October 3, 2023

Unveiling ViperSoftX: A Darktrace Investigation

Read about the ViperSoftX threat and how Darktrace's innovative detection methods exposed this cyber intrusion and its potential impacts.

Written by

Zoe Tilsiter

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

Zoe Tilsiter

Cyber Analyst

Oct 2023

Fighting Info-Stealing Malware

The escalating threat posed by information-stealing malware designed to harvest and steal the sensitive data of individuals and organizations alike has become a paramount concern for security teams across the threat landscape. In direct response to security teams improving their threat detection and prevention capabilities, threat actors are forced to continually adapt and advance their techniques, striving for greater sophistication to ensure they can achieve the malicious goals.

What is ViperSoftX?

ViperSoftX is an information stealer and Remote Access Trojan (RAT) malware known to steal privileged information such as cryptocurrency wallet addresses and password information stored in browsers and password managers. It is commonly distributed via the download of cracked software from multiple sources such as suspicious domains, torrent downloads, and key generators (keygens) from third-party sites.

ViperSoftX was first observed in the wild in 2020 [1] but more recently, new strains were identified in 2022 and 2023 utilizing more sophisticated detection evasion techniques, making it more difficult for security teams to identify and analyze. This includes using more advanced encryption methods alongside monthly changes to command-and-control servers (C2) [2], using dynamic-link library (DLL) sideloading for execution techiques, and subsequently loading a malicious browser extension upon infection which works as an independent info-stealer named VenomSoftX [3].

Between February and June 2023, Darktrace detected activity related to the VipersoftX and VenomSoftX information stealers on the networks of more than 100 customers across its fleet. Darktrace DETECT™ was able to successfully identify the anomalous network activity surrounding these emerging information stealer infections and bring them to the attention of the customers, while Darktrace RESPOND™, when enabled in autonomous response mode, was able to quickly intervene and shut down malicious downloads and data exfiltration attempts.

ViperSoftX Attack & Darktrace Coverage

In cases of ViperSoftX information stealer activity observed by Darktrace, the initial infection was caused through the download of malicious files from multimedia sites, endpoints of cracked software like Adobe Illustrator, and torrent sites. Endpoint users typically unknowingly download the malware from these endpoints with a sideloaded DLL, posing as legitimate software executables.

Darktrace detected multiple downloads from such multimedia sites and endpoints related to cracked software and BitTorrent, which were likely representative of the initial source of ViperSoftX infection. Darktrace DETECT models such as ‘Anomalous File / Anomalous Octet Stream (No User Agent)’ breached in response to this activity and were brought to the immediate attention of customer security teams. In instances where Darktrace RESPOND was configured in autonomous response mode, Darktrace was able to enforce a pattern of life on offending devices, preventing them from downloading malicious files. This ensures that devices are limited to conducting only their pre-established expected activit, minimizing disruption to the business whilst targetedly mitigating suspicious file downloads.

The downloads are then extracted, decrypted and begin to run on the device. The now compromised device will then proceed to make external connections to C2 servers to retrieve secondary PowerShell executable. Darktrace identified that infected devices using PowerShell user agents whilst making HTTP GET requests to domain generation algorithm (DGA) ViperSoftX domains represented new, and therefore unusual, activity in a large number of cases.

For example, Darktrace detected one customer device making an HTTP GET request to the endpoint ‘chatgigi2[.]com’, using the PowerShell user agent ‘Mozilla/5.0 (Windows NT; Windows NT 10.0; en-US) WindowsPowerShell/5.1.19041.2364’. This new activity triggered a number of DETECT models, including ‘Anomalous Connection / PowerShell to Rare External’ and ‘Device / New PowerShell User Agent’. Repeated connections to these endpoints also triggered C2 beaconing models including:

Compromise / Agent Beacon (Short Period)
Compromise / Agent Beacon (Medium Period)
Compromise / Agent Beacon (Long Period)
Compromise / Quick and Regular Windows HTTP Beaconing
Compromise / SSL or HTTP Beacon

Although a large number of different DGA domains were detected, commonalities in URI formats were seen across affected customers which matched formats previously identified as ViperSoftX C2 communication by open-source intelligence (OSINT), and in other Darktrace investigations.

