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May 5, 2020

The Ongoing Threat of Dharma Ransomware Attacks

Stay informed about the dangers of Dharma ransomware and its methods of attack, ensuring your defenses are strong against potential intrusions.
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
Max Heinemeyer
Global Field CISO
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05
May 2020

Executive summary

  • In the past few weeks, Darktrace has observed an increase in attacks against internet-facing systems, such as RDP. The initial intrusions usually take place via existing vulnerabilities or stolen, legitimate credentials. The Dharma ransomware attack described in this blog post is one such example.
  • Old threats can be damaging – Dharma and its variants have been around for four years. This is a classic example of ‘legacy’ ransomware morphing and adapting to bypass traditional defenses.
  • The intrusion shows signs that indicate the threat-actors are aware of – and are actively exploiting – the COVID-19 situation.
  • In the current threat landscape surrounding COVID-19, Darktrace recommends monitoring internet-facing systems and critical servers closely – keeping track of administrative credentials and carefully considering security when rapidly deploying internet-facing infrastructure.

Introduction

In mid-April, Darktrace detected a targeted Dharma ransomware attack on a UK company. The initial point of intrusion was via RDP – this represents a very common attack method of infection that Darktrace has observed in the broader threat landscape over the past few weeks.

This blog post highlights every stage of the attack lifecycle and details the attacker’s techniques, tools and procedures (TTP) – all detected by Darktrace.

Dharma – a varient of the CrySIS malware family – first appeared in 2016 and uses multiple intrusion vectors. It distributes its malware as an attachment in a spam email, by disguising it as an installation file for legitimate software, or by exploiting an open RDP connection through internet-facing servers. When Dharma has finished encrypting files, it drops a ransom note with the contact email address in the encrypted SMB files.

Darktrace had strong, real-time detections of the attack – however the absence of eyes on the user interface prior to the encryption activity, and without Autonomous Response deployed in Active Mode, these alerts were only actioned after the ransomware was unleashed. Fortunately, it was unable to spread within the organization, thanks to human intervention at the peak of the attack. However, Darktrace Antigena in active mode would have significantly slowed down the attack.

Timeline

The timeline below provides a rough overview of the major attack phases over five days of activity.

Figure 1: A timeline of the attack

Technical analysis

Darktrace detected that the main device hit by the attack was an internet-facing RDP server (‘RDP server’). Dharma used network-level encryption here: the ransomware activity takes place over the network protocol SMB.

Below is a chronological overview of all Darktrace detections that fired during this attack: Darktrace detected and reported every single unusual or suspicious event occurring on the RDP server.

Figure 2: An overview of Darktrace detections

Initial compromise

On April 7, the RDP server began receiving a large number of incoming connections from rare IP addresses on the internet.

On April 7, the RDP server began receiving a large number of incoming connections from rare IP addresses on the internet. This means a lot of IP addresses on the internet that usually don’t connect to this company started connection attempts over RDP. The top five cookies used to authenticate show that the source IPs were located in Russia, the Netherlands, Korea, the United States, and Germany.

It is highly likely that the RDP credential used in this attack had been compromised prior to the attack – either via common brute-force methods, credential stuffing attacks, or phishing. Indeed, a TTP growing in popularity is to buy RDP credentials on marketplaces and skip to initial access.

Attempted privilege escalation

The following day, the malicious actor abused the SMB version 1 protocol, notorious for always-on null sessions which offer unauthenticated users’ information about the machine – such as password policies, usernames, group names, machine names, user and host SIDs. What followed was very unusual: the server connected externally to a rare IP address located in Morocco.

Next, the attacker attempted a failed SMB session to the external IP over an unusual port. Darktrace detected this activity as highly anomalous, as it had previously learned that SMB is usually not used in this fashion within this organization – and certainly not for external communication over this port.

Figure 3: Darktrace detecting the rare external IP address

Figure 4: The SMB session failure and the rare connection over port 1047

Command and control traffic

As the entire attack occurred over five days, this aligns with a smash-and-grab approach, rather than a highly covert, low-and-slow operation.

