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.

Written by

Justin Torres

Cyber Analyst

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

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

‍

Local Accounts

DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS

T1078.003

T1078

‍

Application Layer Protocol

COMMAND AND CONTROL

T1071

‍

Browser Extensions

PERSISTENCE

T1176

‍

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

Written by

Justin Torres

Cyber Analyst

Inside the SOC

Written by

Justin Torres

Cyber Analyst

Malware Research Lead

Proactive Security

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June 1, 2026

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Proactive Security

June 1, 2026

Defend What You Trust: Stories from the Front Lines of Modern Cyber Defense

Modern attacks don’t always announce themselves, follow obvious patterns, or rely on known malware. Often, they move quietly inside trusted systems, authenticated sessions, and everyday behavior.

They don’t break in. They blend in.

That’s why an AI-powered defense is essential. It turns invisible signals into actionable insights at a scale neither analysts nor traditional tools can achieve alone.

Confidence is creating risk

One of the most dangerous assumptions in cybersecurity today is that strong controls equal strong protection.

Multi-factor authentication (MFA), for example, is widely viewed as a foundational safeguard. But as the CISO for a professional sports organization explains, that confidence can be misplaced. “A lot of organizations assume that once you have MFA, those accounts are safe. That’s not true.”

In one instance, his team identified a sophisticated attack where a threat actor bypassed MFA entirely, not by breaking it, but by going around it. A user’s authenticated session was hijacked and re-used, allowing the attacker to impersonate them without triggering traditional controls.

“Darktrace picked up that a session had been re-injected by the hacker, and we were able to block it right away,” he explains.

Attackers anticipate what we miss

Even well-trained users can become entry points.

“An email bypassed our existing security tools,” shares the VP of IT at a U.S.-based risk management services provider. “The user missed one signal and entered their credentials into a malicious site. That’s what the bad guys count on.”

The organization responded quickly, but not before damage was done. Crucially, this occurred while Darktrace was in “watch mode,” before autonomous response was fully enabled. “Darktrace would have seen that and shut it down immediately,” he notes.

Mistakes and oversights like misconfigurations, forgotten machines, and missed patches can create serious vulnerabilities.

The CIO of a utility services organization shares an instance when Darktrace detected a breach to a client’s network via their ZTNA VPN due to misconfigured MFA. “Darktrace alerted us and autonomously blocked the scanning, preventing what could have been a ransomware-type incident.”

The most dangerous threats are already inside

The Head of Security at a global business services provider knows firsthand how blind spots can persist inside environments. His team uncovered evidence of dormant ransomware artifacts sitting unnoticed within a company’s environment ¬¬– long before modern detection was in place.

“During a routine file transfer, Darktrace flagged the suspicious activity, identified the ransomware, and immediately quarantined the server,” he recalls. While the attack was never executed, the implication was significant: the risk existed long before it was finally detected.

Cyber threats are also successful because they take advantage of normal human behavior, exploiting moments of cognitive overload, urgency, and trust.

The Executive Director of IT and Business Applications at a pharmaceutical lab describes the time Darktrace flagged an employee logging into Microsoft 365 from Singapore, despite him being physically located in the U.S. Darktrace immediately cut off his access and within minutes revealed that the employee’s son was using a VPN to play a video game.

While the threat was benign, it demonstrated the strength of AI to use contextual information to detect threats other tools miss. The information also saved security analysts hours of investigation and minimized downtime for the employee. “That level of precision and speed isn’t just convenient, it’s game changing.”

“Unusual” behavior is the new red flag

Detecting modern threats requires an understanding of what “normal” looks like and recognizing when something subtly deviates.

One security leader at an AI technology enterprise described a scenario in which an employee connected to a proxy service in China. The service itself was legitimate, and although traditional tools didn’t flag it, the behavior was unusual for that user specifically.

“That’s what Darktrace picked up on. The activity turned out to be benign, but without visibility into behavioral deviations, it could just as easily have been something more serious.”

AI shifts defense from reaction to anticipation

These stories point to a fundamental shift by cyber attackers, both tactically and strategically. Because traditional security tools were built to detect what’s already known, modern attacks are often:

Credential-based, not malware-based
Behavioral, not signature-based
Subtle, not overt

They may operate within the boundaries of what appears normal, exploiting what organizations trust, not what they block:

Trusted sessions
Legitimate services
Human error

This is where AI is changing the equation. Rather than relying on predefined rules or known threat signatures, AI can:

Establish a baseline of normal behavior
Detect subtle anomalies in real time
Act autonomously to contain potential threats

Resilience, not perfection, is the new security standard

As these frontline experiences show, the organizations that lead are those that move beyond reactive defense and embrace AI as a core part of their strategy.

It eliminates the blind spots and uncertainty, says the CISO of a professional sports organization. “If you lack visibility, you’re not managing risk, you’re assuming it. AI gives you the actionable insights needed to turn uncertainty into control.”

And it provides the speed and agility that are vital when seconds matter, says the Executive Director of IT and Business Applications. “When Darktrace alerted us at 3:00 am to a ransomware attack, it had already quarantined the affected systems, blocked the attacker’s access, and provided us with the critical details and time needed to investigate. That action likely saved us hundreds of thousands, if not millions, of dollars.”

The modern SOC has become a cornerstone of enterprise resilience, responsible for protecting data and operational continuity while enabling digital growth and innovation. For today’s security professional, that means success is no longer measured by what they keep out, but by what they protect: revenue, reputation, and trust.