URI paths for example, were always of the format /api/, /api/v1/, /v2/, or /v3/, appearing to detail version number, as can be seen in Figure 1.

*Figure 1: A Packet Capture (PCAP) taken from Darktrace showing a connection made to a ViperSoftX C2 endpoint containing versioning information, consistent with ViperSoftX pattern of communication.*

Before the secondary PowerShell executables are loaded, ViperSoftX takes a digital fingerprint of the infected machine to gather its configuration details, and exfiltrates them to the C2 server. These include the computer name, username, Operating System (OS), and ensures there are no anti-virus or montoring tools on the device. If no security tool are detected, ViperSoftX then downloads, decrypts and executes the PowerShell file.

Following the GET requests Darktrace observed numerous devices performing HTTP POST requests and beaconing connections to ViperSoftX endpoints with varying globally unique identifiers (GUIDs) within the URIs. These connections represented the exfiltration of device configuration details, such as “anti-virus detected”, “app used”, and “device name”. As seen on another customer’s deployment, this caused the model ‘Anomalous Connection / Multiple HTTP POSTs to Rare Hostname’ to breach, which was also detected by Cyber AI Analyst as seen in Figure 2.

*Figure 2: Cyber AI Analyst’s detection of HTTP POSTs being made to apibiling[.]com, a ViperSoftX C2 endpoint.*

The malicious PowerShell download then crawls the infected device’s systems and directories looking for any cryptocurrency wallet information and password managers, and exfiltrates harvest data to the C2 infrastructure. The C2 server then provides further browser extensions to Chromium browsers to be downloaded and act as a separate stand-alone information stealer, also known as VenomSoftX.

Similar to the initial download of ViperSoftX, these malicious extensions are disguised as legitimate browser extensions to evade the detection of security teams. VenomSoft X, in turn, searches through and attempts to gather sensitive data from password managers and crypto wallets stored in user browsers. Using this information, VenomSoftX is able to redirect crypocurrency transactions by intercepting and manipulating API requests between the sender and the intended recipient, directing the cryptocurrency to the attacker instead [3].

Following investigation into VipersoftX activity across the customer base, Darktrace notified all affected customers and opened Ask the Expert (ATE) tickets through which customer’s could directly contact the analyst team for support and guidance in the face on the information stealer infection.

How did the attack bypass the rest of the security stack?

As previously mentioned, both the initial download of ViperSoftX and the subsequent download of the VenomX browser extension are disguised as legitimate software or browser downloads. This is a common technique employed by threat actors to infect target devices with malicious software, while going unnoticed by security teams traditional security measures. Furthermore, by masquerading as a legitimate piece of software endpoint users are more likely to trust and therefore download the malware, increasing the likelihood of threat actor’s successfully carrying out their objectives. Additionally, post-infection analysis of shellcode, the executable code used as the payload, is made significantly more difficult by VenomSoftX’s use of bytemapping. Bytemapping prevents the encryption of shellcodes without its corresponding byte map, meaning that the payloads cannot easily be decrypted and analysed by security researchers. [3]

ViperSoftX also takes numerous attempts to prevent their C2 infrastructure from being identified by blocking access to it on browsers, and using multiple DGA domains, thus renderring defunct traditional security measures that rely on threat intelligence and static lists of indicators of compromise (IoCs).

Fortunately for Darktrace customers, Darktrace’s anomaly-based approach to threat detection means that it was able to detect and alert customers to this suspicious activity that may have gone unnoticed by other security tools.

Insights/Conclusion

Faced with the challenge of increasingly competent and capable security teams, malicious actors are having to adopt more sophisticated techniques to successfully compromise target systems and achieve their nefarious goals.

