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September 19, 2021

Defending Tokyo Olympics: AI Neutralizes IoT Attack

Learn how Darktrace autonomously thwarted a cyber-attack on a national sporting body before the Tokyo Olympics in this detailed breakdown.
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
Oakley Cox
Director of Product
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19
Sep 2021

One of the greatest issues in security is how to deal with high-stress scenarios when there is a significant breach, and there is too much to do in too little time. The nightmare scenario for any CISO is when this happens during a critical moment for the organization: an important acquisition, a crucial news announcement, or in this case, a global sporting event attracting an audience of millions.

Threat actors often exploit the pressure of these events to cause disruption or extract hefty sums. Sporting occasions, especially Formula 1 races, the Super Bowl, and the Olympics, attract a great deal of criminal interest.

The games begin

There have been several recorded attacks and data breaches at the Olympics this year, including an incident when a volleyball commentator asked his colleague for his computer password – not realizing he was still on air.

In a more nefarious case discovered by Darktrace, a Raspberry Pi device was covertly implanted into a national sporting body directly involved in the Olympics, in an attempt to exfiltrate sensitive data. The events took place one week before the start of the Games, and a data breach at this time would have had significant ramifications for the reputation of the organization, the confidentiality of their plans, and potentially the safety of their athletes.

Darktrace AI recognized this activity as malicious given its evolving understanding of ‘self’ for the organization, and Antigena – Darktrace’s autonomous response capability – took action at machine speed to interrupt the threat, affording the human security team the critical time they needed to catch up and neutralize the attack.

In what follows, we break down the attack.

Figure 1: The overall dwell time was three days.

Breaking down the attack

July 15, 14:09 — Initial intrusion

An unauthorized Raspberry Pi device connected to the organization’s digital environment – disguised and named in a way which mimicked the corporate naming convention. As a small IoT device, Raspberry Pis can be easily hidden and are difficult to locate physically in large environments. They have been used in various high-profile hacks in the past including the 2018 NASA breach.

IoT devices – from printers to fish tanks – pose a serious risk to security, as they can be exploited to gather information, move laterally, and escalate privileges.

July 15, 15:25 — External VPN activity

Anomalous UDP connections were made to an external endpoint over port 1194 (Open VPN activity). URIs showed that the device downloaded data potentially associated with Open VPN configuration files. This could represent an attempt to establish a secure channel for malicious activity such as data exfiltration.

By establishing an outgoing VPN, the attacker obfuscated their activity and bypassed the organization’s signature-based security, which could not detect the encrypted traffic. Antigena immediately blocked the suspicious connectivity, regardless of the encryption, identifying that the activity was a deviation from the ‘pattern of life’ for new devices.

July 15, 16:04 — Possible C2 activity

The Raspberry Pi soon began making repeated HTTP connections to a new external endpoint and downloaded octet streams — arbitrary binary data. It seems the activity was initiated by a standalone software process as opposed to a web browser.

Darktrace revealed that the device was performing an unusual external data transfer to the same endpoint, uploading 7.5 MB which likely contained call home data about the new location and name of the device.

July 15, 16:41 — Internal reconnaissance

The device engaged in TCP scanning across three unique internal IP addresses over a wide range of ports. Although the network scan only targeted three internal servers, the activity was identified by Darktrace as a suspicious increase in internal connections and failed internal connections.

Antigena instantly stopped the Raspberry Pi from making internal connections over the ports involved in the scanning activity, as well as enforcing the device’s ‘pattern of life’.

Figure 2: Device event log showing the components which enable Darktrace to detect network scanning.

July 15, 18:14 — Multiple internal reconnaissance tactics

The Raspberry Pi then scanned a large number of devices on SMB port 445 and engaged in suspicious use of the outdated SMB version 1 protocol, suggesting more in-depth reconnaissance to find exploitable vulnerabilities.

Reacting to the scanning activity alongside the insecure protocol SMBv1, Antigena blocked connections from the source device to the destination IPs for one hour.

Four minutes later, the device engaged in connections to the open-source vulnerability scanner, Nmap. Nmap can be used legitimately for vulnerability scanning and so often is not alerted to by traditional security tools. However, Darktrace’s AI detected that the use of the tool was highly anomalous, and so blocked all outgoing traffic for ten minutes.