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May 28, 2026

From Efficiency to Exposure: How AI Adoption Is Creating Unseen Vulnerabilities on the Factory Floor

How AI agents impact the manufacturing industry

Security teams and IT personnel across the manufacturing industry are under constant pressure to protect production, maintain uptime, and safeguard critical assets but the rise of AI is bringing huge new opportunities alongside new cyber risks. Across manufacturing, AI is embedded into workflows, decision-making, and increasingly, autonomous AI agents are acting on behalf of employees and systems.

Agentic systems are powerful because they can act independently, but that same autonomy also creates cyber and operational risk. Agents have extensive permissions and are capable of carrying out complex tasks, making decisions, and interacting with tools or external systems with little to no human intervention.

Unlike traditional AI models that perform predefined tasks, AI agents use advanced techniques to mimic human decision-making processes, dynamically adapting to new challenges, making decision and taking action based on their own judgement. They look like employees operationally but lack judgment, ethics, or fear of consequences like humans do. This means they can be easily manipulated by cybercriminals, and an AI agent embedded across an OT network creates threats that extend well beyond data exposure. For example, at BMW, AI identifies faults in welding processes as they occur. At its Spartanburg plant, AI monitors the weld of 300-400 metal studs onto every SUV frame to detect misplaced or faulty studs and correct them instantly. Corruption of BMW’s AI system could lead to catastrophic quality control errors.

Adopting agentic AI systems across manufacturing raises some concerns across security teams. New data from our State of AI Cybersecurity survey shows that 78% of manufacturing security professionals are worried about employee use of AI agents – their top concern. That’s followed by employee use of generative AI tools like CoPilot and ChatGPT, a worry for 76% of security professionals at manufacturing organizations. As these tools gain more access to business data and processes, and more autonomy within organizations, security teams, who today have minimal visibility of agent activity in their environments, increasingly have sensitive data exposure (a worry for 60%) and accidental policy and regulatory violations (59%) on their minds.

External AI-powered threats are evolving just as quickly

The same capabilities transforming manufacturing are also reshaping cyberattacks.

AI is enabling attackers to automate reconnaissance, refine targeting, and adapt in real time. What once required time and manual effort can now be executed continuously and at scale. Manufacturers are already seeing the impact. According to manufacturing security professionals we surveyed, 76% are already being impacted by AI-powered threats and 90% see AI increasing the success of social engineering attacks.

And the techniques themselves are evolving. Concerns across the manufacturing sector show growing anxiety about the range of AI-powered attack routes, most pressingly of adaptive malware that evolves in real-time – a prospect half (49%) of manufacturing security professionals we surveyed are worried by, a full 9% more than the average across industries. AI adaptive malware is followed by:

Automated vulnerability scanning and exploit chaining (48%) which has become even more pressing as Anthropic’s new Mythos AI Model supercharges vulnerability discovery

Hyper-personalized phishing campaigns (46%), which remain a mainstay in hackers’ arsenals, and AI has amplified their effectiveness by making phishing emails more convincing and harder to detect.

This is not just an increase in volume, it is a shift toward threats that evolve as they unfold - often faster than static defenses can respond.

Despite rising awareness, many manufacturers are not yet equipped to manage this shift. More than half (51%) say they are not adequately prepared for AI-driven threats, and only 37% have formal policies governing AI deployment.

Securing AI through visibility, context, and guardrails

Addressing this challenge does not require manufacturers to slow innovation. It requires a different approach to security, one that can operate at the same speed and scale as AI. Three specific priorities are emerging for manufacturers looking to take advantage of the power of AI.

Visibility is foundational.

Organizations need to understand where AI is being used, what it can access, and how it behaves across both IT and OT environments. Without that, risk cannot be measured or managed. It is no surprise that Darktrace’s research found that 91% of manufacturing security professionals said that they need to understand how AI makes decisions before trusting it. This is even more critical in operational settings where disruption has safety, environmental, financial, and reputational impacts.

Context is what turns visibility into action.

In environments shaped by AI, normal behavior is constantly shifting. Detecting threats requires a behavioral approach; understanding patterns of life across the organization and identifying subtle deviations in real time – a step change in organizations’ traditional approach to security and risk management.

Guardrails ensure that agency does not become exposure

As AI systems take on greater responsibility, organizations need clear boundaries around what they can do and when they can act independently. These controls must be embedded into systems themselves, not applied after the fact.

Securing AI Agents Across Manufacturing IT and OT

The rise of agentic AI is transforming manufacturing - powering next-generation operations while reshaping the security landscape. This is not just an increase in threats, but a shift to autonomous systems, continuously evolving behaviors, and risks moving at machine speed. For organizations trying to grapple with the challenge of enabling AI while managing the risk, visibility, context and guardrails should be foundational.

Darktrace helps manufacturers build secure AI approaches by making those foundations possible. It provides visibility and real-time detection and response to unusual activity across IT and OT environments and allows organizations to understand AI activity from the prompts employees use and the agents they build to how those agents are behaving across the environment. For manufacturers scaling AI, this delivers a foundation for innovation without sacrificing control.

About the author

Oakley Cox

Director of Product

Your data. Our AI.

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Check out this article by Darktrace: Balada Injector: Darktrace’s Investigation into the Malware Exploiting WordPress Vulnerabilities

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

Introduction

What is Balada Injector?

Darktrace’s Coverage of Balada Injector

Conclusion

Appendices

List of IoCs

MITRE ATT&CK Mapping

References

Chinese APT Campaign Targets Entities with Updated FDMTP Backdoor

Defend What You Trust: Stories from the Front Lines of Modern Cyber Defense

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They don’t break in. They blend in.

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The most dangerous threats are already inside

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AI shifts defense from reaction to anticipation

Resilience, not perfection, is the new security standard

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How AI agents impact the manufacturing industry

External AI-powered threats are evolving just as quickly

Securing AI through visibility, context, and guardrails

Securing AI Agents Across Manufacturing IT and OT