ViperSoftX information stealer makes use of numerous tactics, techniques and procedures (TTPs) designed to fly under the radar and carry out their objectives without being detected. ViperSoftX does not rely on just one information stealing malware, but two with the subsequent injection of the VenomSoftX browser extension, adding an additional layer of sophistication to the informational stealing operation and increasing the potential yield of sensitive data. Furthermore, the use of evasion techniques like disguising malicious file downloads as legitimate software and frequently changing DGA domains means that ViperSoftX is well equipped to infiltrate target systems and exfiltrate confidential information without being detected.

However, the anomaly-based detection capabilities of Darktrace DETECT allows it to identify subtle changes in a device’s behavior, that could be indicative of an emerging compromise, and bring it to the customer’s security team. Darktrace RESPOND is then autonomously able to take action against suspicious activity and shut it down without latency, minimizing disruption to the business and preventing potentially significant financial losses.

Credit to: Zoe Tilsiter, Senior Cyber Analyst, Nathan Lorenzo, Cyber Analyst.

Appendices

References

[1] https://www.fortinet.com/blog/threat-research/vipersoftx-new-javascript-threat

[2] https://www.trendmicro.com/en_us/research/23/d/vipersoftx-updates-encryption-steals-data.html

[3] https://decoded.avast.io/janrubin/vipersoftx-hiding-in-system-logs-and-spreading-venomsoftx/

Darktrace DETECT Model Detections

· Anomalous File / Anomalous Octet Stream (No User Agent)

· Anomalous Connection / PowerShell to Rare External

· Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

· Anomalous Connection / Lots of New Connections

· Anomalous Connection / Multiple Failed Connections to Rare Endpoint

· Anomalous Server Activity / Outgoing from Server

· Compromise / Large DNS Volume for Suspicious Domain

· Compromise / Quick and Regular Windows HTTP Beaconing

· Compromise / Beacon for 4 Days

· Compromise / Suspicious Beaconing Behaviour

· Compromise / Large Number of Suspicious Failed Connections

· Compromise / Large Number of Suspicious Successful Connections

· Compromise / POST and Beacon to Rare External

· Compromise / DGA Beacon

· Compromise / Agent Beacon (Long Period)

· Compromise / Agent Beacon (Medium Period)

· Compromise / Agent Beacon (Short Period)

· Compromise / Fast Beaconing to DGA

· Compromise / SSL or HTTP Beacon

· Compromise / Slow Beaconing Activity To External Rare

· Compromise / Beaconing Activity To External Rare

· Compromise / Excessive Posts to Root

· Compromise / Connections with Suspicious DNS

· Compromise / HTTP Beaconing to Rare Destination

· Compromise / High Volume of Connections with Beacon Score

· Compromise / Sustained SSL or HTTP Increase

· Device / New PowerShell User Agent

· Device / New User Agent and New IP

Darktrace RESPOND Model Detections

· Antigena / Network / External Threat / Antigena Suspicious File Block

· Antigena / Network / External Threat / Antigena File then New Outbound Block

· Antigena / Network / External Threat / Antigena Watched Domain Block

· Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block

· Antigena / Network / External Threat / Antigena Suspicious Activity Block

· Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block

· Antigena / Network / Insider Threat / Antigena Large Data Volume Outbound Block

· Antigena / Network / External Threat / Antigena Suspicious File Pattern of Life Block

· Antigena / Network / Significant Anomaly / Antigena Controlled and Model Breach