July 15, 22:03 — Final reconnaissance

Three hours later, the Raspberry Pi initiated another network scan across six unique external IPs – this was in preparation for the final data exfiltration. Antigena responded with instant, specific blocks to the external IPs which the device was attempting to connect to – before any data could be exfiltrated.

After 30 minutes, Darktrace detected bruteforcing activity from the Raspberry Pi using the SMB and NTLM authentication protocols. The device made a large number of failed login attempts to a single internal device using over 100 unique user accounts. Antigena blocked the activity, successfully stopping another wave of attempted SMB lateral movement.

By this stage, Antigena had bought the security team enough time to respond. The team applied an Antigena quarantine rule (the most severe action Antigena can take) to the Raspberry Pi, until they were able to find the physical location of the device and unplug it from the network.

How AI Analyst stitched together the incident

Cyber AI Analyst autonomously reported on three key moments of the attack:

  • Unusual External Data Transfer
  • Possible HTTP Command and Control
  • TCP Scanning of Multiple Devices (the attempted data exfiltration)

It tied together activities over the span of multiple days, which could have been easily missed by human analysis. The AI provided crucial pieces of information, including the extent of the scanning activity. Such insights are time-consuming to calculate manually.

Figure 3: A screenshot from Cyber AI Analyst summarizing potential C2 activity.

Autonomous Response

Antigena took targeted action throughout to neutralize the suspicious behavior, while allowing normal business operations to continue unhindered.

Rather than widespread blocking, Antigena implemented a range of nuanced responses depending on the situation, always taking the smallest action necessary to deal with the threat.

Figure 4: Darktrace’s UI reveals the attempted network reconnaissance, and Antigena actions a targeted response. All IP addresses have been randomized.

Raspberry Pi: IoT threats

In an event involving 206 countries and 11,000 athletes, facing attacks from hacktivists, criminal groups, and nation states, with many broadcasters working remotely and millions watching from home, organizations involved in the Olympics needed a security solution which could rise to the occasion.

Even with the largest affairs, threats can come from the smallest places. The ability to detect unauthorized IoT devices and maintain visibility over all activity in your digital estate is essential.

Autonomous Response protects against the unexpected, stopping malicious activity at machine speed without any user input. This is necessary for rapid response and remediation, especially for resource-stretched internal security teams. When it comes to defending systems and outpacing attackers, AI always wins the race.

Thanks to Darktrace analysts Emma Foulger and Greg Chapman for their insights on the above threat find.

Learn how two rogue Raspberry Pi devices infected a healthcare provider

Darktrace model detections:

  • Compromise / Ransomware / Suspicious SMB Activity
  • Tags / New Raspberry Pi Device
  • Device / Network Scan
  • Unusual Activity / Unusual Raspberry Pi Activity
  • Antigena / Network / Insider Threat / Antigena Network Scan Block
  • Device / Suspicious Network Scan Activity
  • Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block
  • Antigena / Network / Significant Anomaly / Antigena Controlled and Model Breach
  • Device / Suspicious SMB Scanning Activity
  • Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block
  • Device / Attack and Recon Tools
  • Device / New Device with Attack Tools
  • Device / Anomalous Nmap Activity
  • Device / External Network Scan
  • Device / SMB Session Bruteforce
  • Antigena / Network / Manual / Block All Outgoing Connections
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
Oakley Cox
Director of Product

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October 24, 2025

Patch Smarter, Not Harder: Now Empowering Security Teams with Business-Aligned Threat Context Agents

Patch Smarter, Not Harder: Now Empowering Security Teams with Business-Aligned Threat Context Agents Default blog imageDefault blog image

Most risk management programs remain anchored in enumeration: scanning every asset, cataloging every CVE, and drowning in lists that rarely translate into action. Despite expensive scanners, annual pen tests, and countless spreadsheets, prioritization still falters at two critical points.

Context gaps at the device level: It’s hard to know which vulnerabilities actually matter to your business given existing privileges, what software it runs, and what controls already reduce risk.

