GopherWhisper: A burrow full of malware
ESET Research has discovered a new China-aligned APT group that we’ve named GopherWhisper, which targets Mongolian governmental institutions
WeLiveSecurity – Read More
ESET Research has discovered a new China-aligned APT group that we’ve named GopherWhisper, which targets Mongolian governmental institutions
WeLiveSecurity – Read More

Welcome to this week’s edition of the Threat Source newsletter.
If I haven’t said it in a newsletter before, I’ll say it now: If you want to be good at cybersecurity, be a forever student. Cultivating and feeding your desire to know how things work is one of the key ingredients to being a hacker. It’s not always about understanding the micro details, but the macro of how systems work. And not just computers or software or networking systems — those are ecosystems we’re usually quite familiar with — but what about economics? agriculture? material sciences? human behavior? music and art? Do any of those carry any value into this profession?
They damn sure do. Many, many times I have had to branch my technical research into domains that arbitrarily seem to provide no immediate value for technical problems. Learning how maritime insurance fraud works was interesting to me — and a short time later, led to cyber insurance and understanding how risk guides security investment in massive companies. Understanding international agriculture helped me research threat actor targeting and ransomware cartel victimology.
One of the topics I’ve been researching heavily lately is economics, specifically industrial organization. It’s a branch of economics that studies how companies structure production, how markets form around them, and how costs operate at scale. For me, the natural target of my curiosity was Ford Motor Company. Henry Ford didn’t invent the car or the assembly line, but he was darn sure able to build and scale car production in a way that set the standard for all others in that space to emulate. I’ve learned about fixed vs. variable costs, how artisans had their knowledge crystalized within the assembly line process, and how and how amortized costs drove down prices, allowing the Ford Model T to exceed 900,000 units annually by the early 1920s. By that time, more than half of the registered automobiles in the world were Fords. Not half of American cars, half of all cars on Earth.
So what? Well, what took Ford Motor Company 17 years to achieve in cost and ceiling reductions, the AI industry has done in 2.5 years. The rapid and massive influx of investments, fierce competition, and available compute has shown what industrial organization means in a world where AI now almost permeates everything we see and touch. What does this mean for AI replacing jobs? Are we the artisans who move to the frontier of security? What does this mean for enabling threat actors who can move up a step to threatening others with tools developed using an AI corpus already trained on security? There are lots of questions, and to be honest, the future isn’t clear here. One thing is for certain: We can look to the past to understand the future. Henry Ford said it best: “Progress happens when all the factors that make for it are ready, and then it is inevitable.”
As much as we tend to be myopic as security professionals and focus on our tradecraft, we are all part of a series of interconnected systems that lets humanity function. Learning those systems — their quirks, their limitations, and their vulnerabilities — makes you a better hacker. Stay curious, friends.
Cisco Talos Incident Response (Talos IR) is sharing Q1 2026 incident response trends. Phishing has officially reclaimed its crown as the top initial access vector. In a notable first, responders observed adversaries leveraging Softr, an AI-powered web development tool, to rapidly generate credential-harvesting pages. Meanwhile, actual ransomware deployments hit absolute zero this quarter thanks to swift mitigation by Talos IR, though pre-ransomware activity accounted for 18% of engagements this quarter.
The barrier to entry for cybercriminals is plummeting, and they are increasingly using our own tools against us. The use of AI platforms to spin up phishing infrastructure means even unsophisticated actors can launch high-speed, code-free attacks. Furthermore, threat actors are abusing legitimate developer tools like TruffleHog and native cloud APIs to quietly hunt for exposed secrets, making detection incredibly difficult for defenders already struggling with logging gaps.
It’s time to get back to basics and lock down your perimeter. Organizations must implement properly configured multi-factor authentication (MFA), specifically restricting self-service enrollment to stop attackers from registering new devices. Defenders also need to prioritize robust patch management and ensure centralized logging via a SIEM is in place so forensic evidence remains intact. Read the full blog for a deeper dive into this quarter’s trends and adversary tactics.
Third U.S. security expert admits helping ransomware gang
According to the Justice Department, Martino abused his role as a ransomware negotiator for five companies by providing the BlackCat/Alphv cybercrime group with information useful in negotiating a ransom payment. (SecurityWeek)
22 BRIDGE:BREAK flaws expose thousands of Lantronix and Silex serial-to-IP converters
Successful exploitation of the flaws could allow attackers to disrupt serial communications with field assets, conduct lateral movement, and tamper with sensor values or modify actuator behavior. (The Hacker News)
How hackers “trojan-horsed” QEMU virtual machines to bypass security and drop ransomware
In recent incidents, attackers used QEMU, an open-source machine emulator and virtualizer, to run hidden environments where malicious activity remained largely invisible to endpoint defenses and left minimal evidence on the host system. (TechRadar)
Mastodon says its flagship server was hit by a DDoS attack
The cyber attack targeting Mastodon comes days after Bluesky, another decentralized social network, resolved much of its days-long outagesfollowing a lengthy DDoS attack. (TechCrunch)
Exploits turn Windows Defender into attacker tool
Threat actors are using three publicly available proof-of-concept exploits (two are unpatched) to attack Microsoft Defender and turn the security platform’s primary cleanup and protection functions against organizations it is designed to protect. (Dark Reading)
Bad Apples: Weaponizing native macOS primitives for movement and execution
Talos documented several macOS living-off-the-land (LOTL) techniques, demonstrating that native pathways for movement and execution remain accessible to those who understand the underlying architecture.
AI phishing, fake CAPTCHA, and real-world cyber threat trends
The Talos team breaks down findings from Q1 2026 — including phishing returning as the top initial access vector, and how attackers are using AI tools to build credential harvesting campaigns in almost no time at all.
UAT-4356’s targeting of Cisco Firepower devices
UAT-4356 exploited n-day vulnerabilities (CVE-2025-20333 and CVE-2025-20362) to gain unauthorized access to vulnerable devices, where the threat actor deployed their custom-built backdoor dubbed “FIRESTARTER.”
SHA256: 9f1f11a708d393e0a4109ae189bc64f1f3e312653dcf317a2bd406f18ffcc507
MD5: 2915b3f8b703eb744fc54c81f4a9c67f
Talos Rep: https://talosintelligence.com/talos_file_reputation?s=9f1f11a708d393e0a4109ae189bc64f1f3e312653dcf317a2bd406f18ffcc507
Example Filename: VID001.exe
Detection Name: Win.Worm.Coinminer::1201
SHA256: 96fa6a7714670823c83099ea01d24d6d3ae8fef027f01a4ddac14f123b1c9974
MD5: aac3165ece2959f39ff98334618d10d9
Talos Rep: https://talosintelligence.com/talos_file_reputation?s=96fa6a7714670823c83099ea01d24d6d3ae8fef027f01a4ddac14f123b1c9974
Example Filename: d4aa3e7010220ad1b458fac17039c274_63_Exe.exe
Detection Name: W32.Injector:Gen.21ie.1201
SHA256: 90b1456cdbe6bc2779ea0b4736ed9a998a71ae37390331b6ba87e389a49d3d59
MD5: c2efb2dcacba6d3ccc175b6ce1b7ed0a
Talos Rep: https://talosintelligence.com/talos_file_reputation?s=90b1456cdbe6bc2779ea0b4736ed9a998a71ae37390331b6ba87e389a49d3d59
Example Filename: APQ9305.dll
Detection Name: Auto.90B145.282358.in02
SHA256: 5e6060df7e8114cb7b412260870efd1dc05979454bd907d8750c669ae6fcbcfe
MD5: a2cf85d22a54e26794cbc7be16840bb1
Talos Rep: https://talosintelligence.com/talos_file_reputation?s=5e6060df7e8114cb7b412260870efd1dc05979454bd907d8750c669ae6fcbcfe
Example Filename: a2cf85d22a54e26794cbc7be16840bb1.exe
Detection Name: W32.5E6060DF7E-100.SBX.TG
SHA256: 3c1dbc3f56e91cc79f0014850e773a7f12bbfef06680f08f883b2bf12873eccc
MD5: d749e0f8f2cd4e14178a787571534121
Talos Rep: https://talosintelligence.com/talos_file_reputation?s=3c1dbc3f56e91cc79f0014850e773a7f12bbfef06680f08f883b2bf12873eccc
Example Filename: KitchenCanvas_753447.exe
Detection Name: W32.3C1DBC3F56-90.SBX.TG
Cisco Talos Blog – Read More
In many countries, spring is the traditional time for filing income tax returns. These documents are a goldmine for bad actors because they contain a wealth of personal data, such as employment history, income, assets, bank account details — the list goes on. It’s no surprise that scammers ramp up their efforts around this time; the internet is currently crawling with fake websites designed to look exactly like government resources and tax authorities.
With deadlines looming and numbers to crunch, the rush to get everything done in good time can cause people to let their guard down. In the shuffle, it’s easy to miss the signs that the site where you’re detailing your finances has zero connection to the revenue service, or that the file you just downloaded, supposedly from a tax inspector, is actually malware.
In this post, we break down how these fraudulent tax agency sites operate across different countries and what you should absolutely avoid doing to keep your money and sensitive information safe.
This season, attackers have been spoofing tax authority websites across numerous countries, including the official government portals of Germany, France, Austria, Switzerland, Brazil, Chile, and Colombia. On these fraudulent sites, scammers harvest credentials for legitimate services, and steal personal data before offering to process a tax deduction — provided the victim enters their credit card details. In some cases, they even charge a fee for this fraudulent service.
A site imitating the Chilean tax authority. The victim is prompted to enter their credit card information to receive a substantial tax refund — roughly US$375. Instead, the funds are siphoned from the victim’s account directly to the scammers
Sometimes, the tactic involves accusations issued on behalf of government bodies. In the image below, for example, a “head of tax audit” in Paris informs the victim that they provided incomplete income information. To avoid penalties, the user is told to download a document and make corrections immediately. However, the PDF file hides something much worse: malware.
Instead of an official document from the French tax service, the user finds malware waiting inside the PDF
In Colombia, a fake National Directorate of Taxes and Customs site similarly prompts users to download documents that must be “unlocked with a security key”. In reality, this is simply a password-protected, malicious ZIP archive.
Beyond phishing sites mimicking legitimate resources, our experts have discovered fraudulent websites promising paid services for filling out and auditing tax documents — and stealing high-value data, such as taxpayer identification numbers (TINs), instead.
Cryptocurrency holders have emerged as a specific target for attackers. Fake German tax authorities are demanding that wallet owners “verify their digital asset holdings”, citing EU regulations for tax calculation purposes. And of course, there’s a “silver lining”: it turns out crypto earnings are supposedly tax-exempt! However, to claim this generous benefit, users must go through a “verification” procedure. The site even promises to encrypt data using a “2048-bit SSL protocol”.
To complete the “verification” process, users are prompted to enter their seed phrase — the unique sequence of words tied to a crypto wallet that grants full recovery access. This request is paired with a threat: refusing to provide the data will lead to serious legal consequences, such as fines up to one million euros or criminal prosecution.
Attackers pulled a similar stunt on French users as well. They created a non-existent “Crypto Tax Compliance Portal”, which mimics the design of the French Ministry of Economy and Finance website. The phishing site aggressively demands that French residents submit a “digital asset declaration”.
After the user enters their personal information, the scammers prompt them to either manually enter their seed phrase, or “link” their crypto wallet to the portal. If they go through with this, their MetaMask, Binance, Coinbase, Trust Wallet, or WalletConnect wallets will be drained.
When you have AI at your fingertips that can instantly generate text and fill out spreadsheets, there’s a serious temptation to delegate everything to it. Unfortunately, this can lead to serious consequences. First, all popular chatbots process your data on their servers, which puts your sensitive information at risk of a leak. Second, they sometimes make incredibly foolish mistakes, and that can lead to actual trouble with the taxman.
Before you tell a chatbot or an AI agent how much money you made last year — complete with detailed personal and banking info — remember how frequently leaks occur within AI-powered services and consider the risks. Don’t discuss your income with AI, don’t give it personal details like your name or address, and under no circumstances should you upload photos or numbers of vital documents such as passports, insurance info, or social security numbers. Files containing confidential information should be kept in encrypted containers, such as Kaspersky Password Manager.
If you’re still determined to use AI tools, run them locally. This can be done for free even on a standard laptop, and we’ve previously covered how to set up local language models using DeepSeek as an example. However, the quality of the output from these models is often subpar. It’s quite possible that double-checking every digit in an AI-generated response will take more time than just filling out the paperwork manually. Remember, you’re the one accountable to the tax office for any errors — not the AI.
Finally, watch out for phishing AI models that offer “assistance” with tax filing. Kaspersky experts have discovered websites where users are prompted to upload tax invoices, supposedly for the automated generation of returns and deduction claims. Instead, attackers collect this personal data to resell on the dark web, or to use in future phishing attacks, blackmail, and extortion schemes.
The creators of a fake AI tool prompt users to upload tax documents, and kindly assure them that the site doesn’t store any user data. In reality, every piece of information entered — name, address, documents, contact person, phone number — ends up in the hands of cybercriminals
Remember that all legitimate AI services explicitly warn users not to share confidential data, and tax documents certainly fall into this category. Any AI tools promising to help you handle your tax paperwork are quite simply a scam.
Further reading on phishing and data security:
Kaspersky official blog – Read More