List of IoCs

Indicator - Type - Description

ahoravideo-blog[.]com - Hostname - ViperSoftX C2 endpoint

ahoravideo-blog[.]xyz - Hostname - ViperSoftX C2 endpoint

ahoravideo-cdn[.]com - Hostname - ViperSoftX C2 endpoint

ahoravideo-cdn[.]xyz - Hostname - ViperSoftX C2 endpoint

ahoravideo-chat[.]com - Hostname - ViperSoftX C2 endpoint

ahoravideo-chat[.]xyz - Hostname - ViperSoftX C2 endpoint

ahoravideo-endpoint[.]xyz - Hostname - ViperSoftX C2 endpoint

ahoravideo-schnellvpn[.]com - Hostname - ViperSoftX C2 endpoint

ahoravideo-schnellvpn[.]xyz - Hostname - ViperSoftX C2 endpoint

apibilng[.]com - Hostname - ViperSoftX C2 endpoint

arrowlchat[.]com - Hostname - ViperSoftX C2 endpoint

bideo-blog[.]com - Hostname - ViperSoftX C2 endpoint

bideo-blog[.]xyz - Hostname - ViperSoftX C2 endpoint

bideo-cdn[.]com - Hostname - ViperSoftX C2 endpoint

bideo-cdn[.]xyz - Hostname - ViperSoftX C2 endpoint

bideo-chat[.]com - Hostname - ViperSoftX C2 endpoint

bideo-chat[.]xyz - Hostname - ViperSoftX C2 endpoint

bideo-endpoint[.]com - Hostname - ViperSoftX C2 endpoint

bideo-endpoint[.]xyz - Hostname - ViperSoftX C2 endpoint

bideo-schnellvpn[.]com - Hostname - ViperSoftX C2 endpoint

chatgigi2[.]com - Hostname - ViperSoftX C2 endpoint

counter[.]wmail-service[.]com - Hostname - ViperSoftX C2 endpoint

fairu-cdn[.]xyz - Hostname - ViperSoftX C2 endpoint

fairu-chat[.]xyz - Hostname - ViperSoftX C2 endpoint

fairu-endpoint[.]com - Hostname - ViperSoftX C2 endpoint

fairu-schnellvpn[.]com - Hostname - ViperSoftX C2 endpoint

fairu-schnellvpn[.]xyz - Hostname - ViperSoftX C2 endpoint

privatproxy-blog[.]com - Hostname - ViperSoftX C2 endpoint

privatproxy-blog[.]xyz - Hostname - ViperSoftX C2 endpoint

privatproxy-cdn[.]com - Hostname - ViperSoftX C2 endpoint

privatproxy-cdn[.]xyz - Hostname - ViperSoftX C2 endpoint

privatproxy-endpoint[.]xyz - Hostname - ViperSoftX C2 endpoint

privatproxy-schnellvpn[.]com - Hostname - ViperSoftX C2 endpoint

privatproxy-schnellvpn[.]xyz - Hostname - ViperSoftX C2 endpoint

static-cdn-349[.]net - Hostname - ViperSoftX C2 endpoint

wmail-blog[.]com - Hostname - ViperSoftX C2 endpoint

wmail-cdn[.]xyz - Hostname - ViperSoftX C2 endpoint

wmail-chat[.]com - Hostname - ViperSoftX C2 endpoint

wmail-schnellvpn[.]com - Hostname - ViperSoftX C2 endpoint

wmail-schnellvpn[.]xyz - Hostname - ViperSoftX C2 endpoint

Mozilla/5.0 (Windows NT; Windows NT 10.0; en-US) WindowsPowerShell/5.1.19041.2364 - User Agent -PowerShell User Agent

MITRE ATT&CK Mapping

‍Tactic - Technique - Notes

Command and Control - T1568.002 Dynamic Resolution: Domain Generation Algorithms

Command and Control - T1321 Data Encoding

Credential Access - T1555.005 Credentials from Password Stores: Password Managers

Defense Evasion - T1027 Obfuscated Files or Information

Execution - T1059.001 Command and Scripting Interpreter: PowerShell

Execution - T1204 User Execution T1204.002 Malicious File

Persistence - T1176 Browser Extensions - VenomSoftX specific

Persistence, Privilege Escalation, Defense Evasion - T1574.002 Hijack Execution Flow: DLL Side-Loading

Written by

Zoe Tilsiter

Cyber Analyst

Inside the SOC

Written by

Zoe Tilsiter

Cyber Analyst

Principal Solutions Engineer, Cyber Technician

Watch the NIS2 Webinar

Blog

AI

July 6, 2026

NIST Just Proved It: AI Security Can’t Be Solved With Rules

Static AI guardrails are inherently limited

As organizations adopt generative AI, many still assume that the right set of guardrails will be enough. The problem is you can’t anticipate every way these systems might be misused, abused or attacked. What NIST has done is put a mathematical foundation under that intuition.

