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In this article DNS hijacking attack chain: From compromised devices to AiTM and other follow-on activity Mitigation and protection guidance Microsoft Defender detection and hunting guidance Executive summary Forest Blizzard, a threat actor linked to the Russian military, has been compromising insecure home and small-office internet equipment like routers, then modifying their settings in ways that turn them into part of the actor’s malicious infrastructure. The threat actor then hides behind this legitimate but compromised infrastructure to spy on additional targets or conduct follow-on attacks. Microsoft Threat Intelligence is sharing information on this campaign to increase awareness of the risks associated with insecure home and small-office internet routing devices and give users and organizations tools to mitigate, detect, and hunt for these threats where they might be impacted. Since at least August 2025, the Russian military intelligence actor Forest Blizzard , and its sub-group tracked as Storm-2754, has conducted a large-scale exploitation of vulnerable small office/home office (SOHO) devices to hijack Domain Name System (DNS) requests and facilitate the collection of network traffic. For nation-state actors like Forest Blizzard, DNS hijacking enables persistent, passive visibility and reconnaissance at scale. By compromising edge devices that are upstream of larger targets, threat actors can take advantage of less closely monitored or managed assets to pivot into enterprise environments. Microsoft Threat Intelligence has identified over 200 organizations and 5,000 consumer devices impacted by Forest Blizzard’s malicious DNS infrastructure; telemetry did not indicate compromise of Microsoft-owned assets or services. Forest Blizzard, which primarily collects intelligence in support of Russian government foreign policy initiatives, has also leveraged its DNS hijacking activity to support post-compromise adversary-in-the-middle (AiTM) attacks on Transport Layer Security (TLS) connections against Microsoft Outlook on the web domains. This activity enables the interception of cloud-hosted content, impacting numerous sectors including government, information technology (IT), telecommunications, and energy—all usual targets for this actor. While the number of organizations specifically targeted for TLS AiTM is only a subset of the networks with vulnerable SOHO devices, Microsoft Threat Intelligence assesses that the threat actor’s broad access could enable larger-scale AiTM attacks, which might include active traffic interception. Targeting SOHO devices is not a new tactic, technique, or procedure (TTP) for Russian military intelligence actors, but this is the first time Microsoft has observed Forest Blizzard using DNS hijacking at scale to support AiTM of TLS connections after exploiting edge devices. In this blog, we share our analysis of the TTPs used by Forest Blizzard in this campaign to illustrate how threat actors leverage this at

Fortinet has updated its FortiClient EMS product after zero-day attacks surfaced

Microsoft has resolved a known issue that was preventing some Classic Outlook users from sending emails via Outlook.com. [...]

In this article Attack chain overview Mitigation and protection guidance Indicators of compromise (IOC) References Learn more Microsoft Defender Security Research has observed a widespread phishing campaign leveraging the Device Code Authentication flow to compromise organizational accounts at scale. While traditional device code attacks are typically narrow in scope, this campaign demonstrated a higher success rate, driven by automation and dynamic code generation that circumvented the standard 15-minute expiration window for device codes. This activity aligns with the emergence of EvilToken, a Phishing-as-a-Service (PhaaS) toolkit identified as a key driver of large-scale device code abuse. This campaign is distinct because it moves away from static, manual scripts toward an AI-driven infrastructure and multiple automations end-to-end. This activity marks a significant escalation in threat actor sophistication since the Storm-2372 device code phishing campaign observed in February 2025 . Advanced Backend Automation: Threat actors used automation platforms like Railway.com to spin up thousands of unique, short-lived polling nodes. This approach allowed them to deploy complex backend logic (Node.js), which bypassed traditional signature-based or pattern-based detection. This infrastructure was leveraged in the attack end-to-end from generating dynamic device codes to post compromise activities. Hyper-personalized lures: Generative AI was used to create targeted phishing emails aligned to the victim’s role, including themes such as RFPs, invoices, and manufacturing workflows, increasing the likelihood of user interaction. Dynamic Code Generation: To bypass the 15-minute expiration window for device codes, threat actors triggered code generation at the moment the user interacted with the phishing link, ensuring the authentication flow remained valid. Reconnaissance and Persistence: Although many accounts were compromised, follow-on activity focused on a subset of high-value targets. Threat actors used automated enrichment techniques, including analysis of public profiles and corporate directories, to identify individuals in financial or executive roles. This enabled rapid reconnaissance, mapping of permissions, and creation of malicious inbox rules for persistence and data exfiltration. Once authentication tokens were obtained, threat actors focused on post-compromise activity designed to maintain access and extract data. Stolen tokens were used for email exfiltration and persistence, often through the creation of malicious inbox rules that redirected or concealed communications. In parallel, threat actors conducted Microsoft Graph reconnaissance to map organizational structure and permissions, enabling continued access and potential lateral movement while tokens remained valid. Attack chain overview Device Code Authentication is a legitimate OAuth flow designed for devices with limited interfaces, such as smart TVs or printers, that cannot support

The U.S. Cybersecurity and Infrastructure Security Agency (CISA) ordered federal agencies to secure FortiClient Enterprise Management Server (EMS) instances against an actively exploited vulnerability by Friday. [...]