Cisco Talos is aware of UAT-4356‘s continued active targeting of Cisco Firepower devices’ Firepower eXtensible Operating System (FXOS). UAT-4356 exploited n-day vulnerabilities (CVE-2025-20333 and CVE-2025-20362) to gain unauthorized access to vulnerable devices, where the threat actor deployed their custom-built backdoor dubbed “FIRESTARTER.” FIRESTARTER considerably overlaps with the technical capabilities of RayInitiator’s Stage 3 shellcode that processes incoming XML-based payloads to endpoint APIs.
In early 2024, Cisco Talos attributed ArcaneDoor, a state-sponsored campaign focused on gaining access to network perimeter devices for espionage, to UAT-4356.
Customers are advised to refer to Cisco’s Security Advisory for mitigation and detection guidance, indicators of compromise (IOCs), affected products, and applicable software upgrade recommendations.
FIRESTARTER is a malicious backdoor implanted by UAT-4356 that allows remote access and control to execute arbitrary code inside the LINA process, a core component of Cisco’s ASA and FTD appliances running FXOS.
UAT-4356 established persistence for FIRESTARTER on compromised devices by manipulating the mount list for Cisco Service Platform (CSP), namely “CSP_MOUNT_LIST”, to execute FIRESTARTER. The mount list allows programs and commands to be executed as part of the device’s boot sequence. The persistence mechanism triggers during graceful reboot (i.e., when a process termination signal is received). FIRESTARTER also checks the runlevel for value 6 (indicating device reboot) and in case of a match, writes itself to backup location “/opt/cisco/platform/logs/var/log/svc_samcore.log” and updates the CSP_MOUNT_LIST to copy itself back to “/usr/bin/lina_cs” and then be executed. When FIRESTARTER runs after a reboot, it restores the original CSP_MOUNT_LIST and removes the trojanized copy. Because the runlevel triggers establishment of this transient persistence mechanism, a hard reboot (for example, after the device has been unplugged from power) effectively removes the implant from the device.
FIRESTARTER has used the following commands to establish persistence for itself using the transient persistence mechanism:

When the implant injects itself into the LINA process, it removes the traces of its persistence mechanism by restoring the CSP_MOUNT_LIST from a temporary copy (“CSP_MOUNTLIST.tmp”), then removing the temporary copy and the FIRESTARTER file from disk (“/usr/bin/lina_cs”).
FIRESTARTER can run arbitrary shellcode received by the device. A pre-defined handler function specified by a hardcoded offset in the LINA process’ memory is replaced by an unauthorized handler routine that parses the data being served to it. FIRESTARTER specifically looks for a WebVPN request XML. If the request data received matches a specific pattern of custom-defined prefixing then the shellcode that immediately follows it is executed in memory. If the prefixing bytes are not found, then the data is treated as regular request data and passed to the original handler function (if any).
FIRESTARTER’s loading mechanism, Stage 2 shellcode (i.e., the actual request handler component), handler function replacement, XML parsing for magic bytes, and final payload execution display considerable overlaps with RayInitiator’s Stage 3 deployment actions and accompanying artifacts.
FIRESTARTER first reads the LINA process’ memory to search for and verify the presence of the bytes (long) 0x1, 0x2, 0x3, 0x4, 0x5 at specific locations in memory. If found, FIRESTARTER will then query the process’ memory to find an “r-xp” memory range for the shared library “libstdc++.so”. It then copies the next stage shellcode (Stage 2) to the last 0x200 bytes of the memory region. FIRESTARTER then overwrites an internal data structure in the LINA process’ memory to replace a pointer to a WebVPN-specific, legitimate XML handler function with the address of the malicious Stage 2 shellcode.
The malicious shellcode is triggered as part of the authentication API’s request handling process and parses the incoming request data for magic markers signifying an executable payload. If found, the executable payload is then executed on the compromised device.
The presence of the following artifacts – specifically the filenames “lina_cs” and “svc_samcore.log” – though somewhat brittle indicators, may indicate the presence of the FIRESTARTER on a Firepower device:
For more comprehensive detection guidance, please refer to Cisco’s Security Advisory here. Please also refer to CISA’s update to V1: Emergency Directive (ED) 25-03: Identify and Mitigate Potential Compromise of Cisco Devices and FIRESTARTER Backdoor Malware Analysis Report for more information and guidance.
We recommend that Cisco customers follow the steps recommended in Cisco’s advisory, with particular attention to any applicable software upgrade recommendations. Organizations impacted can initiate a TAC request for Cisco support.
A FIRESTARTER infection may be mitigated on all affected devices by reimaging the devices.
On Cisco FTD software that is not in lockdown mode, there is also the option of killing the lina_cs process then reloading the device:
> expert $ sudo kill -9 $(pidof lina_cs) $ exit > reload
Open-source Snort Subscriber Rule Set customers can stay up to date by downloading the latest rule pack available for purchase on Snort.org.
The following Snort rules cover the vulnerabilities CVE-2025-20333 and CVE-2025-20362: 65340, 46897.
Snort rules covering FIRESTARTER: 62949
The following ClamAV signatures detect this threat: Unix.Malware.Generic-10059965-0
Cisco Talos Blog – Read More
Lately, hackers have been turning up the heat on software developers. On the surface, this might seem like a puzzling move — why go after someone who’s literally paid to understand tech when there are plenty of less-savvy targets in the office? As it turns out, compromising a developer’s machine offers a much bigger payoff for an attacker.
For starters, compromising a coder’s workstation can give attackers a direct line to source code, credentials, authentication tokens, or even the entire development infrastructure. If the company builds software for others, a hijacked dev environment allows attackers to launch a massive supply chain attack, using the company’s products to infect its customer base. If the developer works on internal services, their machine becomes a perfect beachhead for lateral movement, allowing hackers to spread deeper into the corporate network.
Even when attackers are purely chasing cryptocurrency (and let’s face it, tech pros are much more likely to hold crypto than the average person), the malware used in these hits doesn’t just swap out wallet addresses; it vacuums up every scrap of valuable data it can find — especially those login credentials and session tokens. Even if the original attackers don’t care about corporate access, they can easily flip those credentials to initial access brokers or more specialized threat actors on the dark web.
In practice, developers aren’t nearly as good at understanding cyberthreats and spotting social engineering as they think they are. This misconception is a big reason why they often fall prey to cybercriminals. Professional expertise can often create a false sense of digital invincibility. This often leads technical professionals to cut corners on security protocols, bypass restrictions set by the security team, or even disable security software on their corporate machines when it gets in the way of their workflow. That mindset, combined with a job that requires them to constantly download and run third-party code, makes them sitting ducks for cyberattackers.
Once an attacker sets their sights on a software engineer, their go-to move is usually finding a way to slip malicious code onto the machine. But that’s just the tip of the iceberg — hackers are also masters at rebranding classic, battle-tested tactics.
One of the most common ways to hit a developer is by poisoning open-source software. We’ve seen a flood of these attacks over the past year. A prime example hit in March 2026, when attackers managed to inject malicious code into LiteLLM, a popular Python library hosted in the PyPI repository. Because this library acts as a versatile gateway for connecting various AI agents, it’s baked into a massive number of projects. These trojanized versions of LiteLLM delivered scripts designed to hunt for credentials across the victim’s system. Once stolen, that data serves as a skeleton key for attackers to infiltrate any company that was unlucky enough to download the infected packages.
Every so often, attackers post enticing job openings for developers, complete with take-home test assignments that are laced with malicious code. For instance, in late February 2026, malicious actors pushed out web application projects built on Next.js via several malicious repositories, framing them as coding tests. Once a developer cloned the repo and fired up the project locally, a script would trigger automatically to download and install a backdoor. The attackers gained full remote access to the developer’s machine.
Recently, our experts described an attack where hackers used paid search-engine ads to push malware disguised as popular AI tools. One of the primary baits was Claude Code, an AI coding assistant. This campaign specifically targeted developers looking for a way to use AI-assistants under the radar, without getting the green light from their company’s infosec team. The ads directed users to a malicious site that perfectly mimicked the official Claude Code documentation. It even included “installation instructions”, which prompted the user to copy and run a command. In reality, running that command installed an infostealer that harvested credentials and shuttled them off to a remote server.
That said, attackers often stick to the basics when trying to plant malware. A recent investigation into a compromised npm package — Axios — revealed that hackers had gained access to a maintainer’s system using a shockingly simple “outdated software” ruse. The attackers reached out to the Axios repository maintainer while posing as the founder of a well-known company. After some back-and-forth, they invited him to a video interview. When the developer tried to join the meeting on what looked like Microsoft Teams, he hit a fake notification claiming his software was out of date and needed an immediate update. That “update” was actually a Remote Access Trojan, giving the attackers access to his machine.
Sometimes, even a blast of fake notifications does the trick, especially when it’s tailored to the audience. For example, just recently, attackers were caught posting fake alerts in the Discussions tabs of various GitHub projects, claiming there was a critical vulnerability in Visual Studio Code that required an immediate update. Because developers subscribed to those discussions received these alerts directly via email, the notifications looked like legitimate security warnings. Of course, the link in the message didn’t lead to an official patch; it pointed to a “fixed” version of VS Code that was actually laced with malware.
To minimize the risk of a breach, companies should lean into the following best practices:
Kaspersky official blog – Read More
ANY.RUN has expanded access to Threat Intelligence capabilities for SOC and MSSP teams, backed by live attack data from 15,000 organizations.
Here’s how your team can test TI’s impact on triage quality, response speed, and threat hunting workflows.
ANY.RUN now offers 20 premium requests in Threat Intelligence Lookup and YARA Search as part of the Free plan.
You can get immediate threat context for over 40 types of IOCs, IOBs, and IOAs belonging to the latest malware & phishing attacks. All data is sourced from real sandbox investigations by ANY.RUN’s community of 15,000 organizations and 600,000 security analysts and experts.

AI-assisted search is available directly in the query flow, allowing analysts to use natural language and move from question to results without manual query building.
With this expanded access, SOC and MSSP teams can explore Threat Intelligence capabilities in their workflows and see how it affects core SOC processes for faster and more confident operations:
This directly impacts key SOC metrics, including reduced time per investigation, lower escalation rates, and faster Mean Time to Respond.
To speed up investigations and simplify how analysts work with Threat Intelligence, TI Lookup now includes AI-assisted search directly in the search bar.