In recent research building on Gödel’s incompleteness theorems, which showed that any system built on a fixed set of rules will always have gaps, NIST demonstrates that there is no finite set of guardrails that can be universally robust against adversarial prompts. In plain terms, if your defense is based on a fixed set of rules, there will always be inputs that bypass them. Not because the rules are badly written, but because the problem space is bigger than static rules can ever cover.

This is not new in cybersecurity - detection rules have always had to live with this trade-off. What is different with GenAI is the scale and shape of that problem. These systems are built on human language, and human language is not bounded. It is fluid, contextual and deliberately ambiguous. The number of ways intent can be hidden is effectively limitless. You are not defending against a defined protocol or a fixed exploit chain. You are defending against the entire expressive capacity of people.

So attempting to create a complete set of rules is the wrong starting point. It assumes the problem can be deterministically described. NIST’s work shows that it cannot. Organizations still need a way to manage AI risk, but the traditional approach of defining allowed and disallowed patterns is always going to lag behind what is actually happening. The same input can be benign in one context and risky in another, and static rules struggle to capture that distinction.

The question then is what fills that gap?

AI security must shift from rules to behavior

What's required is a shift in what you are trying to understand. Rules try to describe what should and shouldn't happen. Behavior shows you what is happening. Or to put it another way, if inputs are unbounded and adversaries adapt, the only stable signal is behavior.

In a GenAI context, that means analyzing how an AI model is being used, how prompts evolve over time, how outputs are shaped, and where AI agent interactions start to drift from what is expected. It means moving from static definitions of bad to a more dynamic understanding of intent.

Instead of trying to predict every bad prompt, you focus on identifying when behavior starts to move outside expected norms. Instead of asking whether a single input matches a rule, you ask whether the overall pattern of activity makes sense for the system and how it’s being used.

Guardrails remain important but they are only one layer

This does not eliminate the need for guardrails. They still play a role. But they will never address the entire problem space and are simply one part of your defense in depth approach.

NIST’s proof is useful because it makes this explicit. It removes the assumption that with enough effort, a complete rule set is achievable. It isn’t.

Once you accept that, the shift becomes unavoidable. This is no longer a problem of writing better rules, but of understanding behavior in a space where the possible inputs are effectively unbounded.

For security leaders, that changes the nature of the problem. It is less about defining what should be allowed, and more about recognizing when something is no longer consistent with expected behavior.

That does not remove the need for guardrails, but it does change their role. They set boundaries, but they do not define understanding. The gap between the two is where risk now sits.

In the end, this is what “can’t be solved with rules” really means. Rules will always leave gaps, and those gaps are not theoretical. They show up in how systems actually behave Not what we expect them to do, or what we intended them to do, but what they are doing in practice. That is where the signal is, and increasingly, that is where the security problem sits.

References:

https://www.nist.gov/news-events/news/2026/06/nist-mathematical-proof-supports-transition-continuous-monitor-and-update

https://ieeexplore.ieee.org/document/11475847

About the author

Andrew Hollister

Principal Solutions Engineer, Cyber Technician

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AI

July 1, 2026

5 Ways AI is changing traditional security models according to modern CISOs

The Reality of Securing AI in Motion

Traditional security tools were built for environments defined by fixed rules and predictable workflows. But AI behavior is non-deterministic. The same prompt can produce different outcomes, and risk often emerges gradually as AI behavior adapts, and permissions drift over time. This creates a constantly shifting environment where security teams are working to define control in a system that resists stability. “In AI security, yesterday's priorities can become tomorrow's blind spots. The landscape shifts that fast,” warned the SVP and Head of Technology and Cybersecurity of a real estate investment trust. Conventional approaches, which rely on establishing and maintaining a steady baseline, struggle to keep up with that level of change.

