Blog
/
Email
/
August 10, 2022

Bytesize Security: A Guide to HTML Phishing Attachments

Darktrace guides you through the common signs of HTML phishing attachments, including common phishing emails, clever impersonations, fake webpages, and more.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Connor Mooney
SOC Analyst
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
10
Aug 2022

Common phishing emails

One of the most common types of phishing email seen by the Darktrace SOC, involves the use of HTML attachments (Figure 1). These emails make use of an attachment to hide redirects to overtly malicious or suspicious domains. Some even impersonate legitimate web pages and send any entered or captured information back to the attacker's infrastructure once opened or filled out by the recipient. Indicators of these attempts can be identified from a few key patterns found across multiple emails.

Figure 1: An example of a suspicious HTML attachment containing dynamic content

A typical feature of these HTML attachments is the use of a generic-sounding filename that relates to the message's subject line, but with no specific information pertaining to the recipient or their line of business. These files almost always contain some form of Javascript code, as they often make use of external Javascript libraries to accomplish whatever goal is being pursued. For example, an attacker might use Javascript to convincingly impersonate a trustworthy website and trick the recipient into providing credentials or sensitive information, or they might use it to deploy malware and get a foothold on the device for further compromise once opened. This can be further identified by the presence of certain links in the HTML file itself (Figure 2).

Figure 2: The HTML file previously referenced contained multiple rare and suspicious links

Figure 2 above is an example of an HTML file containing multiple links with calls for .js files. This shows that the attachment contains Javascript and is making calls for external libraries for an undetermined purpose. 

Another common red flag is when the file contains links to common Product or Service images from domains wholly unrelated to those services, as seen below (Figure 3).

Figure 3: An example of an unusual .png call from a rare domain. The subsequent image called is for a company with no apparent relation to the hosting domain

The examples above imply an obvious (and poor) attempt by the HTML file to impersonate a Microsoft webpage, likely a fake login page set up for credential harvesting, as the ‘Microsoft’ logo is being pulled from a domain entirely unrelated to Microsoft or any common image-hosting service. 

Rather than impersonating a website directly in the file and loading resources from external sources, these HTML files will instead directly point toward a webpage that already contains these elements. This comes with its own set of pros and cons: by hosting their phishing page in a public setting, they are far more likely to be taken down, however it may be easier to appear legitimate than if they were to build it all out in the HTML file itself. 

The final routine element in these types of HTML phishing emails is the mechanism by which the attacker intends to receive any successfully scammed credentials or information. If the fake webpage is entirely contained in the HTML file, this often presents as a suspicious PHP link present in the file itself (Figure 4).

Figure 4: Phishing HTMLs often include links to rare domains with PHP destinations as an indication that it will engage in some form of HTTP POST communication

PHP calls suggest that some part of the webpage is intended to submit an HTTP POST or equivalent ‘submission’ call, often present in the ‘Login’ button in these scenarios. After the victim clicks this button, the webpage sends all the form-submission items to the endpoint hosting the PHP page, which is commonly an indicator of the webserver hosting the attacker infrastructure running the phishing attack.

If the HTML file redirects to an externally hosted phishing page, identical PHP links are often found in the source code of those pages (Figure 5). This serves the same function as sending any entered credentials back to the attacker.

Figure 5: The source-code of an external-hosted phishing page, showing calls for PHP pages hosted on alternate attacker infrastructure

The process of HTML attacks is so standardized that they are commonly released in the form of easily deployable phishing kits. These can be deployed on unsuspecting compromised webservers with little to no modification, resulting in virtually identical attacks being seen year-round. WordPress seems to be a prime target for hosting such attacks, with the site owners often becoming unsuspecting victims in propagating these phishing campaigns. An unfortunate side effect of these kits being readily available is that the attackers often don't bother to set any sort of access restrictions on their phishing servers once established, which can result in their entire setup being publicly viewable with a simple link modification. One example is seen below (Figure 6).

Figure 6: The parent directory of the website hosting a suspicious PHP page was fully accessible without restriction

In this incident, the website hosting the PHP link seen earlier had a publicly accessible parent directory structure, where both the PHP file above and an additional suspicious .txt file could be seen. This .txt file appears to be where any information submitted by victims ultimately ended up written to (Figure 7).

