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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.
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
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03
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

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

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July 24, 2026

Darktrace / EMAIL Expands Behavioral Defense Across Email and Collaboration Workflows

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Email and collaboration tools do more than carry messages. They are where organizations approve payments, share sensitive data, reset credentials, and make thousands of everyday decisions. Increasingly, they are interfaces through which humans direct AI agents in their daily activity. Email, Slack and Teams are high volume, rich with sensitive data, and an easy place to hide malicious activity.

The opportunity isn’t lost on bad actors. Darktrace / EMAIL detected more than 32 million high-confidence phishing emails globally in 2025, and 70% of those messages passed DMARC authentication.  Phishing is increasingly difficult to detect and familiar trust signals alone are not enough. People and security teams need to understand how a message fits the normal behavior of the sender, recipient, and organization. They also need to correlate activity across platforms to spot threats that span multiple channels.

To effectively secure against today’s evolved threats, security teams need to act at two levels: they need to help each employee make a safer decision ‘in the moment’, and they need to understand the wider patterns that may expose the business to risk.

Darktrace is introducing four new capabilities in Darktrace / EMAIL to address both challenges. The new features explain suspicious content more clearly to end users, strengthen the capabilities of Darktrace / Adaptive Human Defense with richer guidance, let organizations define their own patterns for detecting sensitive data in messages, and give security teams a process-level view of risk across email and collaboration workflows.

Darktrace / EMAIL Inbox Analysis highlights risky content within your emails

A warning is more useful when it explains what the user should look at. To help do that, we’ve expanded Darktrace / EMAIL’s Inbox Analysis Add-In to highlight potentially dangerous content within the body of emails that Darktrace / EMAIL flags as potentially suspicious or high risk.  

The add-in can highlight language designed to create urgency, financial references, requests for payment, suspicious links, and content that is unusual for the sender. Each highlighted element includes a pop up that explains why it may be suspicious. Instead of asking an employee to accept a verdict without context, the analysis helps them examine the message and make a more informed decision.

Enhanced Just-In-Time Training Banners in Darktrace / Adaptive Human Defense

Enhanced Just-In-Time Training Banners build on the same principle. The banners now include a contextual header, actionable advice, and specific detection context. This gives employees more useful guidance at the point of risk without adding unnecessary information or cognitive load.

Together, the capabilities help turn a warning into a short learning moment. Employees can see what looks unusual, understand what action to take, and build their judgment.

Custom Sensitive Data Detection in Darktrace / EMAIL - Data Loss Prevention

Sensitive data is different for every business. Standard categories such as payment card details or government identifiers matter, but organizations also have their own customer codes, project names, research formats, account structures, and internal identifiers.

Custom Sensitive Data Detection in Darktrace / EMAIL - Data Loss Prevention allows administrators to write custom expressions for the data their organization needs to protect. Matched content can trigger existing model actions and data loss prevention (DLP) workflows, extending Darktrace's DLP capabilities.

This extends data loss detection beyond a fixed library of common data types. Security teams can apply controls to information that is sensitive in the context of their own organization and adapt those controls as the business changes.

Introducing Email and Collaboration Workflow Risk Posture Dashboards

Some of the most important risks are not isolated events. They are repeated ways of working that create an opening for error, misuse, or attack. For example, a payment request may be one suspicious message, but a recurring approval workflow that relies on weak verification is a business process risk.

The new Email and Collaboration Workflow Risk Posture Dashboard analyzes email and collaboration data across Email, Microsoft Teams, Slack and Zoom to provide a process-level view of risk in the organization. These may include financial authorization workflows, sensitive data sharing patterns, and activity that could expose credentials.

The dashboard brings these patterns into a view and provides actionable recommendations. This helps security teams determine where to investigate or strengthen controls, where ownership needs to be clarified, and where the business may need to change a risky process. It gives CISOs a clearer view of how human and communication risk is embedded in everyday operations, not only where individual alerts occur.