Two hours later, the server initiated a large number of anomalous and rare connections to external destinations located in India, China, and Italy – amongst other destinations the server had never communicated with before. The attacker was now attempting to establish persistence and create stronger channels for command and control (C2). As the entire attack occurred over five days, this aligns with a smash-and-grab approach, rather than a highly covert, low-and-slow operation.

Actions on target

Notwithstanding this approach, the malicious actor remained dormant for two days, biding their time until April 10 — a public holiday in the UK — when security teams would be notably less responsive. This pause in activity provides supporting evidence that the attack was human-driven.

Figure 5: The unusual RDP connections detected by Darktrace

The RDP server then began receiving incoming remote desktop connections from 100% rare IP addresses located in the Netherlands, Latvia, and Poland.

Internal reconnaissance

The IP address 85.93.20[.]6, hosted at the time of investigation in Panama, made two connections to the server, using an administrative credential. On April 12, as other inbound RDP connections scanned the network, the volume of data transferred by the RDP server to this IP address spiked. The RDP server never scans the internal network. Darktrace identified this as highly unusual activity.

Figure 6: Darktrace detects the anomalous external data transfer

Lateral movement and payload execution

Finally, on April 12, the attackers executed the Dharma payload at 13:45. The RDP server wrote a number of files over the SMB protocol, appended with a file extension containing a throwaway email account possibly evoking the current COVID-19 pandemic, ‘cov2020@aol[.]com’. The use of string ‘…@aol.com].ROGER’ and presence of a file named ‘FILES ENCRYPTED.txt’ resembles previous Dharma compromises.

Parallel to the encryption activity, the ransomware tried to spread and infect other machines by initiating successful SMB authentications using the same administrator credential seen during the internal reconnaissance. However, the destination devices did not encrypt any files themselves.

It was during the encryption activity that the internal IT staff pulled the plug from the compromised RDP server, thus ending the ransomware activity.

Conclusion

This incident supports the idea that ‘legacy’ ransomware may morph to resurrect itself to exploit vulnerabilities in remote working infrastructure during this pandemic.

Dharma executed here a fast-acting, planned, targeted, ransomware attack. The attackers used off-the-shelf tools (RDP, abusing SMB1 protocol) blurring detection and attribution by blending in with typical administrator activity.

Darktrace detected every stage of the attack without having to depend on threat intelligence or rules and signatures, and the internal security team acted on the malicious activity to prevent further damage.

This incident supports the idea that ‘legacy’ ransomware may morph to resurrect itself to exploit vulnerabilities in remote working infrastructure during this pandemic. Poorly-secured public-facing systems have been rushed out and security is neglected as companies prioritize availability – sacrificing security in the process. Financially-motivated actors weaponize these weak points.

The use of the COVID-related email ‘cov2020@aol[.]com’ during the attack indicates that the threat-actor is aware of and abusing the current global pandemic.

Recent attacks, such as APT41’s exploitation of the Zoho Manage Engine vulnerability last March, show that attacks against internet-facing infrastructure are gaining popularity as the initial intrusion vector. Indeed, as many as 85% of ransomware attacks use RDP as an entry vector. Ensuring that backups are isolated, configurations are hardened, and systems are patched is not enough – real-time detection of every anomalous action can help protect potential victims of ransomware.

Technical Details

Some of the detections on the RDP server:

  • Compliance / Internet Facing RDP server – exposure of critical server to Internet
  • Anomalous Connection / Application Protocol on Uncommon Port – external connections using an unusual port to rare endpoints
  • Device / Large Number of Connections to New Endpoints – indicative of peer-to-peer or scanning activity
  • Compliance / Incoming Remote Desktop – device is remotely controlled from an external source, increased rick of bruteforce
  • Compromise / Ransomware / Suspicious SMB Activity – reading and writing similar volumes of data to remote file shares, indicative of files being overwritten and encrypted
  • Anomalous File / Internal / Additional Extension Appended to SMB File – device is renaming network share files with an added extension, seen during ransomware activity

The graph below shows the timeline of Darktrace detections on the RDP server. The attack lifecycle is clearly observable.

Figure 7: The model breaches occurring over time

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
Max Heinemeyer
Global Field CISO

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March 26, 2026

Phantom Footprints: Tracking GhostSocks Malware

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Why are attackers using residential proxies?

