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Introduction: When a Routine Payment Email Becomes a Malware Delivery System
Finance departments have always been attractive targets for cybercriminals because they sit directly at the intersection of money, sensitive information, and business urgency. A single convincing email can turn an ordinary payment-review process into an entry point for credential theft, account takeover, and broader corporate compromise.
A newly described Business Email Compromise (BEC) campaign demonstrates how attackers are combining traditional social engineering with increasingly creative malware-delivery techniques. The campaign reportedly delivers Agent Tesla v4, a long-running Windows information-stealing malware family, through a payment-themed phishing attachment disguised as a legitimate financial document.
What makes this campaign particularly interesting is not simply the malware itself. The real danger lies in the delivery chain. Attackers reportedly hide malicious JScript code behind large numbers of Unicode emoji characters, use a fileless execution technique to keep the final payload out of sight, perform extensive anti-analysis checks, and then deploy a credential-stealing toolkit capable of targeting browsers, email clients, messaging applications, and Windows credentials.
The result is a campaign designed around one fundamental principle: make the victim trust the email while making the malware difficult for security tools to understand.
The Attack Begins With a Convincing Financial Conversation
The campaign reportedly impersonates Metropolitan Bank and Trust Company, a legitimate financial institution in the Philippines. Instead of sending an obviously malicious message filled with grammatical mistakes or suspicious links, the attackers create the appearance of an ongoing business conversation.
The email resembles a forwarded wire-transfer discussion and asks the recipient to review an attached document. The language is designed to feel familiar to employees working in accounting, treasury, accounts payable, and other finance-related roles.
The psychological pressure is equally important. Payment requests often have deadlines, and employees are accustomed to dealing with invoices, bank instructions, SWIFT messages, and transaction confirmations under time pressure.
That creates the perfect environment for social engineering.
An employee who normally investigates an unexpected attachment may become less cautious when the message appears to concern an urgent payment that supposedly requires immediate review.
The Attachment Is Made to Look Like a Payment Document
The malicious attachment is reportedly named “SWIFT Payment Maker 103 – 10.06.26.JS.”
The .JS extension is an important clue, but the file is unusually large, reaching approximately 6.94 MB. For a JavaScript file associated with a payment document, that size should immediately raise suspicion.
The enormous size is reportedly caused by extensive obfuscation. Rather than simply hiding malicious code using conventional encoding techniques, the attackers embedded large quantities of Unicode characters, including emoji such as hearts and water droplets.
This unusual approach serves two purposes.
First, it makes the file difficult for a human analyst to inspect quickly. Second, it can disrupt simplistic security systems that depend heavily on recognizable strings, patterns, or signatures.
The Emoji Trick Is More Than a Visual Gimmick
The use of emojis is one of the most unusual aspects of this campaign.
Windows Script Host can ignore certain characters that do not materially affect the interpretation of the underlying JScript. This means attackers can introduce large amounts of visual noise without necessarily preventing the script from executing.
To a human reviewing the file as text, the result can look chaotic.
To the script interpreter, however, the meaningful portions of the code remain usable.
This illustrates an important cybersecurity lesson: code obfuscation does not always need to make the code mathematically complicated. Sometimes it only needs to make the code difficult for detection systems and humans to recognize.
Why Traditional String-Based Detection Can Struggle
Many defensive technologies examine scripts for suspicious keywords, recognizable payload fragments, or known malicious patterns.
Heavy obfuscation can make that approach less reliable.
If a malicious script contains thousands or millions of irrelevant characters, a scanner may have to normalize and interpret the content before it can identify the meaningful execution logic. Older or simplistic detection mechanisms may instead see a giant, unusual script without immediately recognizing the malicious behavior hidden inside it.
This is why modern detection increasingly relies on behavioral analysis, rather than depending exclusively on static signatures.
No Simple Base64-and-Eval Pattern
Another notable characteristic of the sample is that it reportedly does not depend on the familiar Base64-plus-eval pattern often encountered in malicious JavaScript.
There is also reportedly no need for the script to download another payload from an external server.
That matters because security teams frequently build detection logic around known malware-delivery patterns. When attackers change the execution chain while keeping the ultimate objective unchanged, those assumptions can become less effective.
The campaign therefore demonstrates a broader trend in malware development: attackers are increasingly optimizing not just for execution, but for detection avoidance at every stage.