Analysts can use natural language to query data, while the system automatically translates requests into structured queries with the correct parameters and wildcards.
This removes time spent on query construction and reduces friction in the workflow. Analysts move faster from alert to context, run more queries in less time, and get consistent results without additional steps.
Threat intelligence becomes truly valuable when it integrates into everyday operations. Here’s how it reinforces the three pillars of any SOC.
Alert volume is the defining operational challenge for most SOC teams. The ability to validate an alert quickly and to make a confident decision about whether to close it or escalate directly determines how efficiently a team can operate.
With ANY.RUN’s threat intelligence, analysts can immediately check an incoming indicator against a broad base of real-world attack data. Known-malicious infrastructure, recognized malware patterns, and previously documented campaigns can be matched in seconds. This means:

Analysts spend less time on inconclusive alerts and more time on confirmed threats. With documented context to support every decision.
Once an incident is confirmed, speed and precision matter. The quality of the response depends on how well the team understands the threat: its connections, its infrastructure, its behavioral patterns, and its likely next moves. Two clicks in TI Lookup search results cited above take your analyst to a sandbox session of malware detonation and attack chain exposure:

ANY.RUN’s threat intelligence enables response teams to map the relationships between indicators and the broader campaigns or actor groups behind them. Shared infrastructure, overlapping TTPs, and connected artifacts can be identified quickly, giving responders a structural understanding of what they are dealing with, not just a list of individual indicators.
This translates into:
Overreaction and underreaction are reduced at the same time. The response becomes targeted, not reactive.
Proactive threat hunting requires the ability to test hypotheses against real-world data. Analysts need to move from a suspicion about adversary behavior to a confirmed or refuted finding with enough evidence to act.
ANY.RUN’s threat intelligence gives hunters access to a rich, searchable base of behavioral data from real-world malware analysis. Campaign linkages, attacker infrastructure patterns, and behavioral signatures can all be researched in depth.

YARA Rules Search adds a further dimension, allowing hunters to build and validate detection logic against current threat data.
The result is a hunting capability that is grounded in current, real-world evidence rather than theoretical models. It enables teams to find genuine threats and build detection coverage that reflects how adversaries actually behave. Hunting shifts from speculative to evidence-driven.
Behind every alert, investigation, and response action, there is a business impact quietly accumulating.
The Free plan is a genuine starting point: a full-capability evaluation that lets teams verify the value of ANY.RUN’s intelligence on real workflows. For organizations ready to operationalize threat intelligence at scale, ANY.RUN offers paid plans designed for different operational needs.

These include Live, Core, and Complete plans, allowing teams to choose the level of access and integration that fits their workflows and scale.
Across these plans, organizations can leverage the full set of threat intelligence capabilities, including:
1. Threat Intelligence Feeds
Continuous streams of validated indicators enriched with behavioral context from the sandbox analyses, delivered directly into SIEM, EDR, IDS/IPS, and SOAR systems. This enables automated enrichment and faster detection pipelines.
2. Threat Intelligence Reports: full access
Structured analyses of active campaigns, malware families, and attacker techniques. These reports provide ready-to-use insights for both operational response and strategic planning.

What makes them particularly useful in operations:
Reports act as a bridge between raw telemetry and strategic understanding. They help teams not only react faster, but also recognize patterns before they escalate into incidents.
3. Threat Landscape
A contextual layer that maps threats to industries and geographies, helping organizations understand where specific risks are most relevant to their business.

Together, these capabilities support key business objectives:

The result is a measurable improvement in how security operations contribute to overall business resilience.
The gap between threat detection and effective response is not primarily a technology problem. It is a data problem. When analysts have access to rich, current, contextual intelligence at the moment they need it, decisions improve and outcomes follow.
ANY.RUN’s unified threat intelligence — TI Lookup, TI Feeds, TI Reports, and YARA Search, all powered by real sandbox data from 15,000 organizations — gives SOC and MSSP teams that foundation. The free plan removes the evaluation barrier: any team can run it through real workflows, on real alerts, before committing to anything.
For teams that operationalize it, the cumulative effect is a SOC that is measurably faster, more accurate, and more confident — and an organization that is measurably harder to compromise and cheaper to defend.
ANY.RUN, a leading provider of interactive malware analysis and threat intelligence solutions, helps security teams investigate threats faster and with greater clarity across modern enterprise environments.
It allows teams to safely execute suspicious files and URLs, observe real behavior in an Interactive Sandbox, enrich indicators with immediate context through TI Lookup, and monitor emerging malicious infrastructure using Threat Intelligence Feeds. Together, these capabilities help reduce investigation uncertainty, accelerate triage, and limit unnecessary escalations across the SOC.
ANY.RUN is trusted by thousands of organizations worldwide and meets enterprise security and compliance expectations. It is SOC 2 Type II certified, demonstrating its commitment to protecting customer data and maintaining strong security controls.
It includes 20 investigations in Threat Intelligence Lookup with AI-assisted search, access to YARA search, and the free Threat Intelligence Reports to evaluate real workflows.
It is not a limited demo. It allows teams to test threat intelligence directly within their SOC processes, using real alerts and investigations.
It is generated from real-world malware analyses in the ANY.RUN Interactive Sandbox, enriched with behavioral data, infrastructure links, and campaign context.
It simplifies query building by translating intent into structured search parameters, reducing time spent on syntax and accelerating investigations.
Yes, paid plans support integration with SIEM, SOAR, and other security systems, enabling automated workflows and enrichment.
SOC teams, MSSPs, and security leaders who want to improve decision speed, reduce uncertainty, and lower incident response costs.
The post More Attack Context for Faster Triage, Response, and Hunting. Now Available to Every SOC appeared first on ANY.RUN’s Cybersecurity Blog.
ANY.RUN’s Cybersecurity Blog – Read More

Talos IR responded to a campaign that leveraged phishing, the most common means of initial access this quarter, to compromise the most targeted industry vertical this quarter: public administration. Notably, the actors leveraged the SoftrAI-based web application development service, marking the first time we have documented the use of a specific AI tool by an adversary in a phishing campaign. Softr was used to generate a credential harvesting page targeting users’ Microsoft Exchange and Outlook Web Access (OWA) accounts.
State-sponsored and criminal actors have been observed abusing large language models (LLMs) to aid in the development of phishing lures, malicious scripts, and other tasks. DDoS-as-a-service actors have adopted AI algorithms for defense evasion and attack orchestration. While this is the first time we have documented the use of a specific AI tool in a Talos IR incident, we have moderate confidence that malicious actors have used Softr’s AI-powered web application creation platform since at May 2023, based on Cisco Umbrella data and other telemetry, and have done so with increasing frequency to date.
This incident demonstrates how AI tools can lower the barrier to entry for less sophisticated actors and/or accelerate the speed of phishing and credential-harvesting campaigns. Using a form template and the “vibe coding” feature, a phishing page like the one used in this attack could be quickly created with a few AI prompts and no code. Phishing pages built with Softr can direct data to a disposable external data store, such as Google Sheets, and send alerts for new captures via email — all without code.
Talos IR experienced its first case involving Crimson Collective, a cyber extortion group that appeared in September 2025. This attack highlighted the use of valid accounts for initial access, the second most commonly observed means of initial access this quarter. This attack also notably involved targeting exploit weaknesses, the second-most observed security weakness, accounting for 25 percent of all engagements. We attribute this activity to Crimson Collective based on IPs associated with the group that were used to scan the victim’s ASA firewalls, as well as an overlap of observed tactics and techniques with publicly reported Crimson Collective attacks.
The incident began when a GitHub Personal Access Token (PAT) was inadvertently published on a public-facing website, exposing the organization to adversaries for several months. Upon obtaining access, the adversary used TruffleHog, an open-source tool commonly utilized by security professionals, to scan thousands of victim GitHub repositories for additional secrets and sensitive information. This approach allows attackers to perform reconnaissance without triggering suspicion, as they are leveraging standard, legitimate tools. The attacker’s discovery of client secrets through TruffleHog enabled further access to the victim’s Azure cloud storage, where they used Microsoft Graph API calls to authenticate, explore, and exfiltrate data. The abuse of legitimate cloud APIs demonstrates a growing trend where threat actors use native platform functionality to blend into normal user activity, making detection more challenging.
In addition to exfiltrating data, the adversary attempted to inject malicious code into multiple GitHub repositories. This code was designed to harvest any new secrets committed in the future, sending them to adversary-controlled infrastructure. Though these attempts were largely thwarted by the expiration of targeted secrets and effective security controls, the tactic reflects an emerging trend of supply chain and development environment attacks.
Pre-ransomware incidents made up just 18 percent of engagements this quarter, and we did not observe any ransomware encryption due to early and swift mitigation from Talos IR. This is a slight increase from last quarter, when ransomware and pre-ransomware collectively comprised 13 percent of engagements, but overall very low compared to Q1 and Q2 2025, when we observed ransomware in 50 percent of engagements. Attribution is challenging in pre-ransomware events because there are no encryptors or ransom notes, but we assess that Rhysida ransomware and MoneyMessage ransomware accounted for two of the engagements.
While we did not observe many active and prolific ransomware-as-a-service (RaaS) operations, like Qilin or Akira, this likely does not indicate these major players are decreasing operations, as their data leak sites remain consistently active.
Talos IR responded to a ransomware incident where the adversary attempted to deploy Rhysida ransomware. While the attack was mitigated in the pre-ransomware stage, we attribute this activity with moderate confidence to Rhysidabased on observed infrastructure that is associated with Rhysida activity and the use of Gootloader, which is commonly leveraged in Rhysida attacks during initial access. Notably, the actors deployed proxy-related DLLs (e.g., “meow_eu.dll”), which we assess were likely related to MeowBackConn, an uncommon backdoor that is closely associated with Gootloader, based on public reporting.
This attack represents several trends that we observed throughout Talos IR engagements in Q1 2026. The environmental weaknesses that enabled this intrusion — exposed WinRM management ports, over-privileged service accounts, and critical logging gaps — directly echo this quarter’s most prominent security weaknesses, including vulnerable or exposed infrastructure, accounting for 25 percent of engagements. Furthermore, the adversary’s use of Remote Desktop Protocol (RDP) for lateral movement is consistent with RDP being the top technique for lateral movement for the previous two quarters (Q3 and Q4 2025).