In today's threat landscape, blending in to normal activity is the key to success for attackers and the growing reliance on residential proxies shows a significant shift in how threat actors are attempting to bypass IP detection tools.

The increasing dependency on residential proxies has exposed how prevalent proxy services are and how reliant a diverse range of threat actors are on them. From cybercriminal groups to state‑sponsored actors, the need to bypass IP detection tools is fundamental to the success of these groups. One malware that has quietly become notorious for its ability to avoid anomaly detection is GhostSocks, a malware that turns compromised devices into residential proxies.

What is GhostSocks?

Originally marketed on the Russian underground forum xss[.]is as a Malware‑as‑a‑Service (MaaS), GhostSocks enables threat actors to turn compromised devices into residential proxies, leveraging the victim's internet bandwidth to route malicious traffic through it.

How does Ghostsocks malware work? 

The malware offers the threat actor a “clean” IP address, making it look like it is coming from a household user. This enables the bypassing of geographic restrictions and IP detection tools, a perfect tool for avoiding anomaly detection. It wasn’t until 2024, when a partnership was announced with the infamous information stealer Lumma Stealer, that GhostSocks surged into widespread adoption and alluded to who may be the author of the proxy malware.

Written in GoLang, GhostSocks utilizes the SOCKS5 proxy protocol, creating a SOCKS5 connection on infected devices. It uses a relay‑based C2 implementation, where an intermediary server sits in between the real command-and-control (C2) server and the infected device.

How does Ghostsocks malware evade detection?

To further increase evasion, the Ghostsocks malware wraps its SOCKS5 tunnels in TLS encryption, allowing its malicious traffic to blend into normal network traffic.

Early variants of GhostSocks do not implement a persistence mechanism; however, later versions achieve persistence via registry run keys, ensuring sustained proxy operational time [1].

While proxying is its primary purpose, GhostSocks also incorporates backdoor functionality, enabling malicious actors to run arbitrary commands and download and deploy additional malicious payloads. This was evident with the well‑known ransomware group Black Basta, which reportedly used GhostSocks as a way of maintaining long‑term access to victims’ networks [1].

Darktrace’s detection of GhostSocks Malware

Darktrace observed a steady increase in GhostSocks activity across its customer base from late 2025, with its Threat Research team identifying multiple incidents involving the malware. In one notable case from December 2025, Darktrace detected GhostSocks operating alongside Lumma Stealer, reinforcing that the partnership between Lumma and GhostSocks remains active despite recent attempts to disrupt Lumma’s infrastructure.

Darktrace’s first detection of GhostSocks‑related activity came when a device on the network of a customer in the education sector began making connections to an endpoint with a suspicious self‑signed certificate that had never been seen on the network before.

The endpoint in question, 159.89.46[.]92 with the hostname retreaw[.]click, has been flagged by multiple open‑source intelligence (OSINT) sources as being associated with Lumma Stealer’s C2 infrastructure [2], indicating its likely role in the delivery of malicious payloads.

Darktrace’s detection of suspicious SSL connections to retreaw[.]click, indicating an attempted link to Lumma C2 infrastructure.
Figure 1: Darktrace’s detection of suspicious SSL connections to retreaw[.]click, indicating an attempted link to Lumma C2 infrastructure.

Less than two minutes later, Darktrace observed the same device downloading the executable (.exe) file “Renewable.exe” from the IP 86.54.24[.]29, which Darktrace recognized as 100% rare for this network.

Darktrace’s detection of a device downloading the unusual executable file “Renewable.exe”.
Figure 2: Darktrace’s detection of a device downloading the unusual executable file “Renewable.exe”.

Both the file MD5 hash and the executable itself have been identified by multiple OSINT vendors as being associated with the GhostSocks malware [3], with the executable likely the backdoor component of the GhostSocks malware, facilitating the distribution of additional malicious payloads [4].

Following this detection, Darktrace’s Autonomous Response capability recommended a blocking action for the device in an early attempt to stop the malicious file download. In this instance, Darktrace was configured in Human Confirmation Mode, meaning the customer’s security team was required to manually apply any mitigative response actions. Had Autonomous Response been fully enabled at the time of the attack, the connections to 86.54.24[.]29 would have been blocked, rendering the malware ineffective at reaching its C2 infrastructure and halting any further malicious communication.