The Fileless Stage Makes the Attack Harder to See
After execution, the script reportedly creates two files under:
C:UsersPublicLibraries
One is described as a 32-bit .NET loader, while the other uses a .ttf extension despite actually containing encoded payload data.
The extension mismatch is significant.
A file named like a font may appear harmless during a superficial investigation, but the file’s extension does not determine its true contents.
Defenders should therefore avoid treating extensions as trustworthy indicators of file type.
DonutLoader Helps Move the Payload Into Memory
The loader reportedly processes the encoded data using Donut-based shellcode and reflectively injects the final MSIL payload into memory.
This creates an important distinction between what exists on disk and what actually executes.
Traditional antivirus workflows can be particularly effective when malicious executables are simply written to disk and launched. Fileless or memory-oriented execution reduces the amount of conventional executable evidence available for static scanning.
It does not make malware invisible.
Instead, it changes where defenders need to look.
Memory behavior, process relationships, script execution, unusual child processes, .NET loading activity, WMI activity, and suspicious access to credential stores can all become important signals.
The Final Payload Pretends to Be Python
The final payload is reportedly a ConfuserEx-obfuscated .NET 4.0 binary.
Its metadata attempts to disguise the program as “Python 3.11.3 (64-bit)” and identifies the Python Software Foundation as the company.
The disguise is particularly interesting because metadata can influence superficial analysis. An analyst or automated system that relies too heavily on filenames and metadata could incorrectly classify the file.
However, the actual architecture reportedly indicates a 32-bit x86 application, and its runtime characteristics do not correspond to a legitimate Python distribution.
This is another reminder that metadata should be treated as evidence—not truth.
Agent Tesla Performs Its Own Security Screening
Before stealing information, the malware reportedly performs multiple anti-analysis checks.
These checks include debugger detection, cloud-hosting IP identification, timing-based virtual-machine detection, sandbox DLL enumeration, and WMI queries designed to identify virtualization technologies such as VMware, VirtualBox, and Hyper-V.
This behavior is designed to answer a simple question:
“Am I running on a real
If the malware believes it has entered a research environment, automated sandbox, or suspicious infrastructure, it can terminate execution.
Why Anti-Sandbox Techniques Matter
Security researchers routinely detonate suspicious files inside controlled environments.
Attackers know this.
As a result, modern malware increasingly attempts to identify virtual machines, analysis frameworks, cloud environments, debuggers, and other indicators associated with cybersecurity research.
Agent Tesla is not unique in using such techniques, but its presence in this campaign reinforces how mature information stealers have become.
The malware is no longer simply trying to infect a machine.
It is trying to understand where it is before deciding what to do next.
The Credential-Theft Arsenal Is Extensive
Once the malware decides that the environment is suitable, its primary objective is information theft.
The analyzed Agent Tesla sample reportedly contains 21 credential-harvesting modules, with support for 27 Chromium-based browsers and 13 Mozilla-based browsers.
The targeted applications reportedly include Chrome, Microsoft Edge, Brave, Opera, Vivaldi, Firefox, and Thunderbird.
For an organization, this creates a potentially serious exposure because browser credentials frequently contain access to email, cloud platforms, corporate portals, VPN services, financial applications, and SaaS environments.
Browser Credentials Are Valuable to Attackers
Modern browsers do not simply store passwords in plain text. They use encryption mechanisms and operating-system protections such as DPAPI.
The malware reportedly attempts to extract browser master keys and decrypt Chrome v10 and v11 credentials using DPAPI and AES-GCM.
It also reportedly accesses locked SQLite databases through custom parsing and file-handle techniques.
This is significant because credential theft is increasingly about bypassing the protections surrounding credential databases rather than merely reading a password file.
Email and Messaging Accounts Become Secondary Targets
Agent Tesla reportedly goes beyond browsers.
Additional modules target Outlook, Foxmail, Thunderbird contacts, Windows Credential Manager, and Discord.
The Discord component is particularly notable because the malware searches LevelDB data for OAuth2 session tokens.
A stolen session token can potentially provide an attacker with authenticated access without requiring the victim to type a password again.
This illustrates why organizations should not assume that changing a password always ends an account compromise.
If an active session or authentication token has been stolen, defenders may also need to revoke sessions, rotate credentials, invalidate tokens, and investigate associated activity.