Figure 7: The TXT file in the parent directory above appeared to contain the login information that was likely submitted to the PHP page referred to in the initial HTML attachment

Figure 7 above presents the unusual risk of not only having the victims’ credentials at the disposal of the original attacker, but also potentially exposed to any malicious actor that can get creative with a web-crawler to identify key elements of the files used by these particular phishing kits. 

Fortunately, due to the standardized nature of these ready-made phishing kits, these types of attacks often conform to a series of common behaviors that Darktrace / EMAIL excels in identifying. Despite being a popular technique, it is extremely rare for attempts using this HTML attachment method to successfully get through a correct Darktrace / EMAIL  deployment. Overall, this means one less risk for the end user to worry about.

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Connor Mooney
SOC Analyst

More in this series

No items found.

Blog

/

Network

/

April 21, 2026

How a Compromised eScan Update Enabled Multi‑Stage Malware and Blockchain C2

multi-stage malwareDefault blog imageDefault blog image

The rise of supply chain attacks

In recent years, the abuse of trusted software has become increasingly common, with supply chain compromises emerging as one of the fastest growing vectors for cyber intrusions. As highlighted in Darktrace’s Annual Threat Report 2026, attackers and state-actors continue to find significant value in gaining access to networks through compromised trusted links, third-party tools, or legitimate software. In January 2026, a supply chain compromise affecting MicroWorld Technologies’ eScan antivirus product was reported, with malicious updates distributed to customers through the legitimate update infrastructure. This, in turn, resulted in a multi‑stage loader malware being deployed on compromised devices [1][2].

An overview of eScan exploitation

According to eScan’s official threat advisory, unauthorized access to a regional update server resulted in an “incorrect file placed in the update distribution path” [3]. Customers associated with the affected update servers who downloaded the update during a two-hour window on January 20 were impacted, with affected Windows devices subsequently have experiencing various errors related to update functions and notifications [3].

While eScan did not specify which regional update servers were affected by the malicious update, all impacted Darktrace customer environments were located in the Europe, Middle East, and Africa (EMEA) region.

External research reported that a malicious 32-bit executable file , “Reload.exe”, was first installed on affected devices, which then dropped the 64-bit downloader, “CONSCTLX.exe”. This downloader establishes persistence by creating scheduled tasks such as “CorelDefrag”, which are responsible for executing PowerShell scripts. Subsequently, it evades detection by tampering with the Windows HOSTS file and eScan registry to prevent future remote updates intended for remediation. Additional payloads are then downloaded from its command-and-control (C2) server [1].

Darktrace’s coverage of eScan exploitation

Initial Access and Blockchain as multi-distributed C2 Infrastructure

On January 20, the same day as the aforementioned two‑hour exploit window, Darktrace observed multiple devices across affected networks downloading .dlz package files from eScan update servers, followed by connections to an anomalous endpoint, vhs.delrosal[.]net, which belongs to the attackers’ C2 infrastructure.

The endpoint contained a self‑signed SSL certificate with the string “O=Internet Widgits Pty Ltd, ST=SomeState, C=AU”, a default placeholder commonly used in SSL/TLS certificates for testing and development environments, as well as in malicious C2 infrastructure [4].

Utilizing a multi‑distributed C2 infrastructure, the attackers also leveraged domains linked with the Solana open‑source blockchain for C2 purposes, namely “.sol”. These domains were human‑readable names that act as aliases for cryptocurrency wallet addresses. As browsers do not natively resolve .sol domains, the Solana Naming System (formerly known as Bonfida, an independent contributor within the Solana ecosystem) provides a proxy service, through endpoints such as sol-domain[.]org, to enable browser access.

Darktrace observed devices connecting to blackice.sol-domain[.]org, indicating that attackers were likely using this proxy to reach a .sol domain for C2 activity. Given this behavior, it is likely that the attackers leveraged .sol domains as a dead drop resolver, a C2 technique in which threat actors host information on a public and legitimate service, such as a blockchain. Additional proxy resolver endpoints, such as sns-resolver.bonfida.workers[.]dev, were also observed.

Solana transactions are transparent, allowing all activity to be viewed publicly. When Darktrace analysts examined the transactions associated with blackice[.]sol, they observed that the earliest records dated November 7, 2025, which coincides with the creation date of the known C2 endpoint vhs[.]delrosal[.]net as shown in WHOIS Lookup information [4][5].