Fortinet has released an emergency weekend security update for a new critical FortiClient Enterprise Management Server (EMS) vulnerability that is actively exploited in attacks. [...]

Fortinet has released out-of-band patches for a critical security flaw impacting FortiClient EMS that it said has been exploited in the wild. The vulnerability, tracked as CVE-2026-35616 (CVSS score: 9.1), has been described as a pre-authentication API access bypass leading to privilege escalation. "An improper access control vulnerability [CWE-284] in FortiClient EMS may allow an

Microsoft is investigating and working to resolve Exchange Online mailbox access issues that have intermittently affected Outlook mobile and macOS users for weeks. [...]

For the last year, one word has represented the conversation living at the intersection of AI and cybersecurity: speed. Speed matters, but it’s not the most important shift we are observing across the threat landscape today. Now, threat actors from nation states to cybercrime groups are embedding AI into how they plan, refine, and sustain cyberattacks. The objectives haven’t changed, but the tempo, iteration, and scale of generative AI enabled attacks are certainly upgrading them. Explore integrated security solutions with Microsoft Defender However, like defenders, there is typically a human-in-the-loop still powering these attacks, and not fully autonomous or agentic AI running campaigns. AI is reducing friction across the attack lifecycle; helping threat actors research faster, write better lures, vibe code malware, and triage stolen data. The security leaders I spoke with at RSAC™ 2026 Conference this week are prioritizing resources and strategy shifts to get ahead of this critical progression across the threat landscape. The operational reality: Embedded, not emerging The scale of what we are tracking makes the scope impossible to dismiss. Threat activity spans every region. The United States alone represents nearly 25% of observed activity, followed by the United Kingdom, Israel, and Germany. That volume reflects economic and geopolitical realities. 1 But the bigger shift is not geographic, it’s operational. Threat actors are embedding AI into how they work across reconnaissance, malware development, and post-compromise operations. Objectives like credential theft, financial gain, and espionage might look familiar, but the precision, persistence, and scale behind them have changed. Email is still the fastest inroad Email remains the fastest and cheapest path to initial access. What has changed is the level of refinement that AI enables in crafting the message that gets someone to click. When AI is embedded into phishing operations, we are seeing click-through rates reach 54%, compared to roughly 12% for more traditional campaigns. That is a 450% increase in effectiveness . That’s not the result of increased volume, but the result of improved precision. AI is helping threat actors localize content and adapt messaging to specific roles, reducing the friction in crafting a lure that converts into access. When you combine that improved effectiveness with infrastructure designed to bypass multifactor authentication (MFA), the result is phishing operations that are more resilient, more targeted, and significantly harder to defend at scale. A 450% increase in click-through rates changes the risk calculus for every organization. It also signals that AI is not just being used to do more of the same, it is being used to do it better. Tycoon2FA: What industrial-scale cybercrime looks like Tycoon2FA is an example of how the actor we track as Storm-1747 shifted toward refinement and resilience. Understanding how it operated teaches us where threats migh

In this article Cookie-controlled execution behavior Observed variants of cookie-controlled PHP web shells Mitigation and protection guidance Microsoft Defender XDR detections Microsoft Security Copilot prompts Microsoft Defender XDR threat analytics MITRE ATT CK™ Techniques observed References Learn more Threat actors are increasingly abusing HTTP cookies as a control channel for PHP-based webshells on Linux servers. Instead of exposing command execution through URL parameters or request bodies, these webshells rely on threat actor-supplied cookie values to gate execution, pass instructions, and activate malicious functionality. This approach reduces visibility by allowing malicious code to remain dormant during normal application behavior and execute only when specific cookie conditions are met. This technique has been observed across multiple execution contexts, including web requests, scheduled tasks, and trusted background workers. The consistent use of cookies as a control mechanism suggests reuse of established webshell tradecraft. By shifting control logic into cookies, threat actors enable persistent post-compromise access that can evade many traditional inspection and logging controls. Cookie-controlled execution behavior Across the activity analyzed, HTTP cookies acted as the primary trigger for malicious execution. Instead of exposing functionality through visible URL parameters or request bodies, the webshell logic remained dormant unless specific cookie values were present. Only when those conditions were satisfied did the script reconstruct and execute threat actor–controlled behavior. Threat actors likely prefer this approach because cookies blend into normal web traffic and often receive less scrutiny than request paths or payloads. In PHP, cookie values are immediately available at runtime, for example through the $_COOKIE superglobal, allowing malicious code to consume attacker-supplied input without additional parsing. By shifting execution control into cookies, the webshell can remain hidden in normal traffic, activating only during deliberate interactions. This reduces routine logging and inspection visibility while enabling persistent access without frequent changes to files on disk. Observed variants of cookie-controlled PHP web shells Although the core technique remained consistent across incidents, the PHP implementations varied in structure and complexity. The following examples illustrate how attackers adapted the same cookie-controlled execution model across different environments. Loader with execution gating and layered obfuscation One observed implementation introduced an additional execution gate before processing any cookie input. The loader first evaluated request context and reconstructed core PHP functions dynamically using arithmetic operations and string manipulation. Sensitive function names were intentionally absent in cleartext, significantly reducing obvious indicators and complicating pattern-based dete