Keylogging and Clipboard Theft Add Another Layer
The analyzed build reportedly contains functional keylogging and clipboard-capture components, although those features were disabled in the sample examined.
Even when such capabilities are inactive, their presence demonstrates the broader design philosophy behind Agent Tesla.
An information stealer does not need to focus on one type of credential.
It can potentially collect information from multiple sources and wait for the right opportunity.
Clipboard contents are especially interesting because employees frequently copy passwords, payment details, cryptocurrency addresses, authentication codes, API keys, and sensitive business information.
The Bigger Picture: BEC Is Becoming More Technical
The campaign demonstrates how BEC and malware delivery are increasingly converging.
Traditional BEC attacks often focused on manipulating employees into transferring money directly. Malware campaigns, meanwhile, focused on gaining technical access.
Modern operations can combine both.
A fraudulent payment conversation can persuade an employee to open an attachment. The attachment can deploy an infostealer. The infostealer can harvest browser credentials and session tokens. Those credentials can then provide attackers with access to email and cloud services.
That access can ultimately support additional fraud.
The phishing email is therefore only the first stage of a much larger attack chain.
Deep Analysis: Breaking Down the Execution and Detection Chain
Stage One: Social Engineering
The attack begins with a payment-related email that attempts to establish credibility through financial terminology, institutional impersonation, an apparently legitimate conversation, and urgency.
The strongest defense at this stage is not a malware signature.
It is verification.
Employees should independently confirm unusual payment instructions using trusted communication channels rather than replying directly to the suspicious message.
Stage Two: Script-Based Execution
The .JS attachment represents an immediate warning sign.
Organizations that have no legitimate business requirement for employees to receive and execute JavaScript files should consider blocking or heavily restricting such attachments at email gateways.
A useful Windows investigation command is:
Get-ChildItem "C:\Users\Public\Libraries" -Force | Select-Object Name,Length,Extension,CreationTime,LastWriteTime
This can help investigators identify unexpected files appearing in the suspicious directory.
Stage Three: Identify Extension and File-Type Mismatches
Defenders should not trust extensions.
For suspicious files, administrators can calculate hashes and inspect their actual content:
Get-ChildItem "C:\Users\Public\Libraries" -File |
Get-FileHash -Algorithm SHA256
Security teams can then compare the hashes against internal telemetry and trusted threat-intelligence sources.
Stage Four: Investigate Script Activity
PowerShell can help identify recent script-related process activity:
Get-CimInstance Win32_Process |
Where-Object {$_.CommandLine -match '.js|wscript|cscript'} |
Select-Object ProcessId,ParentProcessId,Name,CommandLine
The purpose is not to assume that every wscript.exe or cscript.exe process is malicious.
The objective is to identify unexpected relationships between users, scripts, parent processes, and files.
Stage Five: Monitor Suspicious .NET Activity
The reported execution chain uses a .NET loader before reflective loading of the final payload.
EDR telemetry should therefore be examined for unusual .NET processes, memory allocation behavior, reflective loading indicators, suspicious child processes, and applications loading unexpected assemblies.
A strong investigation should correlate process activity with the original email, attachment hash, user identity, host, and network events.
Stage Six: Look for Anti-Analysis Behavior
WMI queries involving virtualization technologies can be legitimate, but unexpected combinations of WMI inspection, debugger detection, sandbox checks, and suspicious script execution should increase the risk score.
Useful telemetry includes:
Get-CimInstance Win32_ComputerSystem | Select-Object Manufacturer,Model,SystemType
and:
Get-CimInstance Win32_BIOS | Select-Object Manufacturer,SMBIOSBIOSVersion
These commands are defensive inventory checks. They can help analysts understand what environment a suspicious process was running in.
Stage Seven: Hunt for Credential Access
If Agent Tesla is suspected, investigation should not stop at the infected executable.
Security teams should review browser credential access, Windows Credential Manager activity, unusual access to browser databases, suspicious access to Thunderbird or Outlook data, and unexpected interaction with Discord storage.
The question should be:
“What information could have been stolen before the malware was discovered?”
Stage Eight: Search for Suspicious Persistence and Follow-On Activity
After an infection, defenders should investigate scheduled tasks, Run keys, startup folders, services, browser extensions, and other persistence mechanisms.
