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April 8, 2024

Balada Injector: Darktrace’s Investigation into the Malware Exploiting WordPress Vulnerabilities

This blog explores Darktrace’s detection of Balada Injector, a malware known to exploit vulnerabilities in WordPress to gain unauthorized access to networks. Darktrace was able to define numerous use-cases within customer environments which followed previously identified patterns of activity spikes across multiple weeks.
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
Justin Torres
Cyber Analyst
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08
Apr 2024

Introduction

With millions of users relying on digital platforms in their day-to-day lives, and organizations across the world depending on them for their business operations, they have inevitably also become a prime target for threat actors. The widespread exploitation of popular services, websites and platforms in cyber-attacks highlights the pervasive nature of malicious actors in today’s threat landscape.

A prime illustration can be seen within the content management system WordPress. Its widespread use and extensive plug-in ecosystem make it an attractive target for attackers aiming to breach networks and access sensitive data, thus leading to routine exploitation attempts. In the End of Year Threat Report for 2023, for example, Darktrace reported that a vulnerability in one WordPress plug-in, namely an authentication bypass vulnerability in miniOrange's Social Login and Register. Darktrace observed it as one of the most exploited vulnerabilities observed across its customer base in the latter half of 2023.

Between September and October 2023, Darktrace observed a string of campaign-like activity associated with Balada Injector, a malware strain known to exploit vulnerabilities in popular plug-ins and themes on the WordPress platform in order to inject a backdoor to provide further access to affected devices and networks. Thanks to its anomaly-based detection, Darktrace DETECT™ was able to promptly identify suspicious connections associated with the Balada Injector, ensuring that security teams had full visibility over potential post-compromise activity and allowing them to act against offending devices.

What is Balada Injector?

The earliest signs of the Balada Injector campaign date back to 2017; however, it was not designated the name Balada Injector until December 2022 [1]. The malware utilizes plug-ins and themes in WordPress to inject a backdoor that redirects end users to malicious and fake sites. It then exfiltrates sensitive information, such as database credentials, archive files, access logs and other valuable information which may not be properly secured [1]. Balada Injector compromise activity is also reported to arise in spikes of activity that emerge every couple of weeks [4].

In its most recent attack activity patterns, specifically in September 2023, Balada Injector exploited a cross-site scripting (XSS) vulnerability in CVE-2023-3169 associated with the tagDiv composer plug-in. Some of the injection methods observed included HTML injections, database injections, and arbitrary file injections. In late September 2023, a similar pattern of behavior was observed, with the ability to plant a backdoor that could execute PHP code and install a malicious WordPress plug-in, namely ‘wp-zexit’.

According to external security researchers [2], the most recent infection activity spikes for Balada Injector include the following:

Pattern 1: ‘stay.decentralappps[.]com’ injections

Pattern 2: Autogenerated malicious WordPress users

Pattern 3: Backdoors in the Newspaper theme’s 404.php file

Pattern 4: Malicious ‘wp-zexit’ plug-in installation

Pattern 5: Three new Balada Injector domains (statisticscripts[.]com, dataofpages[.]com, and listwithstats[.]com)

Pattern 6: Promsmotion[.]com domain

Darktrace’s Coverage of Balada Injector

Darktrace detected devices across multiple customer environments making external connections to the malicious Balada Injector domains, including those associated with aforementioned six infection activity patterns. Across the incidents investigated by Darktrace, much of the activity appeared to be associated with TLS/SSL connectivity, related to Balada Injector endpoints, which correlated with the reported infection patterns of this malware. The observed hostnames were all recently registered and, in most cases, had IP geolocations in either the Netherlands or Ukraine.

In the observed cases of Balada Injector across the Darktrace fleet, Darktrace RESPOND™ was not active on the affected customer environments. If RESPOND had been active and enabled in autonomous response mode at the time of these attacks, it would have been able to quickly block connections to malicious Balada Injector endpoints as soon as they were identified by DETECT, thereby containing the threat.

Looking within the aforementioned activity patterns, Darktrace identified a Balada Injector activity within a customer’s environment on October 16, 2023, when a device was observed making a total of 9 connection attempts to ‘sleep[.]stratosbody[.]com’, a domain that had previously been associated with the malware [2]. Darktrace recognized that the endpoint had never been seen on the network, with no other devices having connected to it previously, thus treated it as suspicious.

Figure 1: The connection details above demonstrate 100% rare external connections were made from the internal device to the ‘sleep[.]stratosbody[.]com’ endpoint.

