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April 4, 2022

Explore Internet-Facing System Vulnerabilities

Read about 2021's top four incidents and how Darktrace's advanced threat detection technology identified and mitigated vulnerabilities. Learn 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
Sam Lister
Specialist Security Researcher
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04
Apr 2022

By virtue of their exposure, Internet-facing systems (i.e., systems which have ports open/exposed to the wider Internet) are particularly susceptible to compromise. Attackers typically compromise Internet-facing systems by exploiting zero-day vulnerabilities in applications they run. During 2021, critical zero-day vulnerabilities in the following applications were publicly disclosed:

Internet-facing systems running these applications were consequently heavily targeted by attackers. In this post, we will provide examples of compromises of these systems observed by Darktrace’s SOC team in 2021. As will become clear, successful exploitation of weaknesses in Internet-facing systems inevitably results in such systems doing things which they do not normally do. Rather than focusing on identifying attempts to exploit these weaknesses, Darktrace focuses on identifying the unusual behaviors which inevitably ensue. The purpose of this post is to highlight the effectiveness of this approach.

Exchange server compromise

In January, researchers from the cyber security company DEVCORE reported a series of critical vulnerabilities in Microsoft Exchange which they dubbed ‘ProxyLogon’.[1] ProxyLogon consists of a server-side request forgery (SSRF) vulnerability (CVE-2021-26855) and a remote code execution (RCE) vulnerability (CVE-2021-27065). Attackers were observed exploiting these vulnerabilities in the wild from as early as January 6.[2] In April, DEVCORE researchers reported another series of critical vulnerabilities in Microsoft Exchange which they dubbed ‘ProxyShell’.[3] ProxyShell consists of a pre-authentication path confusion vulnerability (CVE-2021-34473), a privilege elevation vulnerability (CVE-2021-34523), and a post-authentication RCE vulnerability (CVE-2021-31207). Attackers were first observed exploiting these vulnerabilities in the wild in August.[4] In many cases, attackers exploited the ProxyShell and ProxyLogon vulnerabilities in order to create web shells on the targeted Exchange servers. The presence of these web shells provided attackers with the means to remotely execute commands on the compromised servers.

In early August 2021, by exploiting the ProxyShell vulnerabilities, an attacker gained the rights to remotely execute PowerShell commands on an Internet-facing Exchange server within the network of a US-based transportation company. The attacker subsequently executed a number of PowerShell commands on the server. One of these commands caused the server to make a 28-minute-long SSL connection to a highly unusual external endpoint. Within a couple of hours, the attacker managed to strengthen their foothold within the network by installing AnyDesk and CobaltStrike on several internal devices. In mid-August, the attacker got the devices on which they had installed Cobalt Strike to conduct network reconnaissance and to transfer terabytes of data to the cloud storage service, MEGA. At the end of August, the attacker got the devices on which they had installed AnyDesk to execute Conti ransomware and to spread executable files and script files to further internal devices.

In this example, the attacker’s exploitation of ProxyShell immediately resulted in the Exchange Server making a long SSL connection to an unusual external endpoint. This connection caused the model Device / Long Agent Connection to New Endpoint to breach. The subsequent reconnaissance, lateral movement, C2, external data transfer, and encryption behavior brought about by the attacker were also picked up by Darktrace’s models.

A non-exhaustive list of the models that breached as a result of the behavior brought about by the attacker:

  • Device / Long Agent Connection to New Endpoint
  • Device / ICMP Address Scan
  • Anomalous Connection / SMB Enumeration
  • Anomalous Server Activity / Outgoing from Server
  • Compromise / Beacon to Young Endpoint
  • Anomalous Server Activity / Rare External from Server
  • Compromise / Fast Beaconing to DGA
  • Compromise / SSL or HTTP Beacon
  • Compromise / Sustained SSL or HTTP Increase
  • Compromise / Beacon for 4 Days
  • Anomalous Connection / Multiple HTTP POSTs to Rare Hostname
  • Unusual Activity / Enhanced Unusual External Data Transfer
  • Anomalous Connection / Data Sent to Rare Domain
  • Anomalous Connection / Uncommon 1 GiB Outbound
  • Compliance / SMB Drive Write
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Anomalous Connection / Suspicious Read Write Ratio
  • Anomalous Connection / Suspicious Read Write Ratio and Unusual SMB
  • Anomalous Connection / Sustained MIME Type Conversion
  • Unusual Activity / Anomalous SMB Move & Write
  • Unusual Activity / Unusual Internal Data Volume as Client or Server
  • Device / Suspicious File Writes to Multiple Hidden SMB Shares
  • Compromise / Ransomware / Suspicious SMB Activity
  • Anomalous File / Internal / Unusual SMB Script Write
  • Anomalous File / Internal / Masqueraded Executable SMB Write
  • Device / SMB Lateral Movement
  • Device / Multiple Lateral Movement Model Breaches

Confluence server compromise

Atlassian’s Confluence is an application which provides the means for building collaborative, virtual workspaces. In the era of remote working, the value of such an application is undeniable. The public disclosure of a critical remote code execution (RCE) vulnerability (CVE-2021-26084) in Confluence in August 2021 thus provided a prime opportunity for attackers to cause havoc. The vulnerability, which arises from the use of Object-Graph Navigation Language (OGNL) in Confluence’s tag system, provides attackers with the means to remotely execute code on vulnerable Confluence server by sending a crafted HTTP request containing a malicious parameter.[5] Attackers were first observed exploiting this vulnerability towards the end of August, and in the majority of cases, attackers exploited the vulnerability in order to install crypto-mining tools onto vulnerable servers.[6]

At the beginning of September 2021, an attacker was observed exploiting CVE-2021-26084 in order to install the crypto-mining tool, XMRig, as well as a shell script, onto an Internet-facing Confluence server within the network of an EMEA-based television and broadcasting company. Within a couple of hours, the attacker installed files associated with the crypto-mining malware, Kinsing, onto the server. The Kinsing-infected server then immediately began to communicate over HTTP with the attacker’s C2 infrastructure. Around the time of this activity, the server was observed using the MinerGate crypto-mining protocol, indicating that the server had begun to mine cryptocurrency.

In this example, the attacker’s exploitation of CVE-2021-26084 immediately resulted in the Confluence server making an HTTP GET request with an unusual user-agent string (one associated with curl in this case) to a rare external IP. This behavior caused the models Device / New User Agent, Anomalous Connection / New User Agent to IP Without Hostname, and Anomalous File / Script from Rare Location to breach. The subsequent file downloads, C2 traffic and crypto-mining activity also resulted in several models breaching.

A non-exhaustive list of the models which breached as a result of the unusual behavior brought about by the attacker:

  • Device / New User Agent
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous File / Script from Rare Location
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Internet Facing System File Download
  • Device / Initial Breach Chain Compromise
  • Anomalous Connection / Posting HTTP to IP Without Hostname
  • Compliance / Crypto Currency Mining Activity
  • Compromise / High Priority Crypto Currency Mining
  • Device / Internet Facing Device with High Priority Alert

GitLab server compromise

GitLab is an application providing services ranging from project planning to source code management. Back in April 2021, a critical RCE vulnerability (CVE-2021-22205) in GitLab was publicly reported by a cyber security researcher via the bug bounty platform, HackerOne.[7] The vulnerability, which arises from GitLab’s use of ExifTool for removing metadata from image files, [8] enables attackers to remotely execute code on vulnerable GitLab servers by uploading specially crafted image files.[9] Attackers were first observed exploiting CVE-2021-22205 in the wild in June/July.[10] A surge in exploitations of the vulnerability was observed at the end of October, with attackers exploiting the flaw in order to assemble botnets.[11] Darktrace observed a significant number of cases in which attackers exploited the vulnerability in order to install crypto-mining tools onto vulnerable GitLab servers.