Public administration and health care were tied as the most targeted industry verticals. Notably, Q3 2025 marked the first time public administration emerged as the most targeted sector in Talos IR engagements, and it has retained that position since. Organizations within the public administration sector are attractive targets as they are often underfunded and use legacy equipment. These entities may have access to sensitive data as well as a low downtime tolerance, making them attractive to financially motivated and espionage-focused threat groups.

Phishing reemerged as the most observed means of gaining initial access, accounting for over a third of the engagements where initial access could be determined. Phishing was the top initial access vector in the first half of 2025, at which point it was surpassed by exploitation of public-facing applications, likely due to the widespread exploitation of vulnerabilities in on-premises Microsoft SharePoint servers, collectively referred to as ToolShell. Since then, we have observeda steady decrease in the exploitation of public-facing applications as an initial access vector from a high of 62 percent to only 18 percent in Q1 2026. Similarly, in this quarter, valid accounts returned to its pre-ToolShell baseline as the second most observed means of gaining initial access, comprising 24 percent of Talos IR engagements. We assess the decline in ToolShell exploitation is likely due to the widespread availability of emergency patches and enhanced security detections, highlighting the importance of timely patching.

35 percent of engagements this quarter involved multi-factor authentication (MFA) weaknesses, an increase from last quarter. This includes incidents where threat actors bypassed MFA and where MFA was either missing or only partially enabled, particularly on remote access services. Adversaries were able to bypass MFA by registering new devices to previously compromised accounts, and in one instance, by configuring Outlook clients to connect directly to Exchange servers, circumventing MFA requirements. Addressing these weaknesses, especially by restricting self-service MFA enrollment and enforcing strong, centralized authentication policies, is essential to reducing risk and strengthening organizational resilience.
Vulnerable or exposed infrastructure was another top security weakness accounting for 25 percent of all engagements, a slight decrease from last quarter. This included exploiting a vulnerability (CVE-2025-20393) in the Spam Quarantine feature of Cisco AsyncOS Software for Cisco Secure Email Gateway and Cisco Secure Email and Web Manager, as well as a vulnerability (CVE-2023-20198) in the web UI feature in Cisco IOS XE Software. Talos also observed exposed management ports (such as WinRM open to the internet), which enabled rapid attacker movement and reconnaissance.
Finally, 18 percent of engagements this quarter involved organizations with insufficient logging capabilities, which hindered investigative efforts. Understanding the full context and chain of events performed by an adversary on a targeted host is vital not only for remediation but also for enhancing defenses and addressing any system vulnerabilities for the future. To address this issue, Talos IR recommends organizations implement a security information and event management (SIEM) solution for centralized logging. In the event an adversary deletes or modifies logs on the host, the SIEM will contain the original logs to support a forensics investigation. Additionally, Talos IR offers a Log Architecture Assessment service, which provides a focused review of an organization’s logs and overall log strategy to identify gaps and offer recommendations that give a complete view of the security environment and strengthen incident response readiness
The tables below represent the MITRE ATT&CK techniques observed in this quarter’s IR engagements and includes relevant examples and the number of times seen. Given that some techniques can fall under multiple tactics, we grouped them under the most relevant tactic based on the way they were leveraged. Please note that this is not an exhaustive list.
Key findings from the MITRE ATT&CK framework include:
|
Tactic |
Technique |
Example |
Estimated times observed |
|
Reconnaissance |
T1589.002: Gather Victim Identity Information: Email Addresses |
The adversary enumeratedinternal processes and identifiedvendor emails to facilitate their fraudulent ordering scheme. |
1 |
|
|
T1595: Active Scanning
|
The adversary scanned public-facing websites to understand the target environment. |
2 |
|
|
T1593: Search Open Websites/Domains |
The adversary scanned the web to obtain Github PATs. |
1 |
|
Initial access |
T1566: Phishing |
The adversary used malicious emails and social engineering to compromise user accounts and facilitate fraudulent purchase orders. |
5 |
|
|
T1189: Drive-by compromise |
The adversary registered several domains that masquerade as being related to VMware, and manipulated the SEO to show them at the top when searching for keywords such as VMware |
3 |
|
|
T1078: Valid Accounts |
The adversary successfully gained access to the environment by using compromised user credentials |
4 |
|
|
T1190: Exploit public-facing applications |
Two internet facing Linux servers running Apache and an LMS application were targeted. |
3 |
|
Execution |
T1204.002: User Execution: Malicious File |
The victim downloaded a malicious installer on their personal host, connected the host to their company’s network, transferred the malware to their primary domain controller, then executed the malware. |
3 |
|
|
T1204.001: User Execution: Malicious link |
The victim clicked on a link that led to a fake DocuSign document hosted on adobe[.]com |
5 |
|
|
T1059.001: Command and Scripting Interpreter: PowerShell |
The adversary used PowerShell commands and scripts for execution. |
4 |
|
|
T1059.006: Command and Scripting Interpreter: Python |
The adversary used automated Python scripts to interact with the environment. |
1 |
|
|
T1059.005: Command and Scripting Interpreter: MSHTA |
The adversary attempted to use mshta.exe to retrieve and execute a remote malicious payload from an external URL. |
1 |
|
Persistence |
T1556.006: ModifyAuthentication Process: Multi-Factor Authentication |
The adversary registered their own malicious MFA devices to maintain access to compromised accounts. |
2 |
|
|
T1219: Remote Access Software |
The adversary installed and used AnyDesk for unauthorized remote access. |
1 |
|
|
T1053.005: Scheduled Task/Job: Scheduled Task |
The adversary configured tasks to run on a schedule or at system startup. |
1 |
|
|
T1505: Server Software Component |
The adversary installed malware on breached devices to facilitateremote command execution via HTTP. |
1 |
|
Privilege escalation |
T1068: Exploitation for Privilege Escalation |
The adversary escalated to SYSTEM level privileges, which may have provided access to cached credentials in memory or registry hive. |
1 |
|
|
T1548: Abuse Elevation Control Mechanism |
The adversary used ExecutionPolicy Bypass in PowerShell and attempted to add users to the local Administrators group. |
1 |
|
|
T1078 Valid Accounts |
The adversary bypassed standard access controls by using compromised accounts with existing high-level privileges. |
1 |
|
Defense evasion |
T1070.003: Indicator Removal on Host: Clear Command History |
The adversary used the terminal emulator “ConEmu” to run commands, intentionally avoiding log generation. |
2 |
|
|
T1070.001: Indicator Removal: Clear Windows Event Logs |
The adversary deleted logs on compromised devices to limit forensic findings. |
1 |
|
|
T1556: ModifyAuthentication Process |
The adversary set up an Outlook client Outlook client to connect to the Exchange Server and was able to send messages via that path which bypasses the requirement for MFA via Duo. |
1 |
|
|
T1562.001: Impair Defenses: Disable or Modify Tools |