WHOIS Look records of the C2 endpoint vhs[.]delrosal[.]net.
Figure 1: WHOIS Look records of the C2 endpoint vhs[.]delrosal[.]net.
 Earliest observed transaction record for blackice[.]sol on public ledgers.
Figure 2: Earliest observed transaction record for blackice[.]sol on public ledgers.

Subsequent instructions found within the transactions contained strings such as “CNAME= vhs[.]delrosal[.]net”, indicating attempts to direct the device toward the malicious endpoint. A more recent transaction recorded on January 28 included strings such as “hxxps://96.9.125[.]243/i;code=302”, suggesting an effort to change C2 endpoints. Darktrace observed multiple alerts triggered for these endpoints across affected devices.

Similar blockchain‑related endpoints, such as “tumama.hns[.]to”, were also observed in C2 activities. The hns[.]to service allows web browsers to access websites registered on Handshake, a decentralized blockchain‑based framework designed to replace centralized authorities and domain registries for top‑level domains. This shift toward decentralized, blockchain‑based infrastructure likely reflects increased efforts by attackers to evade detection.

In outgoing connections to these malicious endpoints across affected networks, Darktrace / NETWORK recognized that the activity was 100% rare and anomalous for both the devices and the wider networks, likely indicative of malicious beaconing, regardless of the underlying trusted infrastructure. In addition to generating multiple model alerts to capture this malicious activity across affected networks, Darktrace’s Cyber AI Analyst was able to compile these separate events into broader incidents that summarized the entire attack chain, allowing customers’ security teams to investigate and remediate more efficiently. Moreover, in customer environments where Darktrace’s Autonomous Response capability was enabled, Darktrace took swift action to contain the attack by blocking beaconing connections to the malicious endpoints, even when those endpoints were associated with seemingly trustworthy services.

Conclusion

Attacks targeting trusted relationships continue to be a popular strategy among threat actors. Activities linked to trusted or widely deployed software are often unintentionally whitelisted by existing security solutions and gateways. Darktrace observed multiple devices becoming impacted within a very short period, likely because tools such as antivirus software are typically mass‑deployed across numerous endpoints. As a result, a single compromised delivery mechanism can greatly expand the attack surface.

Attackers are also becoming increasingly creative in developing resilient C2 infrastructure and exploiting legitimate services to evade detection. Defenders are therefore encouraged to closely monitor anomalous connections and file downloads. Darktrace’s ability to detect unusual activity amidst ever‑changing tactics and indicators of compromise (IoCs) helps organizations maintain a proactive and resilient defense posture against emerging threats.

Credit to Joanna Ng (Associate Principal Cybersecurity Analyst) and Min Kim (Associate Principal Cybersecurity Analyst) and Tara Gould (Malware Researcher Lead)

Edited by Ryan Traill (Content Manager)

Appendices

Darktrace Model Detections

  • Anomalous File::Zip or Gzip from Rare External Location
  • Anomalous Connection / Suspicious Self-Signed SSL
  • Anomalous Connection / Rare External SSL Self-Signed
  • Anomalous Connection / Suspicious Expired SSL
  • Anomalous Server Activity / Anomalous External Activity from Critical Network Device

List of Indicators of Compromise (IoCs)

  • vhs[.]delrosal[.]net – C2 server
  • tumama[.]hns[.]to – C2 server
  • blackice.sol-domain[.]org – C2 server
  • 96.9.125[.]243 – C2 Server

MITRE ATT&CK Mapping

  • T1071.001 - Command and Control: Web Protocols
  • T1588.001 - Resource Development
  • T1102.001 - Web Service: Dead Drop Resolver
  • T1195 – Supple Chain Compromise

References

[1] https://www.morphisec.com/blog/critical-escan-threat-bulletin/

[2] https://www.bleepingcomputer.com/news/security/escan-confirms-update-server-breached-to-push-malicious-update/

[3] hxxps://download1.mwti.net/documents/Advisory/eScan_Security_Advisory_2026[.]pdf

[4] https://www.virustotal.com/gui/domain/delrosal.net

[5] hxxps://explorer.solana[.]com/address/2wFAbYHNw4ewBHBJzmDgDhCXYoFjJnpbdmeWjZvevaVv

Continue reading
About the author
Joanna Ng
Associate Principal Analyst

Blog

/

/

April 17, 2026

Why Behavioral AI Is the Answer to Mythos

mythos behavioral aiDefault blog imageDefault blog image

How AI is breaking the patch-and-prevent security model

The business world was upended last week by the news that Anthropic has developed a powerful new AI model, Claude Mythos, which poses unprecedented risk because of its ability to expose flaws in IT systems.  