A simple defensive check for common Run keys can be performed with:
Get-ItemProperty <code>"HKCU:\Software\Microsoft\Windows\CurrentVersion\Run"</code> -ErrorAction SilentlyContinue
This is only one part of a broader investigation and should never be treated as proof that a system is clean.
Stage Nine: Build Behavioral Detection
A strong detection rule should not depend exclusively on the filename “SWIFT Payment Maker 103 – 10.06.26.JS.”
Attackers can rename a file in seconds.
Instead, detection should combine multiple signals: JavaScript attachment delivery, execution through Windows Script Host, unusual files in public directories, suspicious .NET loading, credential-store access, virtualization checks, and abnormal browser database activity.
The more independent signals that converge, the stronger the detection becomes.
Stage Ten: Example YARA Hunting Concept
For malware-hunting teams, a YARA rule can be designed around suspicious characteristics rather than a single filename.
rule Suspicious_Large_JScript_Emoji_Obfuscation
{
meta:
description = "Hunt for unusually large JScript files containing extensive Unicode obfuscation" author = "Defensive Threat Hunting" purpose = "Detection and investigation"
strings:
$js1 = WScript ascii nocase
$js2 = ActiveXObject ascii nocase
$js3 = Scripting.FileSystemObject ascii nocase
condition:
filesize > 1MB and 2 of ($js) }
This should be treated as a hunting starting point, not a production-ready Agent Tesla signature.
Production detection should be tuned against the
What Undercode Say:
- The Email Is the Real Beginning of the Attack
The most important lesson is that the malware did not begin with code.
It began with trust.
2. Finance Teams Remain High-Value Targets
Employees responsible for payments naturally receive documents from banks, vendors, customers, and executives.
That makes suspicious attachments difficult to distinguish from legitimate business correspondence.
3. Urgency Is a Weapon
The pressure to approve or investigate a payment quickly can override normal security instincts.
Attackers understand this psychological weakness.
4. Impersonation Still Works
Even sophisticated malware campaigns continue to rely on recognizable institutions and believable financial scenarios.
Technology does not eliminate social engineering.
- The Emoji Technique Shows How Detection Is Evolving
Attackers are experimenting with unusual characters because defenders increasingly recognize traditional obfuscation.
The arms race is moving toward more creative forms of concealment.
6. File Size Can Become a Signal
A nearly 7 MB JavaScript attachment associated with a payment document is inherently unusual.
Organizations can use file size and file type together as risk signals.
7. Extensions Should Never Be Trusted
A .ttf file may not actually be a font.
A .pdf file may not actually be a PDF.
Security controls should inspect content and behavior rather than relying on extensions.
8. Fileless Execution Changes the Defensive Battlefield
When the final payload exists primarily in memory, conventional file scanning becomes less powerful.
EDR and memory-aware detection therefore become increasingly important.
9. Metadata Can Lie
The fake Python identity demonstrates why file metadata should never be accepted without verification.
Architecture, behavior, signatures, imports, execution patterns, and provenance provide stronger evidence.
10. Anti-Analysis Is Now Normalized
Virtual-machine detection and debugger checks are no longer exotic capabilities.
They are common features across modern malware families.
11. Sandbox Evasion Creates a Visibility Problem
A malicious file can appear harmless during automated analysis and behave differently on a real employee workstation.
This is why behavioral telemetry outside the sandbox matters.
12. Browser Credentials Are High-Value Assets
Attackers increasingly understand that browsers contain enormous quantities of business information.
Compromising browser credentials can become a gateway into the entire organization.
13. Session Tokens Are Particularly Dangerous
A stolen authenticated session can sometimes bypass the normal password-entry process.
Incident response must therefore include session revocation.
- Password Resets Alone May Not Be Enough
If credentials were stolen, organizations should determine whether authentication tokens, cookies, or sessions were also compromised.
Otherwise, an attacker may retain access.
15. Information Stealers Are Becoming Multi-Purpose Tools
Agent Tesla does not focus on one application.
Its collection modules demonstrate the value attackers place on having many independent sources of information.
16. Clipboard Monitoring Deserves More Attention
Employees routinely copy sensitive information.
The clipboard can therefore become an unexpected source of valuable data.
17. Disabled Features Still Matter
The presence of keylogging and clipboard functionality demonstrates the malware’s broader capabilities even when those components are inactive in a particular sample.
Different builds can behave differently.