Cisco has released updates to address a critical security flaw in the Integrated Management Controller (IMC) that, if successfully exploited, could allow an unauthenticated, remote attacker to bypass authentication and gain access to the system with elevated privileges. The vulnerability, tracked as CVE-2026-20093, carries a CVSS score of 9.8 out of a maximum of 10.0. "This

iOS/iPadOS 18.7.7 updates expanded to protect older devices from DarkSword web exploit kit

Apple on Wednesday expanded the availability of iOS 18.7.7 and iPadOS 18.7.7 to a broader range of devices to protect users from the risk posed by a recently disclosed exploit kit known as DarkSword. "We enabled the availability of iOS 18.7.7 for more devices on April 1, 2026, so users with Automatic Updates turned on can automatically receive important security

Apple has now made it possible for more iPhones still running iOS 18 to receive security updates that protect against the actively exploited DarkSword exploit kit. [...]

Apple pushes rare iOS 18 security patch to protect devices at risk from the DarkSword exploit, urging users to update or move to iOS 26 for stronger protection.

In this article Analysis of the attack Mitigation and protection guidance Microsoft Defender detections Indicators of compromise Hunting queries On March 31, 2026, two new npm packages for updated versions of Axios, a popular HTTP client for JavaScript that simplifies making HTTP requests to a REST endpoint with over 70 million weekly downloads, were identified as malicious. These versions (1.14.1 and 0.30.4) were injected with a malicious dependency to download payloads from known actor command and control (C2). Microsoft Threat Intelligence has attributed this infrastructure and the Axios npm compromise to Sapphire Sleet, a North Korean state actor. Following successful connection to the malicious C2, a second-stage remote access trojan (RAT) payload was automatically deployed based on the operating system of the compromised device, including macOS, Windows, and Linux. This activity follows the pattern of recent high-profile supply chain attacks , where other adversaries poison widely adopted open-source frameworks and their distribution channels to achieve broad downstream impact. Users who have installed Axios version 1.14.1 or 0.30.4 should rotate their secrets and credentials immediately and downgrade to a safe version (1.14.0 or 0.30.3). Users should also follow the mitigation and protection guidance provided in this blog, including disabling auto-updates for Axios npm packages, since the malicious payload includes a hook that will continue to attempt to update. This blog shares Microsoft Threat Intelligence’s findings from our analysis, Microsoft Defender detections in place that alerted and protected our customers, additional protections we have implemented in our products to detect and block malicious components, and suggested mitigations for organizations to prevent further compromise. Analysis of the attack On March 31, 2026, two malicious versions of Axios npm packages were released. These packages connected to a known malicious domain (C2) owned by Sapphire Sleet to retrieve a second-stage remote access trojan (RAT). Since Axios packages are commonly auto-updated, any projects with Axios versions higher than axios@^1.14.0 or axios@^0.30.0 connected to this Sapphire Sleet C2 upon installation and downloaded second-stage malware. Windows, macOS, and Linux systems are all targeted with platform-specific payloads. Microsoft Threat Intelligence has determined the account that created the plain-crypto-js package is associated with Sapphire Sleet infrastructure. That account has been disabled. Silent install-time code execution using dependency insertion The updated versions of Axios inject [email protected] , a fake runtime dependency that executes automatically through post-install with no user interaction required. The trusted package’s application logic is not modified; instead, the threat actor added a dependency that is never imported by the package’s runtime code but only exists to trigger an install-time script to download the

The security update protects a raft of older iPhones and iPads from attacks linked to leaked hacking tools called DarkSword.