At the same time, AI adoption is accelerating across organizations, often faster than security teams can implement the controls needed to manage it. “The car is being built while it’s already on the road,” explained the CISO of a global private fund administrator. “The threats we're securing against today won't be the threats we're facing tomorrow. What kept us up three months ago looks nothing like what we're dealing with today.”

As businesses move quickly to unlock value from AI, security teams are left closing gaps in real time, while also facing adversaries who are using AI to make their attacks more scalable, adaptive, and difficult to detect. In this recent roundtable discussion of CISOs and security leaders, five themes emerged around AI cyber risk.

1. AI agents with human access but no human judgment

In Darktrace’s 2026 State of AI Cybersecurity report, 96% of the surveyed security professionals agree that AI significantly improves the speed and efficiency with which they work. Yet, 92% admitted that they’re concerned with the security implications of the use of AI agents across their workforce.

AI agents now operate with human-level permissions across systems, acting at machine speed, orchestrating actions across platforms, and making decisions without the judgment or caution a person would apply. Unlike human users, they cannot be expected to pause and question whether a given action is appropriate.

Their identities are also difficult to inventory, govern, and audit. As agents become easier to deploy than legacy IT systems ever were, organizations are quickly losing track of what is running, what it has access to, and what it is doing. This creates a growing class of highly privileged, autonomous actors operating without the visibility or oversight that traditional identity and access controls were designed to provide.“While AI adoption is critical to running a modern business, AI alone can’t solve all our cybersecurity challenges,” said a global financial sector CISO. “We still need think critically and use human judgement. Those are two things AI can’t do.”

This lack of human judgment becomes especially risky as new architectures, such as Model Context Protocol (MCP), can expand how agents connect to data, tools, and external systems. By design, MCP enables agents to dynamically discover and interact with new resources, increasing flexibility but also introducing new pathways for unintended access, data exposure, or abuse if not properly governed.

The CISO of a fund administrator highlighted one emerging vector as an example: rogue MCP servers. “Our developers want to move quickly and bring value to the business, but technologies like these can unintentionally expose sensitive data in ways that would never have happened before.”

2. Increased digital complexity and expanded attack surface

AI activity rarely stays contained. A single prompt can trigger a chain of actions across networks, email, cloud infrastructure, SaaS platforms, endpoints, identity systems, and development environments, spanning systems that were never designed to be secured as a single, connected flow. This expands both the scale and complexity of what security teams need to monitor and defend.

Yet no single control has visibility across that entire chain. “You can’t defend effectively what you can’t see,” cautioned the private fund administrator CISO. As AI-driven activity moves fluidly across environments, gaps in coverage become inevitable, creating blind spots that attackers can exploit.

Threat actors are already capitalizing on this lack of visibility. “Threat actors have advanced their use of generative AI to launch more convincing phishing campaigns, automate social engineering, and scale attacks with greater precision down to the individual level,” said the SVP of Technology and Cybersecurity for the real estate investment trust. What was once manual and targeted can now be automated and personalized at scale, making attacks harder to detect and easier to execute.

At the same time, the pace of exploitation is accelerating. As a global CISO operating across 40+ countries described it: “Zero-day vulnerabilities are no longer zero day; it’s minus one day. By the time you get to it and address it, it’s already a problem.” By the time risk is identified, it has often already been realized.

The result is a rapidly expanding and increasingly interconnected attack surface that challenges security teams to maintain visibility, context, and control across AI-driven activity.

3. Shadow AI is already everywhere

76% of organizations now cite shadow AI as a problem, one that is spreading through organizations in ways that are hard to track and even harder to control.

Employees are experimenting with publicly available Gen AI tools. Teams are spinning up low-code automations on their own. SaaS providers are quietly embedding AI into existing products. Developers are plugging AI services directly into workflows, often without pausing to consider what that exposure means.

The result is a lack of visibility into:

What AI tools are being used
What data those tools can access
Where prompts and outputs are going
Which AI agents are interacting with enterprise systems

The SVP of Cybersecurity at a real estate investment trust described the shift: “Before, I was worried about someone sending data erroneously to their personal email. Now we have all these agents online that people are utilizing, and we’re looking at those vectors as well.” For security teams, this means operating without a complete view of how AI is being used, what it can access, and where risk may already be emerging.

