatting to target supply chains. Read the analysis to learn more. The post Phantom Squatting: AI-Hallucinated Domains as a Software Supply Chain Vector appeared first on Unit 42.

We’re accelerating quantum-safe readiness—and sharing what organizations can do now to transition earlier and with confidence. The post Accelerating the quantum-safe timeline appeared first on Microsoft Security Blog.

This month’s updates help security and IT teams strengthen identity and multicloud foundations, protect data wherever it lives, and secure the developer workflows powering AI innovation. The post ​​What’s new in Microsoft Security: June 2026 appeared first on Microsoft Security Blog.

MCP tool poisoning turns trusted AI agents into a control plane for data loss. Learn how threat actors manipulate tool descriptions to trigger unauthorized actions, and how to detect, contain, and prevent it. The post Securing AI agents: When AI tools move from reading to acting appeared first on Microsoft Security Blog.

CrowdStrike Named a Leader in Frost & Sullivan 2026 Radar for Cloud-Native Application Protection Platforms

A malicious Chromium-based extension that spoofs the AI-powered answer engine Perplexity AI redirects browser search traffic using MV3 APIs and intermediary infrastructure. The post Chromium extension uses AI‑related branding to redirect browser search appeared first on Microsoft Security Blog.

Your inbox is an identity system all of its own: whoever owns it may own a lot more

本文通过半结构化访谈15名不同角色和专业背景的安全从业者，探讨了高级持续性威胁（APT）分析、归因及面临的挑战。研究发现，从业者在APT归因中采用三层方法，每层有各自目标和挑战。他们通常更关注理解对手的战术、技术和程序（TTP）及动机，而非确定具体攻击实体。现有工具和流程的主要问题包括无法处理多样复杂的数据，以及内部和外部协作的困难。基于这些发现，作者提出了四项改进归因方法的建议，并讨论了这些改进如何应对已识别的挑战。该研究填补了对安全从业者实际感知和挑战理解的空白，为未来APT分析工具和流程设计提供了重要参考。

该论文聚焦于从系统活动图中检索已知高级持续性威胁（APT）活动的任务。在现实运维环境中，系统活动图（节点代表MITRE ATT&CK技术，边表示时间或资源级别的关联）常因检测不完整、技术误分类以及良性行为引入的结构伪影而包含噪声。传统基于精确图匹配的方法在噪声环境下鲁棒性差。为此，论文将问题形式化为已知APT查询图与含噪声、部分观测的技术图之间的近似子图匹配。作者提出了一种基于嵌入的初步检索方法，通过将图结构转换为低维向量表示，在向量空间中进行相似度搜索，以容忍噪声和缺失边。该方法旨在为实际环境中已知APT活动的检索提供鲁棒且实用的框架。实验部分（摘要未详述）应验证该方法在合成噪声数据上的有效性。该工作适合安全分析师、威胁情报研究员及图分析在网络安全应用中的开发者阅读。

Your business may be small, but its attack surface is anything but. Readiness is the first step to resilience.

Microsoft Threat Intelligence identified an active multi-stage intrusion campaign targeting hospitality organizations in Europe and Asia. The campaign uses photo-themed ZIP archives and fake image shortcut files to deliver a persistent Node.js implant and evade detection. The post Photo ZIP campaign targeting hospitality industry delivers Node.js implant for persistent access appeared first on Mic

Government entities and critical infrastructure were targeted for espionage in SE Asia by attackers using a hybrid toolkit, including custom TinyRCT backdoor. The post CL-STA-1062 Targets Southeast Asian Governments and Critical Infrastructure appeared first on Unit 42.

Microsoft named a Leader in the Forrester Wave™: Endpoint Management Platforms, Q2 2026, with the highest scores in the current offering and strategy categories. The post Microsoft a Leader in The Forrester Wave™ for Endpoint Management Platforms appeared first on Microsoft Security Blog.

ESET Research analyzes Gamaredon’s new toolset and the group’s growing reliance on legitimate online services to hide its C&C infrastructure and exfiltrate stolen data

Learn how CNAPP platforms are helping organizations prioritize exploitable risks, reduce exposure, and operationalize security across the application lifecycle. The post CNAPP evolution: How Microsoft aligns with leading cloud risk management platforms appeared first on Microsoft Security Blog.

ESET researchers assisted in the global disruption of the Amadey botnet and Stealc infostealer, providing technical analysis, infrastructure tracking, and affiliate-level insights

On June 24, 2026, Microsoft’s Digital Crimes Unit (DCU) facilitated the takedown, suspension, and blocking of domains that formed the backbone of the StealC and Amadey infrastructure. This blog is a technical breakdown of StealC and Amadey. The post StealC and Amadey: Breaking down infostealers and the cybercrime services that deliver them appeared first on Microsoft Security Blog.

Unit 42's analysis of ClawHub revealed evasive malicious skills bypassing automated scanners to deploy infostealers and execute agentic financial fraud. The post OpenClaw’s Skill Marketplace and the Emerging AI Supply Chain Threat appeared first on Unit 42.

CrowdStrike Named a Leader in Identity Threat Detection and Response

CrowdStrike Expands Real-Time Cloud Detection and Response to Google Cloud

Falcon Exposure Management Now Available for Third-Party EnvironmentsJun 16, 2026

After Executive Order 14409: Next Steps for Securing AIJun 17, 2026

Unit 42 research details how attackers could exploit global name uniqueness in bucket hijacking to redirect cloud data streams across major CSPs. The post The Global Namespace Risk: Universal Bucket Hijacking Technique for Cloud Data Exfiltration appeared first on Unit 42.

What happens when threat actors target what AI remembers? Microsoft breaks down the risks and the defenses. The post Guarding AI memory appeared first on Microsoft Security Blog.

Ransomware case reveals two parallel threat actors, blending tactics and evasion—showing why isolated signals can often miss modern, overlapping cyberattacks. The post One intrusion, two cyberattackers: Uncovering parallel threat activity appeared first on Microsoft Security Blog.

AutoJack is a novel exploit chain showing how a single malicious webpage can turn an AI browsing agent into a remote code execution vector on the host machine. By abusing trust in localhost, missing authentication, and unsafe parameter handling, attackers can trigger arbitrary process execution through AutoGen Studio’s MCP WebSocket. The research highlights a broader pattern - when agents can brow

New Forrester Total Economic Impact™ study shows Microsoft Security consolidation delivers ROI, lowers risk, and prepares organizations to secure AI. The post New Forrester study shows customers who unified with Microsoft Security benefited from 124% ROI appeared first on Microsoft Security Blog.

ESET Research shares the results of a months-long investigation into the suite of EDR killers maintained by the RaaS gang Gentlemen