 Darktrace’s Autonomous Response capability suggesting blocking the suspicious connections to the unusual endpoint from which the malicious executable was downloaded.
Figure 3: Darktrace’s Autonomous Response capability suggesting blocking the suspicious connections to the unusual endpoint from which the malicious executable was downloaded.

As the attack was able to progress, two days later the device was detected downloading additional payloads from the endpoint www.lbfs[.]site (23.106.58[.]48), including “Setup.exe”, “,.exe”, and “/vp6c63yoz.exe”.

Darktrace’s detection of a malicious payload being downloaded from the endpoint www.lbfs[.]site.
Figure 4: Darktrace’s detection of a malicious payload being downloaded from the endpoint www.lbfs[.]site.

Once again, Darktrace recognized the anomalous nature of these downloads and suggested that a “group pattern of life” be enforced on the offending device in an attempt to contain the activity. By enforcing a pattern of life on a device, Darktrace restricts its activity to connections and behaviors similar to those performed by peer devices within the same group, while still allowing it to carry out its expected activity, effectively preventing deviations indicative of compromise while minimizing disruption. As mentioned earlier, these mitigative actions required manual implementation, so the activity was able to continue. Darktrace proceeded to suggest further actions to contain subsequent malicious downloads, including an attempt to block all outbound traffic to stop the attack from progressing.

An overview of download activity and the Autonomous Response actions recommended by Darktrace to block the downloads.
Figure 5: An overview of download activity and the Autonomous Response actions recommended by Darktrace to block the downloads.

Around the same time, a third executable download was detected, this time from the hostname hxxp[://]d2ihv8ymzp14lr.cloudfront.net/2021-08-19/udppump[.]exe, along with the file “udppump.exe”.While GhostSocks may have been present only to facilitate the delivery of additional payloads, there is no indication that these CloudFront endpoints or files are functionally linked to GhostSocks. Rather, the evidence points to broader malicious file‑download activity.

Shortly after the multiple executable files had been downloaded, Darktrace observed the device initiating a series of repeated successful connections to several rare external endpoints, behavior consistent with early-stage C2 beaconing activity.

Cyber AI Analyst’s investigation

Darktrace’s detection of additional malicious file downloads from malicious CloudFront endpoints.
Figure 7: Darktrace’s detection of additional malicious file downloads from malicious CloudFront endpoints.

Throughout the course of this attack, Darktrace’s Cyber AI Analyst carried out its own autonomous investigation, piecing together seemingly separate events into one wider incident encompassing the first suspicious downloads beginning on December 4, the unusual connectivity to many suspicious IPs that followed, and the successful beaconing activity observed two days later. By analyzing these events in real-time and viewing them as part of the bigger picture, Cyber AI Analyst was able to construct an in‑depth breakdown of the attack to aid the customer’s investigation and remediation efforts.

Cyber AI Analyst investigation detailing the sequence of events on the compromised device, highlighting its extensive connectivity to rare endpoints, the related malicious file‑download activity, and finally the emergence of C2 beaconing behavior.
Figure 8: Cyber AI Analyst investigation detailing the sequence of events on the compromised device, highlighting its extensive connectivity to rare endpoints, the related malicious file‑download activity, and finally the emergence of C2 beaconing behavior.

Conclusion

The versatility offered by GhostSocks is far from new, but its ability to convert compromised devices into residential proxy nodes, while enabling long‑term, covert network access—illustrates how threat actors continue to maximise the value of their victims’ infrastructure. Its growing popularity, coupled with its ongoing partnership with Lumma, demonstrates that infrastructure takedowns alone are insufficient; as long as threat actors remain committed to maintaining anonymity and can rapidly rebuild their ecosystems, related malware activity is likely to persist in some form.