The adversary was able to uninstall EDR agents from hosts and attempted to delete Windows Defender policies. |
4 |
|
Credential access
|
T1003.002: OS Credential Dumping: Security Account Manager |
The adversary saved SAM and SYSTEM registry hives to extract local account hashes. |
2 |
|
|
T1003.003: OS Credential Dumping: NTDS |
The adversary dumped the ntds.dit file from Domain Controllers to obtain domain-wide credential hashes. |
1 |
|
|
T1003.005: Cached Domain Credentials |
The adversary gained NT hashes for multiple domain accounts from cached logon information. |
1 |
|
|
T1557: Adversary-in-the-Middle |
The adversary used an AiTMproxy to capture credentials and session tokens. |
1 |
|
Discovery |
T1087.003: Account Discovery: Email Account |
The adversary used Graph API calls to verify long lists of email addresses and retrieve associated user GUIDs. |
1 |
|
|
T1580: Cloud Infrastructure Discovery |
The adversary performed enumeration of the environment, including gathering OneDrive metadata (drive IDs and child item counts) and user roles. |
1 |
|
|
T1069.002: Permission Groups Discovery: Domain Groups |
The adversary used commands like net group “domain admins” /domain to find high-privilege accounts.
|
1 |
|
|
T1526: Cloud Service Discovery |
The adversary ran the legitimate cybersecurity tool TruffleHog to discover repositories containingclient secrets and personal information. |
1 |
|
Lateral movement |
T1021.002: Remote Services: SMB/Windows Admin Shares |
The adversary used PsExec(communicated over SMB) to move laterally from the compromised domain controller to other servers. |
4 |
|
|
T1047: Windows Management Instrumentation |
The adversary used PowerShell scripts to leverage WMI (Get-WmiObject) to query remote computers. |
3 |
|
|
T1021.001: Remote Services: Remote Desktop Protocol |
The adversary used RDP connections between hosts. |
3 |
|
Collection |
T1530: Data from Cloud Storage Object |
The analysis of M365 Audit Logs showed multiple FileAccessedand FileDownloaded events for documents stored in SharePoint and OneDrive. |
1 |
|
|
T1040 Network Sniffing |
The adversary executed monitor capture commands on specific interfaces to intercept and capture network traffic. |
1 |
|
Command and control |
T1071.001: Application Layer Protocol: Web Protocols |
The adversary used MeshAgentto communicate with the C2 server over WebSockets. |
5 |
|
|
T1102: Web Service |
The adversary leveraged a Telegram URL to issue instructions and download links. |
1 |
|
|
T1572: Protocol Tunneling |
The adversary used a second-stage script to create an HTTPS tunnel directly to the C2 system. |
1 |
|
|
T1201: Traffic Signaling |
The adversary communicated with external infrastructure using regular beaconing or other signaling patterns to maintain C2 or check in with their C2 server. |
1 |
|
Exfiltration |
T1567.002: Exfiltration Over Web Service |
The adversary accessed and exfiltrated internal data, specifically SharePoint files, via web-based channels. |
1 |
|
|
T1041: Exfiltration Over C2 Channel |
The adversary exfiltrated approximately 2,500 client secrets and personal information. |
2 |
|
Impact |
T1657: Financial Theft |
The adversary used company resources to place orders totaling hundreds of thousands of US dollars for various products which were successfully delivered. |
1 |
|
|
T1486 Data Encrypted for Impact |
The adversary encrypted victim data. |
1 |
|
|
T1531 Account Access Removal |
The adversary disabled admin accounts and deleted service accounts in the Active Directory (AD) and Azure |
1 |
|
Software |
Rhysida |
A RaaS, known for posing as a cybersecurity team that “helps” its victims identify security weaknesses in their networks. |
Pre-ransomware engagement |
|
|
SocGholish |
A JavaScript-based loader malware that has been used since at least 2017, primarily for initial access. |
1 |
|
|
Money Message |
A ransomware that emerged in March 2023, and is capable of targeting Windows and Linux systems (including VMware ESXiservers). |
Pre-ransomware engagement |
Cisco Talos Blog – Read More
![[Podcast] It's not you, it's your printer: State-sponsored and phishing threats in 2025](https://storage.ghost.io/c/af/a0/afa04ee3-414f-4481-8d23-7e7c146f192e/content/images/2026/04/YiR2025_cover_2x1-2-1.jpg)
In this episode, we unpack state-sponsored and phishing trends from the 2025 Talos Year in Review. Amy and Martin Lee explore the alarming rise of internal phishing campaigns that bypass traditional perimeter defenses, including the widespread weaponization of Microsoft 365’s Direct Send feature. Beyond simple phishing, we analyze the aggressive, blended operations of state-sponsored actors from China and North Korea who are combining high-level zero-day exploits with sophisticated social engineering. From the “Dear Leader” interview test to the reality of fake developer personas, we break down exactly how these adversaries are infiltrating modern organizations.
View the 2025 Year in Review here.
Cisco Talos Blog – Read More

In 2025, attackers increasingly targeted weaknesses in multi-factor authentication (MFA) workflows, and phishing attacks leveraged valid, compromised credentials to launch lures from trusted accounts. The trends focused entirely on trust, or the lack thereof, in everyday business operations.
In 2025, phishing attacks were used for initial access in 40% of incidents, maintaining their prevalence. Attackers ramped up cascaded phishing campaigns, where attackers leveraged the trust of the initial compromised account to create specialized phishing attempts, within the network and out of it, aimed at trusted partners and third parties.

The content of phishing emails changed somewhat. Transitioning away from spam offers, they took the form of workflow-style emails — IT, travel, and other everyday business tasks that look familiar to employees and executives. Travel and logistics lures in particular surged, while political lures dropped off. Internal expensing and travel emails, even when legitimate, are often repetitive and come from disparate sources with changeable formats or poorly-rendered templates, leading to a lowered guard toward spotting malicious intent. Attackers were likely aiming to steal credentials, payment information, or MFA tokens via fake single sign-on (SSO) pages.
In reviews of thousands of blocked-email keywords, 60% contained subject lines with “request,” “invoice,” “fwd,” “report,” and similar. IT-focused phishing keywords turned more technical, to words like “tampering,” “domain,” “configuration,” “token,” and others, showing that attackers were making plays toward IT and security workflows.
Attackers also abused Microsoft 365 Direct Send to capitalize on internal email trust. Direct Send is the method by which networked devices like printers and scanners deliver documents to users. The messages appear to be sent and received by the same email address. These internal messages do not receive the same scrutiny that external emails do, from employees or automated email filters. Direct Send allowed attackers to spoof internal email addresses and deliver highly convincing lures from inside the organization, without compromising real accounts, to target key attack services and deliver high-impact damage.
Identity and access management (IAM) applications have grown popular with organizations hoping to consolidate user privileges. Unfortunately, it has also grown in popularity with attackers. Nearly a third of 2025 MFA spray attacks targeted IAM, turning the tools companies used to maintain access control into a point of failure. Device compromise surged by 178%, largely driven by voice phishing designed to trick administrators into registering malicious devices.
MFA attack strategy changed by sector. A successful attack could glean SSO tokens and give adversaries the ability to change user roles and credentials, or even the MFA policies themselves. Attackers increasingly exploited authentication workflows to gain and maintain access.