- BEC and Infostealers Can Reinforce Each Other
BEC can provide the social engineering mechanism.
An infostealer can provide the credentials.
Together, they can create a much more dangerous operation.
- The Attack Chain Is More Important Than the Malware Name
Organizations should not build their entire defense around detecting Agent Tesla.
They should detect suspicious behavior that could also indicate other malware families.
20. Defense Must Be Layered
Email filtering, endpoint protection, application control, identity security, employee training, and incident response all need to work together.
No single control is sufficient.
- Blocking Script Attachments Can Have Significant Value
For organizations that do not require JavaScript attachments, blocking them at the email gateway can eliminate an entire class of delivery mechanisms.
22. Application Control Can Reduce Risk
Restricting unauthorized script interpreters and controlling where scripts can execute can make exploitation substantially harder.
23. Public Directories Deserve Monitoring
Unexpected executable or encoded content appearing under publicly writable directories should receive attention.
24. Memory Telemetry Is Becoming More Important
As attackers move payloads into memory, defenders need visibility into memory allocation, injection, and suspicious module-loading behavior.
25. Identity Telemetry Is Equally Important
An endpoint compromise becomes far more dangerous when stolen credentials are used successfully.
Identity systems should therefore be monitored alongside endpoints.
- Unusual Login Geography Can Become a Clue
A stolen credential may later be used from infrastructure unrelated to the employee’s normal activity.
Identity analytics can help identify that transition.
- MFA Helps but Does Not Solve Everything
Strong authentication reduces the impact of stolen passwords, but session theft and token abuse can introduce additional risks.
Authentication needs to be combined with endpoint security.
28. Finance Employees Need Scenario-Based Training
Generic warnings about “phishing” are less effective than realistic examples involving invoices, SWIFT transfers, bank confirmations, and payment approvals.
Training should reflect actual workflows.
29. Verification Procedures Should Be Simple
If employees have to navigate a complicated verification process, they may bypass it during an urgent transaction.
Security procedures should be fast and practical.
30. Independent Verification Is Critical
A suspicious payment request should be confirmed through a trusted channel rather than through the contact information contained in the suspicious email.
31. Detection Should Correlate Events
An email attachment, script execution, file creation, .NET process, browser database access, and suspicious login should be considered parts of the same investigation when they involve the same endpoint and user.
32. Threat Hunting Should Look for Patterns
The filename can change.
The malware can change.
The infrastructure can change.
Behavioral patterns are harder for attackers to change without sacrificing functionality.
33. Attackers Are Learning From Detection
Every time defenders develop a reliable signature, attackers have an incentive to change their implementation.
That is why adaptive detection is essential.
- Obfuscation Is Not a Defense Against Good Telemetry
Emoji characters may confuse static inspection, but they cannot hide the fact that an employee launched an unusual script that created suspicious files and accessed sensitive credential stores.
35. Endpoint Isolation Remains Essential
When an infostealer is discovered, rapid containment can prevent additional credential theft and limit follow-on activity.
36. Incident Response Should Assume Credential Exposure
If a mature infostealer executed successfully, organizations should investigate what credentials and sessions may have been accessible during the infection window.
37. Browser Sessions Should Be Considered Compromised
Where evidence indicates browser credential theft, defenders should consider session invalidation and credential rotation as part of remediation.
38. Threat Intelligence Can Accelerate Investigation
Hashes, filenames, infrastructure indicators, malware configurations, and behavioral indicators can help security teams determine whether related systems were exposed.
39. The Human Element Remains Central
Even the most advanced malware requires a delivery mechanism.
In this campaign, that mechanism is a believable financial conversation.
40. The Biggest Lesson Is Simple
The most dangerous phishing attacks are not necessarily the ones that look obviously malicious.
They are the ones that look normal.
✅ Agent Tesla Is an Information-Stealing Malware Family
The supplied report correctly characterizes Agent Tesla as an infostealer capable of collecting credentials and other sensitive information.
Its long-running presence in malware campaigns makes it a relevant threat to Windows environments.
The specific capabilities available can vary between Agent Tesla versions and individual builds.
✅ Script-Based Delivery and Obfuscation Are Consistent With Modern Malware Techniques
Using malicious scripts, obfuscation, and indirect execution mechanisms is a well-established method for attempting to bypass security controls.