Credit to Isabel Evans (Cyber Analyst), Gernice Lee (Associate Principal Analyst & Regional Consultancy Lead – APJ)
Edited by Ryan Traill (Content Manager)

Appendices

References

1.    https://bloo.io/research/malware/ghostsocks

2.    https://www.virustotal.com/gui/domain/retreaw.click/community

3.    https://synthient.com/blog/ghostsocks-from-initial-access-to-residential-proxy

4.    https://www.joesandbox.com/analysis/1810568/0/html

5. https://www.virustotal.com/gui/url/fab6525bf6e77249b74736cb74501a9491109dc7950688b3ae898354eb920413

Darktrace Model Detections

Real-time Detection Models

Anomalous Connection / Suspicious Self-Signed SSL

Anomalous Connection / Rare External SSL Self-Signed

Anomalous File / EXE from Rare External Location

Anomalous File / Multiple EXE from Rare External Locations

Compromise / Possible Fast Flux C2 Activity

Compromise / Large Number of Suspicious Successful Connections

Compromise / Large Number of Suspicious Failed Connections

Compromise / Sustained SSL or HTTP Increase

Autonomous Response Models

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

Antigena / Network / External Threat / Antigena Suspicious File Block

Antigena / Network / Significant Anomaly / Antigena Controlled and Model Alert

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

Antigena / Network / Significant Anomaly / Antigena Alerts Over Time Block

Antigena / Network / External Threat / Antigena Suspicious Activity Block

MITRE ATT&CK Mapping

Tactic – Technique – Sub-Technique

Resource Development – T1588 - Malware

Initial Access - T1189 - Drive-by Compromise

Persistence – T1112 – Modify Registry

Command and Control – T1071 – Application Layer Protocol

Command and Control – T1095 – Non-application Layer Protocol

Command and Control – T1071 – Web Protocols

Command and Control – T1571 – Non-Standard Port

Command and Control – T1102 – One-Way Communication

List of Indicators of Compromise (IoCs)

86.54.24[.]29 - IP - Likely GhostSocks C2

http[://]86.54.24[.]29/Renewable[.]exe - Hostname - GhostSocks Distribution Endpoint

http[://]d2ihv8ymzp14lr.cloudfront[.]net/2021-08-19/udppump[.]exe - CDN - Payload Distribution Endpoint

www.lbfs[.]site - Hostname - Likely C2 Endpoint

retreaw[.]click - Hostname - Lumma C2 Endpoint

alltipi[.]com - Hostname - Possible C2 Endpoint

w2.bruggebogeyed[.]site - Hostname - Possible C2 Endpoint

9b90c62299d4bed2e0752e2e1fc777ac50308534 - SHA1 file hash – Likely GhostSocks payload

3d9d7a7905e46a3e39a45405cb010c1baa735f9e - SHA1 file hash - Likely follow-up payload

10f928e00a1ed0181992a1e4771673566a02f4e3 - SHA1 file hash - Likely follow-up payload

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About the author
Gernice Lee
Associate Principal Analyst & Regional Consultancy Lead

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March 27, 2026

State of AI Cybersecurity 2026: 92% of security professionals concerned about the impact of AI agents

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The findings in this blog are taken from Darktrace's annual State of AI Cybersecurity Report 2026.

AI is already embedded in day-to-day enterprise activity, with 78% of participants in one recent survey reporting that their organizations are using generative AI in at least one business function. Generative AI now acts as an always-on assistant, researcher, creator, and coach across an expanding array of departments and functions. Autonomous agents are performing multi-step operational workflows from end to end. AI features have been layered on top of every SaaS application. And vibe coding is making it possible for employees without deep technical expertise to build their own AI-powered automations.

According to Gartner, more than 80% of enterprises will have deployed GenAI models, applications, or APIs in production environments by the end of this year, up from less than 5% in 2023. Companies report a 130% increase in spending on AI over the same period, with 72% of business leaders using AI tools at least weekly. The outsized efficiency and productivity gains that were once a future vision are quickly becoming everyday reality.

AI is currently driving business growth and innovation, and organizations risk falling behind peers if they don’t keep up with the pace of adoption, but it is also quietly expanding the enterprise attack surface. The modern CISO is challenged to both enable innovation and protect the business from these emerging threats.

AI agents introduce new risks and vulnerabilities

AI agents are playing growing roles in enterprise production environments. In many cases, these agents act with broad permissions across multiple software systems and platforms. This means they’re granted far-reaching access – to sensitive data, business-critical applications, tokens and APIs, and IT and security tools. With this access comes risk for security leaders – 92% are concerned about the use of AI agents across the workforce and their impact on security.