On October 29, an attacker successfully exploited CVE-2021-22205 on an Internet-facing GitLab server within the network of a UK-based education provider. The organization was trialing Darktrace when this incident occurred. The attacker installed several executable files and shell scripts onto the server by exploiting the vulnerability. The attacker communicated with the compromised server (using unusual ports) for several days, before making the server transfer large volumes of data externally and download the crypto-mining tool, XMRig, as well as the botnet malware, Mirai. The server was consequently observed making connections to the crypto-mining pool, C3Pool.

In this example, the attacker’s exploitation of the vulnerability in GitLab immediately resulted in the server making an HTTP GET request with an unusual user-agent string (one associated with Wget in this case) to a rare external IP. The models Anomalous Connection / New User Agent to IP Without Hostname and Anomalous File / EXE from Rare External Location breached as a result of this behavior. The attacker’s subsequent activity on the server over the next few days resulted in frequent model breaches.

A non-exhaustive list of the models which breached as a result of the attacker’s activity on the server:

  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Multiple EXE from Rare External Locations
  • Anomalous File / Internet Facing Device with High Priority Alert
  • Anomalous File / Script from Rare Location
  • Anomalous Connection / Application Protocol on Uncommon Port
  • Anomalous Connection / Anomalous SSL without SNI to New External
  • Device / Initial Breach Chain Compromise
  • Unusual Activity / Unusual External Data to New IPs
  • Anomalous Server Activity / Outgoing from Server
  • Device / Large Number of Model Breaches from Critical Network Device
  • Anomalous Connection / Data Sent to Rare Domain
  • Compromise / Suspicious File and C2
  • Unusual Activity / Enhanced Unusual External Data Transfer
  • Compliance / Crypto Currency Mining Activity
  • Compliance / High Priority Crypto Currency Mining
  • Anomalous File / Zip or Gzip from Rare External Location
  • Compromise / Monero Mining
  • Device / Internet Facing Device with High Priority Alert
  • Anomalous Server Activity / Rare External from Server
  • Compromise / Slow Beaconing Activity To External Rare
  • Compromise / Beaconing Activity To External Rare
  • Compromise / HTTP Beaconing to Rare Destination
  • Compromise / High Volume of Connections with Beacon Score
  • Anomalous File / Numeric Exe Download

Log4j server compromise

On December 9 2021, a critical RCE vulnerability (dubbed ‘Log4Shell’) in version 2 of Apache’s Log4j was publicly disclosed by researchers at LunaSec.[12] As a logging library present in potentially millions of Java applications,[13] Log4j constitutes an obscured, yet ubiquitous feature of the digital world. The vulnerability (CVE-2021-44228), which arises from Log4j’s Java Naming and Directory Interface (JNDI) Lookup feature, enables an attacker to make a vulnerable server download and execute a malicious Java class file. To exploit the vulnerability, all the attacker must do is submit a specially crafted JNDI lookup request to the server. The fact that Log4j is present in so many applications and that the exploitation of this vulnerability is so simple, Log4Shell has been dubbed the ‘most critical vulnerability of the last decade’.[14] Attackers have been exploiting Log4Shell in the wild since at least December 1.[15] Since then, attackers have been observed exploiting the vulnerability to install crypto-mining tools, Cobalt Strike, and RATs onto vulnerable servers.[16]

On December 10, one day after the public disclosure of Log4Shell, an attacker successfully exploited the vulnerability on a vulnerable Internet-facing server within the network of a US-based architecture company. By exploiting the vulnerability, the attacker managed to get the server to download and execute a Java class file named ‘Exploit69ogQNSQYz.class’. Executing the code in this file caused the server to download a shell script file and a file related to the Kinsing crypto-mining malware. The Kinsing-infected server then went on to communicate over HTTP with a C2 server. Since the customer was using the Proactive Threat Notification (PTN) service, they were immediately alerted to this activity, and the server was subsequently quarantined, preventing crypto-mining activity from taking place.