The described Unicode-obfuscation technique is technically plausible and represents an evolution of script concealment.
However, the exact implementation should be validated against the original malware sample before being treated as a universal Agent Tesla characteristic.
✅ Anti-Analysis Techniques Are Plausible
Debugger detection, virtual-machine checks, WMI-based environment discovery, and sandbox evasion are all established malware behaviors.
These techniques can make automated analysis more difficult.
They should therefore be considered important behavioral indicators during investigation.
✅ Credential Theft Claims Match the General Behavior of Infostealers
Browser credentials, Windows credentials, email information, and application tokens are highly valuable to attackers.
The reported focus on multiple browsers and communication applications is consistent with the broader evolution of credential-stealing malware.
⚠️ The Exact “21 Modules” and “27 Chromium / 13 Mozilla” Figures Require Sample-Level Verification
Those numbers appear to describe the particular Agent Tesla build analyzed in the referenced research rather than every Agent Tesla version.
They should therefore not be interpreted as universal capabilities of the entire malware family.
The same caution applies to the exact applications and cryptographic mechanisms identified in the sample.
⚠️ The Metropolitan Bank Impersonation Detail Should Be Treated as Campaign-Specific
The supplied article identifies Metropolitan Bank and Trust Company as the impersonated institution.
That does not mean the legitimate bank is connected to the operation.
It is presented as part of the
Prediction
(+1) Defensive Detection Will Shift Further Toward Behavior
Security products are likely to place even greater emphasis on behavioral telemetry as attackers continue developing unusual obfuscation techniques.
Simple signatures based on filenames, extensions, or recognizable strings will remain useful, but they will increasingly be supplemented by process, memory, identity, and endpoint behavior.
(+1) Finance Departments Will Receive More Specialized Phishing Attacks
Payment workflows provide attackers with a powerful combination of urgency, authority, and financial motivation.
We should expect more campaigns built around invoices, SWIFT documents, bank confirmations, supplier payments, payroll files, and executive approvals.
(+1) Fileless and Memory-Based Malware Will Remain a Major Defensive Challenge
Attackers have strong incentives to reduce the amount of malicious code written directly to disk.
As a result, EDR, memory inspection, process correlation, and identity telemetry will become increasingly important in detecting sophisticated infostealers.
(-1) Trusting Email Attachments Will Become Increasingly Dangerous
Organizations that continue allowing employees to freely execute scripts and unfamiliar file types from email will remain exposed to preventable attacks.
The combination of social engineering and technically sophisticated payload delivery creates too many opportunities for attackers.
(-1) A Single Password Reset Will Not Always Resolve an Infection
When malware can steal credentials and potentially authenticated session information, remediation must go beyond changing one password.
Organizations will increasingly need coordinated credential rotation, session invalidation, endpoint containment, malware eradication, and identity monitoring.
Final Thoughts: The Emoji Is the Distraction, the Credential Theft Is the Goal
The most fascinating part of this campaign may be the use of emojis to conceal malicious JScript, but that should not distract from the larger threat.
The emojis are merely the camouflage.
The payment email is the lure.
The script is the delivery mechanism.
The in-memory loader is the evasion layer.
And the stolen credentials are the prize.
Agent Tesla demonstrates why modern malware defense cannot depend on one detection technique. Attackers can disguise code, manipulate metadata, hide payloads in memory, test whether they are being analyzed, and target multiple sources of credentials after gaining execution.
For organizations, the answer is not simply to search for a file named “SWIFT Payment Maker 103 – 10.06.26.JS.” The stronger strategy is to recognize the entire behavioral chain.
A finance employee unexpectedly receives a JavaScript attachment. The file is unusually large. Windows Script Host launches it. New files appear inside a public directory. A suspicious .NET process begins executing. The process performs virtualization checks. Browser databases and credential stores are accessed. Shortly afterward, unusual authentication activity appears.
Individually, each event might be explainable.
Together, they tell a very different story.
That is where modern cybersecurity needs to focus: not on whether one suspicious file looks malicious, but on whether the entire sequence of behavior makes sense.
In an era when attackers can hide malicious code behind emojis and move payloads directly into memory, the safest assumption is simple:
If a payment email creates urgency, demands an attachment review, and asks an employee to trust something that cannot be independently verified, stop and verify before opening it.
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References:
Reported By: cyberpress.org
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