These agents must be governed as identities, with least-privilege access and ongoing monitoring. They can’t be thought of as invisible aspects of the application estate. Understanding how AI agents behave, and how to manage their permissions, control their behavior, and limit their data access will be a top security priority throughout 2026.

Generative AI prompts: The next frontier

Prompts are how users – both human and agentic – interact with AI systems, and they’re where natural language gets translated into model behavior. Natural language is infinite in its potential combinations and permutations, making this aspect of the attack surface open-ended and far more complex than traditional CVEs. With carefully crafted prompts, bad actors may be able to coax models into disclosing sensitive data, bypassing guardrails, or initiating undesirable actions.

Among security leaders, the biggest worries about AI usage in their environments all involve ways that systems might be manipulated to bypass traditional controls.

  • 61% are most concerned about the exposure of sensitive data
  • 56% are most concerned about potential data security and policy violations
  • 51% are most concerned about the misuse or abuse of AI tools

The more employees rely on AI in their day-to-day workflows, the more critical it becomes for security teams to understand how prompt behavior determines model behavior – and where that behavior could go wrong.

What does “securing AI” mean in practice?

AI adoption opens new security risks that blur the boundaries between traditional security disciplines. A single malicious interaction with an AI model could involve identity misuse, sensitive data exposure, application logic abuse, and supply chain risk – all within a single workflow. Protecting this dynamic and rapidly evolving attack surface requires an approach that spans identity security, cloud security, application security, data security, software development security, and more.

The task for security leaders is to implement the tools, policies, and frameworks to mitigate these novel, expansive, and cross-disciplinary risks.

However, within most enterprises, AI policy creation remains in its infancy. Just 37% of security leaders report that their organization has a formal AI policy, representing a small but worrisome decrease from last year. Conversations about AI abound: in 52% of organizations, there’s discussion about an AI policy. Still, talk is cheap, and leaders will need to take action if they’re to successfully enable secure AI innovation.

To govern and protect their AI systems, organizations must take a multi-pronged approach. This requires building out policies, but it also demands that they are able to:

  • Monitor the prompts driving GenAI assistants and agents in real time. Organizations must be able to inspect prompts, sessions, and responses across enterprise GenAI tools, low- and high-code environments, and SaaS and SASE so that they can detect clever conversational prompt attacks and malicious chaining.
  • Secure all business AI agent identities. Security teams need to identify all the agents acting within their environment and supply chain, map their connections and interactions via MCP and services like Amazon S3, and audit their behavior across the cloud, SaaS environments, and on the network and endpoint devices.
  • Maintain centralized, comprehensive visibility. Understanding intent, assessing risks, and enforcing policies all require that security teams have a single view that spans AI interactions across the entire business.
  • Discover and control shadow AI. Teams need to be able to identify unsanctioned AI activities, distinguish the misuse of legitimate tools from their appropriate use, and apply policies to protect data, while guiding users towards approved solutions.

Scaling AI safely and responsibly

The approach that most cybersecurity vendors have taken – using historical patterns to predict future threats – doesn’t work well for AI systems. Because AI changes its behavior in response to the information it encounters while taking action, previous patterns don’t indicate what it will do next. Looking at past attacks can’t tell you how complex models will behave in your individual business.

Securing AI requires interpreting ambiguous interactions, uncovering subtleties that reveal intent within extended conversations, understanding how access accumulates over time, and recognizing when behavior – both human and machine – begins to drift towards areas of risk. To do this, you need to understand what “normal” looks like in each unique organization: how users, systems, applications, and AI agents behave, how they communicate, and how data flows between them.

Darktrace has spent more than a decade designing AI-powered solutions that can understand and adapt to evolving behavior in complex environments. This technology learns directly from the environment it protects, identifying malicious actions that deviate from normal operations, so that it can stop AI-related threats on the very first encounter.

As AI adoption reshapes enterprise operations, humans and machines will collaborate more and more often. This collaboration might dramatically expand the attack surface, but it also has the potential to be a force multiplier for defenders.

Explore the full State of AI Cybersecurity 2026 report for deeper insights into how security leaders are responding to AI-driven risks.

Learn more about securing AI in your enterprise.

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