In this example, the attacker’s exploitation of the zero-day vulnerability immediately resulted in the vulnerable server making an HTTP GET request with an unusual user-agent string (one associated with Java in this case) to a rare external IP. The models Anomalous Connection / Callback on Web Facing Device and Anomalous Connection / New User Agent to IP Without Hostname breached as a result of this behavior. The device’s subsequent file downloads and C2 activity caused several Darktrace models to breach.

A non-exhaustive list of the models which breached as a result of the unusual behavior brought about by the attacker:

  • Anomalous Connection / Callback on Web Facing Device
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous File / Internet Facing System File Download
  • Anomalous File / Script from Rare External Location
  • Device / Initial Breach Chain Compromise
  • Anomalous Connection / Posting HTTP to IP Without Hostname

Round-up

It is inevitable that attackers will attempt to exploit zero-day vulnerabilities in applications running on Internet-facing devices. Whilst identifying these attempts is useful, the fact that attackers regularly exploit new zero-days makes the task of identifying attempts to exploit them akin to a game of whack-a-mole. Whilst it is uncertain which zero-day vulnerability attackers will exploit next, what is certain is that their exploitation of it will bring about unusual behavior. No matter the vulnerability, whether it be a vulnerability in Microsoft Exchange, Confluence, GitLab, or Log4j, Darktrace will identify the unusual behaviors which inevitably result from its exploitation. By identifying unusual behaviors displayed by Internet-facing devices, Darktrace thus makes it almost impossible for attackers to successfully exploit zero-day vulnerabilities without being detected.

For Darktrace customers who want to find out more about detecting potential compromises of internet-facing devices, refer here for an exclusive supplement to this blog.

Thanks to Andy Lawrence for his contributions.

Footnotes

1. https://devco.re/blog/2021/08/06/a-new-attack-surface-on-MS-exchange-part-1-ProxyLogon/

2. https://www.volexity.com/blog/2021/03/02/active-exploitation-of-microsoft-exchange-zero-day-vulnerabilities/

3. https://www.zerodayinitiative.com/blog/2021/8/17/from-pwn2own-2021-a-new-attack-surface-on-microsoft-exchange-proxyshell

4. https://www.rapid7.com/blog/post/2021/08/12/proxyshell-more-widespread-exploitation-of-microsoft-exchange-servers/

5. https://www.kaspersky.co.uk/blog/confluence-server-cve-2021-26084/23376/

6. https://www.bleepingcomputer.com/news/security/atlassian-confluence-flaw-actively-exploited-to-install-cryptominers/

7. https://hackerone.com/reports/1154542

8. https://security.humanativaspa.it/gitlab-ce-cve-2021-22205-in-the-wild/

9.https://about.gitlab.com/releases/2021/04/14/security-release-gitlab-13-10-3-released/

10. https://www.rapid7.com/blog/post/2021/11/01/gitlab-unauthenticated-remote-code-execution-cve-2021-22205-exploited-in-the-wild/

11. https://www.hackmageddon.com/2021/12/16/1-15-november-2021-cyber-attacks-timeline/

12. https://www.lunasec.io/docs/blog/log4j-zero-day/

13. https://www.csoonline.com/article/3644472/apache-log4j-vulnerability-actively-exploited-impacting-millions-of-java-based-apps.html

14. https://www.theguardian.com/technology/2021/dec/10/software-flaw-most-critical-vulnerability-log-4-shell

15. https://www.rapid7.com/blog/post/2021/12/15/the-everypersons-guide-to-log4shell-cve-2021-44228/

16. https://www.microsoft.com/security/blog/2021/12/11/guidance-for-preventing-detecting-and-hunting-for-cve-2021-44228-log4j-2-exploitation/

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
Sam Lister
Specialist Security Researcher

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April 21, 2026

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

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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

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About the author
Joanna Ng
Associate Principal Analyst

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April 17, 2026

Why Behavioral AI Is the Answer to Mythos

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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]

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About the author
Ed Jennings
President and CEO
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