Business translation: Even when the technical priority is clear, justifying effort and spend in financial terms—especially across many affected devices—can delay action. Especially if it means halting other areas of the business that directly generate revenue.

The result is familiar: alert fatigue, “too many highs,” and remediation that trails behind the threat landscape. Darktrace / Proactive Exposure Management addresses this by pairing precise, endpoint‑level context with clear, financial insight so teams can prioritize confidently and mobilize faster.

A powerful combination: No-Telemetry Endpoint Agent + Cost-Benefit Analysis

Darktrace / Proactive Exposure Management now uniquely combines technical precision with business clarity in a single workflow.  With this release, Darktrace / Proactive Exposure Management delivers a more holistic approach, uniting technical context and financial insight to drive proactive risk reduction. The result is a single solution that helps security teams stay ahead of threats while reducing noise, delays, and complexity.

  • No-Telemetry Endpoint: Collects installed software data and maps it to known CVEs—without network traffic—providing device-level vulnerability context and operational relevance.
  • Cost-Benefit Analysis for Patching: Calculates ROI by comparing patching effort with potential exploit impact, factoring in headcount time, device count, patch difficulty, and automation availability.

Introducing the No-Telemetry Endpoint Agent

Darktrace’s new endpoint agent inventories installed software on devices and maps it to known CVEs without collecting network data so you can prioritize using real device context and available security controls.

By grounding vulnerability findings in the reality of each endpoint, including its software footprint and existing controls, teams can cut through generic severity scores and focus on what matters most. The agent is ideal for remote devices, BYOD-adjacent fleets, or environments standardizing on Darktrace, and is available without additional licensing cost.

Darktrace / Proactive Exposure Management user interface
Figure 1: Darktrace / Proactive Exposure Management user interface

Built-In Cost-Benefit Analysis for Patching

Security teams often know what needs fixing but stakeholders need to understand why now. Darktrace’s new cost-benefit calculator compares the total cost to patch against the potential cost of exploit, producing an ROI for the patch action that expresses security action in clear financial terms.

Inputs like engineer time, number of affected devices, patch difficulty, and automation availability are factored in automatically. The result is a business-aligned justification for every patching decision—helping teams secure buy-in, accelerate approvals, and move work forward with one-click ticketing, CSV export, or risk acceptance.

Darktrace / Proactive Exposure Management Cost Benefit Analysis
Figure 2: Darktrace / Proactive Exposure Management Cost Benefit Analysis

A Smarter, Faster Approach to Exposure Management

Together, the no-telemetry endpoint and Cost–Benefit Analysis advance the CTEM motion from theory to practice. You gain higher‑fidelity discovery and validation signals at the device level, paired with business‑ready justification that accelerates mobilization. The result is fewer distractions, clearer priorities, and faster measurable risk reduction. This is not from chasing every alert, but by focusing on what moves the needle now.

  • Smarter Prioritization: Device‑level context trims noise and spotlights the exposures that matter for your business.
  • Faster Decisions: Built‑in ROI turns technical urgency into executive clarity—speeding approvals and action.
  • Practical Execution: Privacy‑conscious endpoint collection and ticketing/export options fit neatly into existing workflows.
  • Better Outcomes: Close the loop faster—discover, prioritize, validate, and mobilize—on the same operating surface.

Committed to innovation

These updates are part of the broader Darktrace release, which also included:

1. Major innovations in cloud security with the launch of the industry’s first fully automated cloud forensics solution, reinforcing Darktrace’s leadership in AI-native security.

2. Darktrace Network Endpoint eXtended Telemetry (NEXT) is revolutionizing NDR with the industry’s first mixed-telemetry agent using Self-Learning AI.

3. Improvements to our OT product, purpose built for industrial infrastructure, Darktrace / OT now brings dedicated OT dashboard, segmentation-aware risk modeling, and expanded visibility into edge assets and automation protocols.

Join our Live Launch Event

When? 

December 9, 2025

What will be covered?

Join our live broadcast to experience how Darktrace is eliminating blind spots for detection and response across your complete enterprise with new innovations in Agentic AI across our ActiveAI Security platform. Industry leaders from IDC will join Darktrace customers to discuss challenges in cross-domain security, with a live walkthrough reshaping the future of Network Detection & Response, Endpoint Detection & Response, Email Security, and SecOps in novel threat detection and autonomous investigations.