This is the fifth update to the TeamPCP supply chain campaign threat intelligence report, When the Security Scanner Became the Weapon (v3.0, March 25, 2026). Update 004 covered developments through March 30, including the Databricks investigation, dual ransomware operations, and AstraZeneca data release. This update consolidates two days of intelligence through April 1, 2026. HIGH: Mercor AI Confirms Breach Tied to LiteLLM Supply Chain Compromise - First Official Victim Disclosure AI recruiting startup Mercor has publicly confirmed it was breached as a direct consequence of the LiteLLM supply chain compromise, making it the first organization to officially acknowledge being victimized through the TeamPCP campaign. TechCrunch reported on March 31 that LAPSUS$ claims to have exfiltrated approximately 4TB of data, including 939GB of source code, a 211GB user database, and 3TB of video interviews and identity verification documents (passports). Initial access was reportedly via a compromised Tailscale VPN credential. Mercor stated it was one of thousands of companies affected by the LiteLLM compromise. The nature of the claimed exfiltrated data -- which includes biometric identity verification materials -- raises significant privacy and regulatory implications under GDPR, CCPA, and potentially HIPAA depending on the contents. This is operationally significant because it moves the campaign's downstream impact from theoretical to confirmed. Prior victim claims (AstraZeneca, Databricks) remain unconfirmed by the named organizations. Mercor's public acknowledgment validates what analysts have assessed since Update 002: the credential trove harvested during the supply chain phase is being actively exploited for data theft and extortion. Recommended action: Organizations that used LiteLLM v1.82.7 or v1.82.8 should treat this as confirmation that credential exploitation is actively underway. If you have not completed credential rotation, the Mercor disclosure demonstrates the consequence of delay. VPN credentials, cloud access tokens, and API keys accessible in compromised environments should be prioritized for rotation. HIGH: Wiz Documents TeamPCP Post-Compromise AWS and Cloud Enumeration in the Wild SecurityWeek reported on March 31 that Wiz's Cloud Incident Response Team (CIRT) has published detailed findings on TeamPCP's post-compromise cloud operations in Tracking TeamPCP: Investigating Post-Compromise Attacks Seen in the Wild . This is the first detailed public documentation of what TeamPCP does after obtaining stolen credentials. Key findings from the Wiz CIRT investigation: Credential validation via TruffleHog: TeamPCP uses the open-source secret scanning tool TruffleHog to programmatically verify that stolen AWS access keys, Azure application secrets, and SaaS tokens are still valid and in use. 24-hour operational tempo: Within 24 hours of validating stolen secrets, the group transitions to discovery operations in compromised AWS en

Microsoft released an emergency update to fix the March 2026 KB5079391 non-security preview update, which was pulled over the weekend due to installation issues. [...]

What to know about the era of AI The first thing to know is that AI isn’t magic The best way to think about how to effectively use and secure a modern AI system is to imagine it like a very new, very junior person. It’s very smart and eager to help but can also be extremely unintelligent. Like a junior person, it works at its best when it’s given clear, fairly specific goals, and the vaguer its instructions, the more likely it is to misinterpret them. If you’re giving it the ability to do anything consequential, think about how you would give that responsibility to someone very new: at what point would you want them to stop and check with you before continuing, and what information would you want them to show you so that you could tell they were on track? Apply that same kind of human reasoning to AI and you will get best results. Microsoft Deputy CISOs To hear more from Microsoft Deputy CISOs, check out the OCISO blog series . To stay on top of important security industry updates, explore resources specifically designed for CISOs, and learn best practices for improving your organization’s security posture, join the Microsoft CISO Digest distribution list . At its core, a language model is really a role-playing engine that tries to understand what kind of conversation you want to have and continues it. If you ask it a medical question in the way a doctor would ask another doctor, you’ll get a very different answer than if you asked it the question the way a patient would. The more it’s in the headspace of “I am a serious professional working with other serious professionals,” the more professional its responses get. This also means that AI is most helpful when working together with humans who understand their fields and it is most unpredictable when you ask it about something you don’t understand at all. The second thing to know is that AI is software AI is essentially a stateless piece of software running in your environment. Unless the code wrapping does so explicitly, it doesn’t store your data in a log somewhere or use it to train AI models for new uses. It doesn’t learn dynamically. It doesn’t consume your data in new ways. Often, AI works similarly to the way most other software works: in the ways you expect and the ways you’re used to, with the same security requirements and implications. The basic security concerns—like data leakage or access—are the same security concerns we’re all already aware of and dealing with for other software. An AI agent or chat experience needs to be running with an identity and with permissions, and you should follow the same rules of access control that you’re used to. Assign the agent a distinct identity that suits the use case, whether as a service identity or one derived from the user, and ensure its access is limited to only what is necessary to perform its function. Never rely on AI to make access control decisions. Those decisions should always be made by deterministic, non-AI mechanisms. You should sim