Similarly, on September 21, 2023, Darktrace observed a device on another customer network connecting to an external IP that had never previously been observed on the environment, 111.90.141[.]193. The associated server name was a known malicious endpoint, ‘stay.decentralappps[.]com’, known to be utilized by Balada Injector to host malicious scripts used to compromise WordPress sites. Although the ‘stay.decentralappps[.]com’ domain was only registered in September 2023, it was reportedly used in the redirect chain of the aforementioned stratosbody[.com] domain [2]. Such scripts can be used to upload backdoors, including malicious plug-ins, and create blog administrators who can perform administrative tasks without having to authenticate [2].

Figure 2: Advance Search results displaying the metadata logs surrounding the unusual connections to ‘stay.decentralappps[.]com’. A total of nine HTTP CONNECT requests were observed, with status messages “Proxy Authorization Required” and “Connection established”.

Darktrace observed additional connections within the same customer’s environment on October 10 and October 18, specifically SSL connections from two distinct source devices to the ‘stay.decentralappps[.]com’ endpoint. Within these connections, Darktrace observed the normalized JA3 fingerprints, “473f0e7c0b6a0f7b049072f4e683068b” and “aa56c057ad164ec4fdcb7a5a283be9fc”, the latter of which corresponds to GitHub results mentioning a Python client (curl_cffi) that is able to impersonate the TLS signatures of browsers or JA3 fingerprints [8].

Figure 3: Advanced Search query results showcasing Darktrace’s detection of SSL connections to ‘stay.decentralappps[.]com over port 443.

On September 29, 2023, a device on a separate customer’s network was observed connecting to the hostname ‘cdn[.]dataofpages[.]com’, one of the three new Balada Injector domains identified as part of the fifth pattern of activity outlined above, using a new SSL certificate via port 443. Multiple open-source intelligence (OSINT) vendors flagged this domain as malicious and associated with Balada Injector malware [9].

Figure 4: The Model Breach Event Log detailing the Balada Injector-related connections observed causing the ‘Anomalous External Activity from Critical Network Device’ DETECT model to breach.

On October 2, 2023, Darktrace observed the device of another customer connecting to the rare hostname, ‘js.statisticscripts[.]com’ with the IP address 185.39.206[.]161, both of which had only been registered in late September and are known to be associated with the Balada Injector.

Figure 5: Model Breach Event Log detailing connections to the hostname ‘js.statisticscripts[.]com’ over port 137.

On September 13, 2023, Darktrace identified a device on another customer’s network connecting to the Balada Injector endpoint ‘stay.decentralappps[.]com’ endpoint, with the destination IP 1.1.1[.]1, using the SSL protocol. This time, however, Darktrace also observed the device making subsequent connections to ‘get.promsmotion[.]com’ a subdomain of the ‘promsmotion[.]com’ domain. This domain is known to be used by Balada Injector actors to host malicious scripts that can be injected into the WordPress Newspaper theme as potential backdoors to be leveraged by attackers.

In a separate case observed on September 14, Darktrace identified a device on another environment connecting to the domain ‘collect[.]getmygateway[.]com’ with the IP 88.151.192[.]254. No other device on the customer’s network had visited this endpoint previously, and the device in question was observed repeatedly connecting to it via port 443 over the course of four days. While this specific hostname had not been linked with a specific activity pattern of Balada Injector, it was reported as previously associated with the malware in September 2023 [2].

Figure 6: Model Breach Event Log displaying a customer device making repeated connections to the endpoint ‘collect[.]getmygateway[.]com’, breaching the DETECT model ‘Repeating Connections Over 4 Days’.

In addition to DETECT’s identification of this suspicious activity, Darktrace’s Cyber AI Analyst™ also launched its own autonomous investigation into the connections. AI Analyst was able to recognize that these separate connections that took place over several days were, in fact, connected and likely represented command-and-control (C2) beaconing activity that had been taking place on the customer networks.

By analyzing the large number of external connections taking place on a customer’s network at any one time, AI Analyst is able to view seemingly isolated events as components of a wider incident, ensuring that customers maintain full visibility over their environments and any emerging malicious activity.

Figure 7: Cyber AI Analyst investigation detailing the SSL connectivity observed, including endpoint details and overall summary of the beaconing activity.

Conclusion

While Balada Injector’s tendency to interchange C2 infrastructure and utilize newly registered domains may have been able to bypass signature-based security measures, Darktrace’s anomaly-based approach enabled it to swiftly identify affected devices across multiple customer environments, without needing to update or retrain its models to keep pace with the evolving iterations of WordPress vulnerabilities.