Whether it’s Mythos or OpenAI’s GPT-5.4-Cyber, which was just announced on Tuesday, supercharged AI models in the hands of hackers will allow them to carry out attacks at machine speed, much faster than most businesses can stop them.  

This news underscores a stark reality for all leaders: Patching holes alone is not a sufficient control against modern cyberattacks. You must assume that your software is already vulnerable right now. And while LLMs are very good at spotting vulnerabilities, they’re pretty bad at reliably patching them.

Project Glasswing members say it could take months or years for patches to be applied. While that work is done, enterprises must be protected against Zero-Day attacks, or security holes that are still undiscovered.  

Most cybersecurity strategies today are built like a daily multivitamin: broad, preventative, and designed to keep the system generally healthy over time. Patch regularly. Update software. Reduce known vulnerabilities. It’s necessary, disciplined, and foundational. But it’s also built for a world where the risks are well known and defined, cycles are predictable, and exposure unfolds at a manageable pace.

What happens when that model no longer holds?

The AI cyber advantage: Behavioral AI

The vulnerabilities exposed by AI systems like Mythos aren’t the well-understood risks your “multivitamin” was designed to address. They are transient, fast-emerging entry points that exist just long enough to be exploited.

In that environment, prevention alone isn’t enough. You don’t need more vitamins—you need a painkiller. The future of cybersecurity won’t be defined by how well you maintain baseline health. It will be defined by how quickly you respond when something breaks and every second counts.

That’s why behavioral AI gives businesses a durable cyber advantage. Rather than trying to figure out what the attacker looks like, it learns what “normal” looks like across the digital ecosystem of each individual business.  

That’s exactly how behavioral AI works. It understands the self, or what's normal for the organization, and then it can spot deviations in from normal that are actually early-stage attacks.

The Darktrace approach to cybersecurity

At Darktrace, we’ve been defending our 10,000 customers using behavioral AI cybersecurity developed in our AI Research Centre in Cambridge, U.K.

Darktrace was built on the understanding that attacks do not arrive neatly labeled, and that the most damaging threats often emerge before signatures, indicators, or public disclosures can catch up.  

Our AI algorithms learn in real time from your personalized business data to learn what’s normal for every person and every asset, and the flows of data within your organization. By continuously understanding “normal” across your entire digital ecosystem, Darktrace identifies and contains threats emerging from unknown vulnerabilities and compromised supply chain dependencies, autonomously curtailing attacks at machine speed.  

Security for novel threats

Darktrace is built for a world where AI is not just accelerating attacks, but fundamentally reshaping how they originate. What makes our AI so unique is that it's proven time and again to identify cyber threats before public vulnerability disclosures, such as critical Ivanti vulnerabilities in 2025 and SAP NetWeaver exploitations tied to nation-state threat actors.  

As AI reshapes how vulnerabilities are found and exploited, cybersecurity must be anchored in something more durable than a list of known flaws. It requires a real-time understanding of the business itself: what belongs, what does not, and what must be stopped immediately.

What leaders should do right now

The leadership priority must shift accordingly.

First, stop treating unknown vulnerabilities as an edge case. AI‑driven discovery makes them the norm. Security programs built primarily around known flaws, signatures, and threat intelligence will always lag behind an attacker that is operating in real time.

Second, insist on an understanding of what is actually normal across the business. When threats are novel, labels are useless. The earliest and most reliable signal of danger is abnormal behavior—systems, users, or data flows that suddenly depart from what is expected. If you cannot see that deviation as it happens, you are effectively blind during the most critical window.

Finally, assume that the next serious incident will occur before remediation guidance is available. Ask what happens in those first minutes and hours. The organizations that maintain resilience are not the ones waiting for disclosure cycles to catch up—they are the ones that can autonomously identify and contain emerging threats as they unfold.

This is the reality of cybersecurity in an AI‑shaped world. Patching and prevention remain important foundations, but the advantage now belongs to those who can respond instantly when the unpredictable occurs.

Behavioral AI is security designed not just for known threats, but for the ones that AI will discover next.

[related-resource]

Continue reading
About the author
Ed Jennings
President and CEO
Your data. Our AI.
Elevate your network security with Darktrace AI