Behavior connects the individual decision to the wider risk

These capabilities build on Darktrace’s unique behavioral approach to security. We use Adaptive AI to learn how people and AI normally behave within an organization, creating the context needed to recognize when activity changes.

Within the Darktrace Behavioral Defense Platform, Darktrace / EMAIL helps protect people against phishing, account takeover, data exfiltration, and human risk across email and collaboration tools. The new capabilities extend that protection in both directions. They give employees clearer context for the decision in front of them, while giving security leaders a broader view of the workflows and behavior that create risk across the organization.

The result is not simply more alerts. It is a better understanding of why something is risky, what action to take, and where the organization can reduce risk before a familiar process becomes an easy route for an attacker.

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Carlos Gray
Senior Product Marketing Manager, Email

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July 24, 2026

When Guardrails Break: Why Securing AI Requires Behavioral Detection and Autonomous Containment

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Bottom line up front: Governance, guardrails, identity controls, and secure development are necessary to secure AI, but they are not sufficient. AI systems are probabilistic, adaptive, and non-deterministic. Therefore, organizations need two critical layers of security:

  1. Behavioral-based detection that can identify when AI begins to act outside its intended purpose; and  
  2. Surgical, explainable autonomous containment that can stop risky activity before it causes material damage.  

That capability depends on multiple specialized AI models working together, not one LLM making every decision.

Organizations are embedding AI into development, business operations, and security workflows faster than most security programs can adapt. The risk is no longer limited to the model. It extends across prompts, data, identities, agents, memory, APIs, tools, permissions, and the trust relationships connecting them.

In my recent blog, Securing AI: Analysis of the Complete Security Stack with Governance and Controls, I outlined a defense-in-depth strategy spanning governance, identity, data security, secure development, runtime detection, autonomous containment, and recovery. The most urgent requirement across that architecture is the ability to understand how AI behaves in practice and contain it when that behavior becomes risky.  

Why non-deterministic systems require behavioral-based detection

Traditional controls remain foundational. Organizations need least privilege, strong identity controls, secure-by-design architecture, data governance, AI inventories, guardrails, testing, and clear boundaries on autonomy.

But deterministic controls, which assume predictable and repeatable behavior, cannot fully secure non-deterministic systems, where the same input may not always produce the same outcome.

AI agents can interpret the same instruction differently, chain individually authorized actions into an unsafe outcome, or pursue a legitimate goal through a method the organization did not anticipate. One of the most recent examples of this is the incident that OpenAI and Hugging Face jointly disclosed, where an autonomous agent escaped its intended testing boundaries and compromised Hugging Face infrastructure.  

An agent may have permission to access data and invoke a tool, but that does not mean every use of that access is appropriate. It is not enough to know whether an action is allowed. Organizations need to know whether it makes sense.

  • Is this normal for this agent?  
  • Is it acting within its intended purpose?  
  • Is it accessing unusual data, invoking an unexpected tool, or beginning to drift?  
  • Do a series of ordinary-looking actions become risky when viewed together?

Behavioral-based detection specific to an environment or organization with an understanding of context and risk enables provides the needed detection engineering for AI systems. It learns normal activity across people, systems, data, devices, and AI agents, then identifies deviations and evaluates their risk, intent, and context. This enables detection of misuse, abuse, compromise, manipulation, and unintended behavior even when no known attack signature or explicit policy violation exists.

Why accuracy is the foundation for SOC optimization

AI will only improve the SOC if it produces accurate, explainable, and actionable outcomes.

If analysts must manually validate every AI-generated finding because they cannot understand the evidence or confidence behind it, automation has not reduced workload. It has moved the workload. False positives increase fatigue. False negatives cause the most risk and damage to organizations. Inaccurate autonomous actions can disrupt critical operations.

Accuracy is therefore more than a model-performance metric. It is the prerequisite for analyst trust, SOC optimization, and safe autonomous response.

That accuracy is unlikely to come from one model.