Unlike traditional measures, Darktrace DETECT’s Self-Learning AI focusses on behavioral analysis, crucial for identifying emerging threats like those exploiting commonly used platforms such as WordPress. Rather than relying on historical threat intelligence or static indicators of compromise (IoC) lists, Darktrace identifies the subtle deviations in device behavior, such as unusual connections to newly registered domains, that are indicative of network compromise.

Darktrace’s suite of products, including DETECT+RESPOND, is uniquely positioned to proactively identify and contain network compromises from the onset, offering vital protection against disruptive cyber-attacks.

Credit to: Justin Torres, Cyber Analyst, Nahisha Nobregas, Senior Cyber Analyst

Appendices

Darktrace DETECT Model Coverage

  • Anomalous Server Activity / Anomalous External Activity from Critical Network Device
  • Anomalous Connection / Anomalous SSL without SNI to New External
  • Anomalous Connection / Rare External SSL Self-Signed
  • Compliance / Possible DNS Over HTTPS/TLS
  • Compliance / External Windows Communications
  • Compromise / Repeating Connections Over 4 Days
  • Compromise / Beaconing Activity To External Rare
  • Compromise / SSL Beaconing to Rare Destination
  • Compromise / HTTP Beaconing to Rare Destination
  • Compromise / Suspicious TLS Beaconing To Rare External
  • Compromise / Large DNS Volume for Suspicious Domain
  • Anomalous Server Activity / Outgoing from Server
  • Anomalous Server Activity / Rare External from Server
  • Device / Suspicious Domain

List of IoCs

IoC - Type - Description + Confidence

collect[.]getmygateway[.]com - Hostname - Balada C2 Endpoint

cdn[.]dataofpages[.]com - Hostname - Balada C2 Endpoint

stay[.]decentralappps[.]com - Hostname - Balada C2 Endpoint

get[.]promsmotion[.]com - Hostname - Balada C2 Endpoint

js[.]statisticscripts[.]com - Hostname - Balada C2 Endpoint

sleep[.]stratosbody[.]com - Hostname - Balada C2 Endpoint

trend[.]stablelightway[.]com - Hostname - Balada C2 Endpoint

cdn[.]specialtaskevents[.]com - Hostname - Balada C2 Endpoint

88.151.192[.]254 - IP Address - Balada C2 Endpoint

185.39.206[.]160 - IP Address - Balada C2 Endpoint

111.90.141[.]193 - IP Address - Balada C2 Endpoint

185.39.206[.]161 - IP Address - Balada C2 Endpoint

2.59.222[.]121 - IP Address - Balada C2 Endpoint

80.66.79[.]253 - IP Address - Balada C2 Endpoint

Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:68.0) - User Agent - Observed User Agent in Balada C2 Connections

Gecko/20100101 Firefox/68.0 - User Agent - Observed User Agent in Balada C2 Connections

Mozilla/5.0 (Windows NT 10.0; Win64; x64) - User Agent - Observed User Agent in Balada C2 Connections

AppleWebKit/537.36 (KHTML, like Gecko) - User Agent - Observed User Agent in Balada C2 Connections

Chrome/117.0.0.0 - User Agent - Observed User Agent in Balada C2 Connections

Safari/537.36 - User Agent - Observed User Agent in Balada C2 Connections

Edge/117.0.2045.36 - User Agent - Observed User Agent in Balada C2 Connections

MITRE ATT&CK Mapping

Technique - Tactic - ID - Sub Technique

Exploit Public-Facing Application

INITIAL ACCESS

T1190

Web Protocols

COMMAND AND CONTROL

T1071.001

T1071

Protocol Tunneling

COMMAND AND CONTROL

T1572


Default Accounts

DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS

T1078.001

T1078

Domain Accounts

DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS

T1078.002

T1078

External Remote Services

PERSISTENCE, INITIAL ACCESS

T1133

NA

Local Accounts

DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS

T1078.003

T1078

Application Layer Protocol

COMMAND AND CONTROL

T1071

NA

Browser Extensions

PERSISTENCE

T1176

NA

Encrypted Channel

COMMAND AND CONTROL

T1573

Fallback Channels

COMMAND AND CONTROL

T1008

Multi-Stage Channels

COMMAND AND CONTROL

T1104

Non-Standard Port

COMMAND AND CONTROL

T1571

Supply Chain Compromise

INITIAL ACCESS ICS

T0862

Commonly Used Port

COMMAND AND CONTROL ICS

T0885

References

[1] https://blog.sucuri.net/2023/04/balada-injector-synopsis-of-a-massive-ongoing-wordpress-malware-campaign.html