Spray attacks were deployed against networks with predictable identity behavior, while diverse, unmanaged, or high-turnover device ecosystems proved weaker to device compromise attacks.
Notably, higher education was the most targeted device compromise sector. Several factors could contribute to the trend:
· Diverse unmanaged device population
· Poorly patched and managed operating systems
· Necessarily low new-device verification policies
· Large, public-facing directories for targeted phishing
Higher education was a very unfavorable target for MFA spray attacks, however. Passwords and MFA are also highly varied and segmented, and most universities have strong login portal policies, enforced lockouts, and login attempt limits.
As always, prioritize based on your own environment.
Organizations should keep in mind that living-off-the-land binaries (LOLBins) and open-source and dual-use tools, which are not inherently malicious, are key to further exploitation. Blocking external IPs from using a feature, enabling Microsoft’s newer “Reject Direct Send” control, tightening SPF/DMARC enforcement, and treating “internal-looking” emails with the same scrutiny as inbound mail are currently the most effective defenses.
Likewise, MFA attack protection should be tailored to the style of environment and sector.
MFA spray attacks work well on stable, scaled identity controls. Counter these attacks with strong lockout policies, good password hygiene, and conditional access.
Device compromise works best on variable networks where devices change over fast and MFA use is spotty. Work on establishing better device hardening and management, session controls, and strict phishing-resistant MFA with enrollment governance. Solutions such as Cisco Duo provide controls for phishing-resistant MFA, device trust, and secure enrollment, helping reduce risk from phishing and identity-based attacks. Solutions such as Cisco Duo provide controls for phishing-resistant MFA, device trust, and secure enrollment, helping reduce risk from phishing and identity-based attacks.

This blog only scratched the surface on 2025 threat trends. See the full Year in Review report for a detailed explanation of Microsoft 365 Direct Send and how it was used for attacks, infographic breakdowns of MFA spray vs. device compromise attacks, the full list of targeted tools and sectors by percentage, and more.
Cisco Talos Blog – Read More

As macOS adoption in the enterprise reaches record highs, with over 45 percent of organizations now utilizing the platform, the traditional “security through obscurity” narrative surrounding the OS has been rendered obsolete. Mac endpoints, once relegated to creative departments, are now the primary workstations for developers, DevOps engineers, and system administrators. Consequently, these machines have become high-value targets that serve as gateways to source code repositories, cloud infrastructure, and sensitive production credentials.
Despite this shift, macOS-native lateral movement and execution tradecraft remain significantly understudied compared to their Windows counterparts. This research was conducted to address this critical knowledge gap. Through a systematic validation of native macOS protocols and system binaries, it is demonstrated how adversaries can “live off the land” (LOTL) by repurposing legitimate administrative tools. By weaponizing native primitives, such as Remote Application Scripting (RAS) and Spotlight metadata, intentional OS security features can be bypassed to transform standard system functions into robust mechanisms for arbitrary code execution and fleet-wide orchestration.

macOS is no longer a niche operating system. According to the Stack Overflow 2024 Developer Survey, a third of professional developers use macOS as their primary platform. These machines represent high-value pivot points, often holding source code repositories, cloud credentials, and SSH keys to production infrastructure.
Despite this trend, the MITRE ATT&CK framework documents far fewer techniques for macOS than for Windows, and recent industry reports indicate that macOS environments prevent significantly fewer attacks than their Windows or Linux counterparts. To address this disparity, community-driven resources such as LOOBins (living-off-the-orchard binaries) have emerged to catalog native macOS binaries that can be repurposed for malicious activity. This research aims to further close that gap by systematically enumerating the native pathways available for both movement and execution.
Establishing a remote shell is the first step in any post-exploitation chain. While SSH is the standard, native macOS features provide several alternatives that can bypass traditional monitoring.
Remote Application Scripting (formerly known as Remote Apple Events or RAE) was introduced to extend the capabilities of the AppleScript Inter-Process Communication (IPC) framework across a network. By utilizing the Electronic Program-to-Program Communication (“eppc”) protocol, administrative tasks and application automation can be performed on remote macOS systems. This mechanism allows a controller machine to send high-level commands to a target machine, which are then processed by the “AppleEventsD” daemon.
The Open Scripting Architecture (OSA) is utilized as the standardized framework for this inter-application communication and automation on macOS. Through the exchange of Apple Events, this architecture enables scripts to programmatically interact with the operating system and installed applications, providing the functional foundation for the “osascript” utility.
Traditionally, RAE is viewed as a lateral movement vector; however, this research demonstrates that it can also be utilized as a standalone Software Deployment Tool for Execution (T1072).
Adversaries attempting to use RAE for complex payloads often encounter Apple’s intentional security features, specifically the -10016 Handler Error. This restriction prevents the “System Events” application from executing remote shell commands via do shell script, even when RAE is globally enabled.

To bypass this, a methodology was developed that treats “Terminal.app” as an execution proxy. Unlike “System Events”, “Terminal.app” is designed for shell interaction and accepts remote “do script” commands. To ensure payload integrity and bypass AppleScript parsing limitations (such as the -2741 syntax error), Base64 transport encoding is utilized. This transforms multi-line scripts into flat, alphanumeric strings that are decoded and executed in a two-stage process:
chmod +x. 
While RAE can be weaponized for execution, its primary function remains the facilitation of inter-process communication (IPC) across a network. In a lateral movement context, RAE is utilized to control remote applications by targeting the “eppc://” URI. This allows for the remote manipulation of the file system or the retrieval of sensitive environmental data without the need for a traditional interactive shell.
For example, the command in Figure 4 can be used to remotely query the Finder for a list of mounted volumes on a target machine, providing an adversary with immediate insight into the victim’s network shares and external storage:

Because these actions are performed via Apple Events rather than standard shell commands, they often bypass security telemetry that focuses exclusively on process execution trees, making RAE a discreet and effective vector for lateral movement.
AppleScript is macOS’s built-in scripting language for automation. While RAE is a viable application control mechanism, Apple security controls prevent RAE from launching applications; they must already be running. Additionally, RAE must be enabled on the target. To circumvent these obstacles, osascript can be invoked directly over SSH.
Passing osascript the system info command over SSH returns critical environmental details:

For arbitrary command execution, AppleScript’s do shell script handler can be invoked over SSH. In the following example, do shell script is used to write a file to the target:

While SSH alone can accomplish shell tasks, osascript provides access to graphical user interfact (GUI) automation and Finder manipulation through Apple Events IPC rather than spawning shell processes. This creates a significant telemetry gap, as most endpoint detection tooling has less visibility into IPC-driven actions than standard shell process trees.
socat (SOcket CAT) is a command line utility for establishing bidirectional data streams between two endpoints. It supports a wide range of socket types including TCP, UDP, Unix domain sockets, and pseudo terminals (pty).
In a lateral movement context, socat can establish an interactive shell on a target without relying on SSH. The target runs a listener that binds a login shell to a TCP port with pty allocation, and the attacker connects to it from a remote machine.
On the target, the listener spawns an interactive bash session for each incoming connection with pty forwarding:

From the attacking machine, connecting to the listener provides a fully interactive terminal:

On the target, the reuseaddr,fork options allow multiple connections and reuse of the port, while pty,stderr on the exec gives the connecting client a proper terminal with stderr output. On the sender side, raw,echo=0,icanon=0 puts the local terminal into raw mode so that control characters and signals pass through to the remote shell correctly.
SSH is the de facto mechanism for gaining remote shell access on remote hosts, and as a result, it is where most detection engineering efforts are focused. socat achieves the same outcome, fully interactive terminal access, but operatesentirely outside the SSH ecosystem. There are no sshd logs, PAM authentication events, or “authorized_keys” to manage, which means detection pipelines built around SSH telemetry would not catch this activity.
A notable constraint of RAE is its inability to write file contents directly. To work around this, we can abuse the Finder Comment (“kMDItemFinderComment”) field, which is stored as Spotlight metadata.
A notable constraint of RAE is its inability to write file contents directly. To circumvent this, threat actors can abuse the Finder Comment field (“kMDItemFinderComment”) — a component of Spotlight metadata stored as an extended attribute. By storing a payload within metadata rather than the file’s data fork, they can bypass traditional file-based security scanners and static analysis tools, which typically focus on executable code and script contents.
Because Finder is scriptable over RAE, the comment of a file on a remote machine can be set via the “eppc://” protocol. By Base64 encoding a payload locally, a multi-line script can be stored within this single string field. The make new file command handles the creation of the target file, ensuring that no pre-existing file is required:

The payload resides entirely within the Spotlight metadata, a location that remains largely unexamined by standard endpoint detection and response (EDR) solutions. This creates a stealthy staging area where malicious code can persist on the disk without triggering alerts associated with suspicious file contents.
On the target, extraction and execution is a single line. mdls reads the comment, base64 -D decodes it, and the result is piped to “bash”:

This approach can be paired with a LaunchAgent for persistence. A plist in “~/Library/LaunchAgents” that executes the extraction chain at user login allows the payload to run automatically.
Our initial attempt using mdls inside the LaunchAgent failed because Spotlight may not be fully initialized when LaunchAgents fire. The fix was to replace mdls with osascript calling Finder directly to read the comment:

Talos confirmed this successfully executes the payload at login. It is worth noting that macOS prompts the user to approve the bash execution at login, which is a visible indicator of background activity. The plist contains no payload, only a reference to metadata, so static analysis of the LaunchAgent would not reveal the malicious content.
Once attackers achieve execution, they must move their toolkit across the environment. Several native protocols were validated for tool transfer (T1570).
SCP (Secure Copy Protocol) and SFTP (SSH File Transfer Protocol) are the most straightforward methods, operating over SSH and available out-of-the-box on any macOS system with Remote Login enabled.


Server Message Block (SMB) is a network file sharing protocol commonly associated with Windows environments, but macOS includes native support for both SMB client and server functionality. In a lateral movement context, an attacker can mount a remote SMB share and access its contents as if they were local files.
This method of setting up an SMB share on the victim requires SSH access. The following command creates a shared directory, loads the SMB daemon, and creates the share.

With the share created, the next step is mounting it from the attacker machine. Attempting this action with the mount command failed due to an authentication error.

To resolve this issue, GUI access to the victim machine was required. On the victim machine, navigate to System Settings > General > Sharing > File Sharing > Options. Located here is the option to store the user’s account password on the computer. Even though this is labeled as “Windows File Sharing”, it was required to properly authenticate the user when using the mount utility.
However, this entire GUI dependency can be avoided by using osascript to mount the share instead of mount:

This mounts the share to “/Volumes/share” without requiring the GUI configuration step. With the share mounted, any file copied into the mount directory appears on the victim immediately.
nc (netcat) is a well-known general-purpose networking utility that ships with macOS. It can be utilized to open arbitrary TCP and UDP connections, listen on ports, and pass data between them.
The simplest pattern involves piping commands directly into a netcat listener. On the target, a listener is established that pipes incoming data directly to sh:

From the attacking machine, a command is then echoed into nc targeting the victim’s IP and port:


The attacker sends the curl google.com command over the wire, which is caught by the victim’s listener and executed by sh. The resulting output confirms successful execution on the target.
Netcat can also facilitate file transfers through several different methods. An attacker could invoke a fetch to a remote system where a script or payload is hosted, or start a simple HTTP server on their own machine to perform ad hoc tool transfer.


git is a version control system ubiquitous in software development. Its prevalence on developer machines and reliance on SSH as a transport make git push a practical file transfer mechanism. The technique requires initializing a repository on the target and setting receive.denyCurrentBranch updateInstead. By default, git refuses pushes to a branch that is currently checked out on the remote. This setting overrides that behavior and updates the working tree on push, landing files on disk the moment the operation completes.
First, a receiving repository is initialized on the target over SSH:

On the attacker, a local repository is created with the payload, and the remote is pointed at the target:

After the push, “script.sh” exists on the target at “~/repos/project/script.sh”. Additional file transfers only require adding new files, committing, and pushing again. Because git operates over SSH, the transfer is encrypted and uses the same authentication established for command execution.
TFTP (Trivial File Transfer Protocol) is a lightweight, unauthenticated file transfer protocol that operates over UDP. macOS includes both a TFTP server and client. The server is not active by default but can be started through launchd.
With root access on the target, the system’s built-in TFTP plist activates the server in a single command:

This serves “/private/tftpboot” on the standard TFTP port (UDP 69). The TFTP system plist does not provide the -w flag to the tftpd process. Without it, the server only allows writes to files that already exist. A placeholder file must be created on the target for each file being transferred:

From the attacker, the payload is pushed to the target:

In a post-exploitation scenario without root access, tftpd can still be deployed by loading a user-created plist from “/tmp” on a non-standard port. This variant passes the tftpd -w flag, which allows write requests to create new files, removing the placeholder requirement.

SNMP (Simple Network Management Protocol) is used for monitoring and managing network devices. SNMP traps are unsolicited notifications sent from agents to a management station over UDP port 162. The trap payload can carry arbitrary string data under custom OIDs, which can be repurposed as a data transfer channel. macOS ships with the necessary net-snmp tools: snmptrap (“/usr/bin/snmptrap”) on the sender and snmptrapd (“/usr/sbin/snmptrapd”) on the receiver.
The approach works by Base64 encoding a file, splitting it into fixed-size chunks, and sending each chunk as an SNMP trap payload under a custom OID in the private enterprise space (“1[.]3[.]6[.]1[.]4[.]1[.]99999”). A trap handler on the receiving end reassembles the chunks and decodes the file. The protocol uses three message types: “FILENAME” signals the start of a transfer, “DATA” carries a Base64 chunk, and “END” triggers reassembly.
On the receiver, a trap handler processes incoming traps:

The snmptrapd daemon is then configured on the target to route all incoming traps to the handler and started in the foreground:

On the sender, a script handles the encoding, chunking, and transmission. Each chunk is sent as a separate SNMP trap with a short delay between sends to avoid overwhelming the receiver:

The sender initiates the transfer:

The target receives the transfer:

The matching MD5 hashes confirm the file was transferred and reassembled intact.
The socat shell established in the above “socat remote shell” section can also serve as a file transfer channel. Because the listener provides a fully interactive bash session, file contents can be written to the remote host by injecting a heredoc through the connection. This means socat alone handles both remote command execution and tool transfer without requiring any additional services or listeners.
With the socat listener running on the target, the attacker delivers a file by piping a heredoc-wrapped cat command through a socat connection:

Defending against LOTL techniques requires a shift from simple network alerts to granular process and metadata analysis.
Inbound TCP traffic on port 3031 (the “eppc” port) and unusual SNMP/TFTP traffic on internal LAN segments should be monitored for potential unauthorized activity.
Through mapping to the Open Cybersecurity Schema Framework (OCSF), an open-source effort to deliver a simplified and vendor-agnostic taxonomy for security telemetry, high-fidelity signatures for these behaviors were identified:
launchd -> AppleEventsD -> Terminal -> sh/bash. mdls or writes to “com.apple.metadata:kMDItemFinderComment”. base64 --decode commands originating from GUI applications or osascript executions containing “of machine “eppc://…”” arguments. Several built-in macOS security mechanisms can be configured to mitigate the risks associated with native primitive abuse:
tftpd and snmpd, should be explicitly disabled. The removal of these launchd plists from “/System/Library/LaunchDaemons” (where permitted by System Integrity Protection) or the use of launchctl disable commands prevents their use as ad-hoc data transfer channels. The research presented in this article underscores a fundamental reality of modern endpoint security. The same primitives designed for administrative convenience and system automation are often the most potent tools in an adversary’s arsenal. By moving beyond traditional exploit-based attacks and instead LOTL, attackers can operate within the noise of legitimate system activity.
From the weaponization of the “eppc” protocol to the creative abuse of Spotlight metadata and SNMP traps, it is clear that the macOS attack surface is both vast and nuanced. These techniques demonstrate that even within a “walled garden” ecosystem, native pathways for movement and execution remain accessible to those who understand the underlying architecture.
For defenders, the primary takeaway is that visibility remains the most effective deterrent. By shifting focus from static file analysis to the monitoring of process lineage, inter-process communication, and metadata anomalies, these “bad Apples” can be identified and neutralized. As macOS continues its expansion into the enterprise core, the documentation and detection of these native techniques must remain a priority for the security community.
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