Generative AI is valuable for natural-language analysis, summarization, and human interaction. But an LLM should not be the sole analytical engine for behavioral-based detection, investigation, risk assessment, and containment. Interpretability and consistency are required for high-consequence security decisions.

A stronger architecture uses multiple specialized AI systems collaboratively:  

  • Behavioral models can establish normal activity.  
  • Unsupervised learning can identify novel anomalies.  
  • Graph analysis can evaluate relationships among agents, identities, systems, and tools.  
  • Other models can correlate events, investigate competing hypotheses, and assess risk.  
  • Semantic models can analyze language where behavior-based language analysis is needed but this can be used in tandem with vector embeddings, graph neural networks, and a variety of other AI systems.

Each model contributes a different analytical perspective. Their outputs can corroborate one another, improving accuracy and creating a more reliable basis for response. The objective is not one model operating as an oracle. It is layered, adaptive intelligence designed to produce decisions the SOC can understand and trust.

Autonomous containment is required to secure autonomous systems

Many SOCs remain hesitant to trust LLM-based agents with autonomous containment. That concern is reasonable. A poorly selected response can isolate the wrong asset, stop a critical workflow, block a legitimate identity, or create more operational damage than the original incident.

But relying exclusively on human response is also not viable.

AI systems can operate at machine speed. They can expose sensitive data, execute workflows, modify records, call tools, or propagate actions across connected systems before an analyst can investigate and intervene. The behavior may be unintentional, the result of an agent optimizing toward a goal, or caused by misuse, compromise, prompt injection, or offensive AI.

Intent affects the investigation. It does not change the need to stop the damage.

Organizations need autonomous response, but it must be surgical and explainable. The objective is not to shut down an entire agent, user, application, or business process whenever an anomaly occurs. It is to interrupt the specific risky behavior: block an unusual connection, constrain a tool call, stop an abnormal data transfer, or temporarily limit an agent when it is performing anomalous, risky activity.  

That buys humans time. It stops the spread, limits damage, and allows the SOC to investigate without unnecessarily disrupting the business.

Layered, Adaptive AI provides a path forward

Darktrace has spent more than a decade researching and operationalizing layered, behavioral, Adaptive AI that learns a specific organization rather than relying only on historic attacks or predefined signatures.

The approach is designed to understand normal behavior, identify anomalous activity, assess its risk, correlate related events, autonomously investigate, and, when necessary, apply targeted containment while normal operations continue.

That sequence matters. Autonomous response cannot simply be added to the end of an LLM workflow. Trusted containment depends on broad visibility, continuous behavioral understanding, multiple analytical techniques, risk and context evaluation, autonomous investigation, explainability, and precise response actions.

This represents a more responsible model for security autonomy: not automation for its own sake, but controlled autonomy built to improve security outcomes and protect business operations.

Security must enable AI adoption

The answer for security teams is not to block AI. Organizations are adopting it to improve productivity, accelerate development, and create new business value.

But innovation without behavioral detection and autonomous containment is not sustainable.

Organizations should continue investing in governance, identity, least privilege, data security, secure MLOps, guardrails, testing, evaluation, validation, verification, kill switches, rollback, and forensic readiness. At the same time, they cannot wait for every governance program to mature before addressing runtime risk.

Behavioral-based detection and autonomous containment provide an immediate layer of resilience. They allow organizations to detect exploitation and risky AI behavior they did not anticipate, contain it at machine speed, and preserve human control over broader remediation.

The future of AI security will not be defined by a single model making every decision. It will be defined by multiple specialized AI systems working collaboratively, with sufficient accuracy, transparency, and context to support trusted autonomous action.

Surgical, explainable autonomous containment is no longer a future capability. It is a requirement for scaling AI securely today.

Learn how to build a defense-in-depth strategy for securing AI at scale in our talk at Black Hat on August 5 at 3:15 PM.  

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About the author
Nicole Carignan
SVP, Security & AI Strategy, Field CISO
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