[2] https://blog.sucuri.net/2023/10/balada-injector-targets-unpatched-tagdiv-plugin-newspaper-theme-wordpress-admins.html

[3] https://securityboulevard.com/2021/05/wordpress-websites-redirecting-to-outlook-phishing-pages-travelinskydream-ga-track-lowerskyactive/

[4] https://thehackernews.com/2023/10/over-17000-wordpress-sites-compromised.html

[5] https://www.bleepingcomputer.com/news/security/over-17-000-wordpress-sites-hacked-in-balada-injector-attacks-last-month/

[6]https://nvd.nist.gov/vuln/detail/CVE-2023-3169

[7] https://www.geoedge.com/balda-injectors-2-0-evading-detection-gaining-persistence/

[8] https[:]//github[.]com/yifeikong/curl_cffi/blob/master/README.md

[9] https://www.virustotal.com/gui/domain/cdn.dataofpages.com

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
Justin Torres
Cyber Analyst

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May 12, 2026

Resilience at the Speed of AI: Defending the Modern Campus with Darktrace

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Why higher education is a different cybersecurity battlefield

After four decades in IT, now serving as both CIO and CISO, I’ve learned one simple truth: cybersecurity is never “done.” It’s a constant game of cat and mouse. Criminals evolve. Technologies advance. Regulations expand. But in higher education, the challenge is uniquely complex.

Unlike a bank or a military installation, we can’t lock down networks to a narrow set of approved applications. Higher education environments are open by design. Students collaborate globally, faculty conduct cutting-edge research, and administrators manage critical operations, all of which require seamless access to the internet, global networks, cloud platforms, and connected systems.

Combine that openness with expanding regulatory mandates and tight budgets, and the balancing act becomes clear.

Threat actors don’t operate under the same constraints. Often well-funded and sponsored by nation-states with significant resources, they’re increasingly organized, strategic, and innovative.

That sophistication shows up in the tactics we face every day, from social engineering and ransomware to AI-driven impersonation attacks. We’re dealing with massive volumes of data, countless signals, and a very small window between detection and damage.

No human team, no matter how talented or how numerous, can manually sift through that noise at the speed required.

Discovering a force multiplier

Nothing in cybersecurity is 100% foolproof. I never “set it and forget it.” But for institutions balancing rising threats and finite resources, the Darktrace ActiveAI Security Platform™ offers something incredibly valuable: peace of mind through speed and scale.

It closes the gap between detection and response in a way humans can’t possibly match. At the speed of light, it can quarantine, investigate, and contain anomalous activity.

I’ve purchased and deployed Darktrace three separate times at three different institutions because I’ve seen firsthand what it can do and what it enables teams like mine to achieve.

I first encountered Darktrace while serving as CIO for a large multi-campus college system. What caught my attention was Darktrace's Self-Learning AI, and its ability to learn what "normal" looked like across our network. Instead of relying solely on static signatures or rigid rules, Darktrace built a behavioral baseline unique to our environment and alerted us in real time when something simply didn’t look right.

In higher education, where strict lockdowns aren’t realistic, that behavioral model made all the difference. We deployed it across five campuses, and the impact was immediate. Operating 24/7, Darktrace surfaced threats in ways our team couldn’t replicate manually.

Over time, the Darktrace platform evolved alongside the changing threat landscape, expanding into intrusion prevention, cloud visibility, and email security. At subsequent institutions, including Washington College, Darktrace was one of my first strategic investments.

Revealing the hidden threat other tools missed

One of the most surprising investigations of my career involved a data leak. Leadership suspected sensitive information from high-level meetings was being exposed, but our traditional tools couldn’t provide any answers.

Using Darktrace’s deep network visibility, down to packet-level data, we traced unusual connections to our CCTV camera system, which had been configured with a manufacturer’s default password. A small group of employees had hacked into the CCTV cameras, accessed audio-enabled recordings from boardroom meetings, and stored copies locally.

No other tool in our environment could have surfaced those connections the way Darktrace did. It was a clear example of why using AI to deeply understand how your organization, systems, and tools normally behave, matters: threats and risks don’t always look the way we expect.