4. Built-in guardrails are not enough

Organizations often assume that native AI guardrails or provider-level controls are sufficient to manage AI risk. But securing AI requires ongoing visibility, oversight, and governance, not just controls configured at deployment. "It’s a misconception that adopting AI is going to solve all your problems,” warns a global financial services CISO.

Security leaders are increasingly recognizing the limitations of these controls as:

Fragmented and difficult to enforce consistently across multiple AI systems, workflows, and environments
Ambiguous in terms of accountability due to shared responsibility for AI governance between IT, security, developers, business teams, and third-party providers
Limited in end-to-end oversight, leaving gaps that stretch from the initial prompt all the way through to the downstream impact of an agent's actions

Securing AI demands more than simple prompt filtering or static policy enforcement. It requires understanding intent, behavior, and context across both human and AI activity.

The next phase of cybersecurity: securing AI

To safely and responsibly adopt AI at scale, organizations need a new operational model for cybersecurity that’s capable of:

• Understanding AI behavior

• Identifying risk in real time

• Maintaining governance without slowing innovation

The CSO of a $10 billion municipal utility organization described the challenge with precision: “We have to move at the speed of innovation and risk, because both are accelerating faster than ever.”

Embrace AI with confidence with Darktrace / SECURE AI

Darktrace has introduced Darktrace / SECURE AI™, a new product within the Darktrace ActiveAI Security Platform™ ,designed to provide enterprise-wide security for AI by applying industry leading behavioral analysis to how prompts, agents, and AI systems are used.

Darktrace / SECURE AI^TMdelivers real-time visibility and control across Enterprise and SaaS GenAI prompts, AI agent identities, development and production environments, and Shadow AI - detecting even subtle misuse, misconfiguration, and drift that traditional, rule-based controls simply do not understand. By interpreting context and intent across humans and machines, Darktrace enables organizations to adopt AI at scale without introducing unmanaged risk

What makes this possible is Darktrace’s decade-long maturity and expertise in behavioral understanding and AI-native cybersecurity. Achieved with Self-Learning AI that has been proven across more than 10,000 organizations, Darktrace understands what “normal” looks like for a business, across its users, systems, and now AI, so that meaningful deviations can be detected and acted on before they become incidents.

With one CISO describing Darktrace’s Self-Learning AI as “a leap forward compared to other tools” and another as a “force multiplier,” the technology can interpret ambiguous interactions, understand how access accumulates over time, and recognize when behavior, human or machine, begins to drift.

“Strategically, we’re looking to gain more visibility into how AI is operating across the environment and achieve greater control over what AI should be allowed to access and do,” shared the CISO at a private fund administrator.

“What I’ve seen from Darktrace / SECURE AI is extremely promising. I have tremendous confidence in Darktrace’s vision for where this is headed and its ability to execute on this new solution.”

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Check out this article by Darktrace: Unveiling ViperSoftX: A Darktrace Investigation

Unveiling ViperSoftX: A Darktrace Investigation

Fighting Info-Stealing Malware

What is ViperSoftX?

ViperSoftX Attack & Darktrace Coverage

How did the attack bypass the rest of the security stack?

Insights/Conclusion

Appendices

References

Darktrace DETECT Model Detections

Darktrace RESPOND Model Detections

List of IoCs

MITRE ATT&CK Mapping

From Click to Command: Behavioral Detection of AppleScript-Led MacOS Intrusions

NIST Just Proved It: AI Security Can’t Be Solved With Rules

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July 6, 2026

NIST Just Proved It: AI Security Can’t Be Solved With Rules

Static AI guardrails are inherently limited

AI security must shift from rules to behavior

Guardrails remain important but they are only one layer

Blog

AI

July 1, 2026

5 Ways AI is changing traditional security models according to modern CISOs

The Reality of Securing AI in Motion

The next phase of cybersecurity: securing AI

Embrace AI with confidence with Darktrace / SECURE AI