Elevating a D-rating into a A-level security program

When I arrived at my last CISO role, the institution had recently experienced a significant ransomware attack. Attackers located  data  which informed their setting  ransom demands to an amount they knew would likely result in payment. It was a sobering example of how calculated and strategic modern cybercriminals have become.

Third-party cyber ratings reflected that reality, with a  D rating.

To raise the bar, we implemented a comprehensive security program and integrated layered defenses; -deploying state of the art tools and methods-  across the environment, with Darktrace at its core.

After a 90-day learning period to establish our behavioral baseline, we transitioned the platform into fully autonomous mode. In a single 30-day span, Darktrace conducted more than 2,500 investigations and autonomously resolved 92% of all false positives.

For a small team, that’s transformative. Instead of drowning in alerts, my staff focused on less than  200 meaningful cases that warranted human review.

Today, we maintain a perfect A rating from third-party assessors and have remained cybersafe.

Peace of mind isn’t about complacency

The effect of Darktrace as a force multiplier has a real human impact.

With the time reclaimed through automation, we expanded community education programs and implemented simulated phishing exercises. Through sustained training and awareness efforts, we reduced social engineering susceptibility from nearly 45% to under 5%.

On a personal level, Darktrace allows me to sleep better at night and take time off knowing we have intelligent systems monitoring and responding around the clock. For any CIO or CISO carrying institutional risk on their shoulders, that matters.

The next era: AI vs. AI

A new chapter in cybersecurity is unfolding as adversaries leverage AI to enhance scale, speed, and believability. Phishing campaigns are more personalized, impersonation attempts are more precise, and deepfake video technology, including live video, is disturbingly authentic. At the same time, organizations are rapidly adopting AI across their own environments —from GenAI assistants to embedded tools to autonomous agents. These systems don’t operate within fixed rules. They act across email, cloud, SaaS, and identity systems, often with broad permissions, and their behavior can evolve over time in ways that are difficult to predict or control.

That creates a new kind of security challenge. It’s not just about defending against AI-powered threats but understanding and governing how AI behaves within your environment, including what it can access, how it acts, and where risk begins to emerge.

From my perspective, this is a natural next step for Darktrace.

Darktrace brings a level of maturity and behavioral understanding uniquely suited to the complexity of AI environments. Self-Learning AI learns the normal patterns of each business to interpret context, uncover subtle intent, and detect meaningful deviations without relying on predefined rules or signatures. Extending into securing AI by bringing real-time visibility and control to GenAI assistants, AI agents, development environments and Shadow AI, feels like the logical evolution of what Darktrace already does so well.

Just as importantly, Darktrace is already built for dynamic, cross-domain environments where risk doesn’t sit in a single tool or control plane. In higher education, activity already spans multiple systems and, with AI, that interconnection only accelerates.

Having deployed Darktrace multiple times, I have confidence it’s uniquely positioned to lead in this space and help organizations adopt AI with greater visibility and control.

---

Since authoring this blog, Irving Bruckstein has transitioned to the role of Chief Executive Officer of the Cyberaigroup.

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Irving Bruckstein
CEO CyberAIgroup

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May 11, 2026

The Next Step After Mythos: Defending in a World Where Compromise is Expected

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Is Anthropic’s Mythos a turning point for cybersecurity?

Anthropic’s recent announcements around their Mythos model, alongside the launch of Project Glasswing, have generated significant interest across the cybersecurity industry.

The closed-source nature of the Mythos model has understandably attracted a degree of skepticism around some of the claims being made. Additionally, Project Glasswing was initially positioned as a way for software vendors to accelerate the proactive discovery of vulnerabilities in their own code; however, much of the attention has focused on the potential for AI to identify exploitable vulnerabilities for those with malicious intent.

Putting questions around the veracity of those claims to one side – which, for what it’s worth, do appear to be at least partially endorsed by independent bodies such as the UK’s AI Security Institute – this should not be viewed as a critical turning point for the industry. Rather, it reflects the natural direction of travel.

How Mythos affects cybersecurity teams  

At Darktrace, extolling the virtues of AI within cybersecurity is understandably close to our hearts. However, taking a step back from the hype, we’d like to consider what developments like this mean for security teams.

Whether it’s Mythos or another model yet to be released, it’s worth remembering that there is no fundamental difference between an AI discovered vulnerability and one discovered by a human. The change is in the pace of discovery and, some may argue, the lower the barrier to entry.

In the hands of a software developer, this is unquestionably positive. Faster discovery enables earlier remediation and more proactive security. But in the hands of an attacker, the same capability will likely lead to a greater number of exploitable vulnerabilities being used in the wild and, critically, vulnerabilities that are not yet known to either the vendor or the end user.

That said, attackers have always been able to find exploitable vulnerabilities and use them undetected for extended periods of time. The use of AI does not fundamentally change this reality, but it does make the process faster and, unfortunately, more likely to occur at scale.

While tools such as Darktrace / Attack Surface Management and / Proactive Exposure Management  can help security teams prioritize where to patch, the emergence of AI-driven vulnerability discovery reinforces an important point: patching alone is not a sufficient control against modern cyber-attacks.

Rethinking defense for a world where compromise is expected

Rather than assuming vulnerabilities can simply be patched away, defenders are better served by working from the assumption that their software is already vulnerable - and always will be -and build their security strategy accordingly.

Under that assumption, defenders should expect initial access, particularly across internet exposed assets, to become easier for attackers. What matters then is how quickly that foothold is detected, contained, and prevented from expanding.

For defenders, this places renewed emphasis on a few core capabilities:

  • Secure-by-design architectures and blast radius reduction, particularly around identity, MFA, segmentation, and Zero Trust principles
  • Early, scalable detection and containment, favoring behavioral and context-driven signals over signatures alone
  • Operational resilience, with the expectation of more frequent early-stage incidents that must be managed without burning out teams

How Darktrace helps organizations proactively defend against cyber threats

At Darktrace, we support security teams across all three of these critical capabilities through a multi-layered AI approach. Our Self-Learning AI learns what’s normal for your organization, enabling real-time threat detection, behavioral prediction, incident investigation and autonomous response. - all while empowering your security team with visibility and control.

To learn more about Darktrace’s application of AI to cybersecurity download our White Paper here.  

Reducing blast radius through visibility and control

Secure-by-design principles depend on understanding how users, devices, and systems behave. By learning the normal patterns of identity and network activity, Darktrace helps teams identify when access is being misused or when activity begins to move beyond expected boundaries. This makes it possible to detect and contain lateral movement early, limiting how far an attacker can progress even after initial access.

Detecting and containing threats at the earliest stage  

As AI accelerates vulnerability discovery, defenders need to identify exploitation before it is formally recognized. Darktrace’s behavioral understanding approach enables detection of subtle deviations from normal activity, including those linked to previously unknown vulnerabilities.

A key example of this is our research on identifying cyber threats before public CVE disclosures, demonstrating that assessing activity against what is normal for a specific environment, rather than relying on predefined indicators of compromise, enables detection of intrusions exploiting previously unknown vulnerabilities days or even weeks before details become publicly available.

Additionally, our Autonomous Response capability provides fast, targeted containment focused on the most concerning events, while allowing normal business operations to continue. This has consistently shown that even when attackers use techniques never seen before, Darktrace’s Autonomous Response can contain threats before they have a chance to escalate.

Scaling response without increasing operational burden

As early-stage incidents become more frequent, the ability to investigate and respond efficiently becomes critical. Darktrace’s Cyber AI Analyst’s AI-driven investigation capabilities automatically correlate activity across the environment, prioritizing the most significant threats and reducing the need for manual triage. This allows security teams to respond faster and more consistently, without increasing workload or burnout.

What effective defense looks like in an AI-accelerated landscape

Developments like Mythos highlight a reality that has been building for some time: the window between exposure and exploitation is shrinking, and in many cases, it may disappear entirely. In that environment, relying on patching alone becomes increasingly reactive, leaving little room to respond once access has been established.

The more durable approach is to assume that compromise will occur and focus on controlling what happens next. That means identifying early signs of misuse, containing threats before they spread, and maintaining visibility across the environment so that isolated signals can be understood in context.

AI plays a role on both sides of this equation. While it enables attackers to move faster, it also gives defenders the ability to detect subtle changes in behavior, prioritize what matters, and respond in real time. The advantage will not come from adopting AI in isolation, but from applying it in a way that reduces the gap between detection and action.

AI may be accelerating parts of the attack lifecycle, but the fundamentals of defense, detection, and containment still apply. If anything, they matter more than ever – and AI is just as powerful a tool for defenders as it is for attackers.

To learn more about Darktrace and Mythos read more on our blog: Mythos vs Ethos: Defending in an Era of AI‑Accelerated Vulnerability Discovery

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About the author
Toby Lewis
Head of Threat Analysis
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