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October 24, 2025

Darktrace Announces Extended Visibility Between Confirmed Assets and Leaked Credentials from the Deep and Dark Web

Darktrace Announces Extended Visibility Between Confirmed Assets and Leaked Credentials from the Deep and Dark Web Default blog imageDefault blog image

Why exposure management needs to evolve beyond scans and checklists

The modern attack surface changes faster than most security programs can keep up. New assets appear, environments change, and adversaries are increasingly aided by automation and AI. Traditional approaches like periodic scans, static inventories, or annual pen tests are no longer enough. Without a formal exposure program, many businesses are flying blind, unaware of where the next threat may emerge.

This is where Continuous Threat Exposure Management (CTEM) becomes essential. Introduced by Gartner, CTEM helps organizations continuously assess, validate, and improve their exposure to real-world threats. It reframes the problem: scope your true attack surface, prioritize based on business impact and exploitability, and validate what attackers can actually do today, not once a year.

With two powerful new capabilities, Darktrace / Attack Surface Management helps organizations evolve their CTEM programs to meet the demands of today’s threat landscape. These updates make CTEM a reality, not just a strategy.

Too much data, not enough direction

Modern Attack Surface Management tools excel at discovering assets such as cloud workloads, exposed APIs, and forgotten domains. But they often fall short when it comes to prioritization. They rely on static severity scores or generic CVSS ratings, which do not reflect real-world risk or business impact.

This leaves security teams with:

  • Alert fatigue from hundreds of “critical” findings
  • Patch paralysis due to unclear prioritization
  • Blind spots around attacker intent and external targeting

CISOs need more than visibility. They need confidence in what to fix first and context to justify those decisions to stakeholders.

Evolving Attack Surface Management

Attack Surface Management (ASM) must evolve from static lists and generic severity scores to actionable intelligence that helps teams make the right decision now.

Joining the recent addition of Exploit Prediction Assessment, which debuted in late June 2025, today we’re introducing two capabilities that push ASM into that next era:

  • Exploit Prediction Assessment: Continuously validates whether top-priority exposures are actually exploitable in your environment without waiting for patch cycles or formal pen tests.  
  • Deep & Dark Web Monitoring: Extends visibility across millions of sources in the deep and dark web to detect leaked credentials linked to your confirmed domains.
  • Confidence Score: our newly developed AI classification platform will compare newly discovered assets to assets that are known to belong to your organization. The more these newly discovered assets look similar to assets that belong to your organization, the higher the score will be.

Together, these features compress the window from discovery to decision, so your team can act with precision, not panic. The result is a single solution that helps teams stay ahead of attackers without introducing new complexities.

Exploit Prediction Assessment

Traditional penetration tests are invaluable, but they’re often a snapshot of that point-in-time, are potentially disruptive, and compliance frameworks still expect them. Not to mention, when vulnerabilities are present, teams can act immediately rather than relying solely on information from CVSS scores or waiting for patch cycles.  

Unlike full pen tests which can be obtrusive and are usually done only a couple times per year, Exploit Prediction Assessment is surgical, continuous, and focused only on top issues Instead of waiting for vendor patches or the next pen‑test window. It helps confirm whether a top‑priority exposure is actually exploitable in your environment right now.  

For more information on this visit our blog: Beyond Discovery: Adding Intelligent Vulnerability Validation to Darktrace / Attack Surface Management

Deep and Dark Web Monitoring: Extending the scope

Customers have been asking for this for years, and it is finally here. Defense against the dark web. Darktrace / Attack Surface Management’s reach now spans millions of sources across the deep and dark web including forums, marketplaces, breach repositories, paste sites, and other hard‑to‑reach communities to detect leaked credentials linked to your confirmed domains.  

Monitoring is continuous, so you’re alerted as soon as evidence of compromise appears. The surface web is only a fraction of the internet, and a sizable share of risk hides beyond it. Estimates suggest the surface web represents roughly ~10% of all online content, with the rest gated or unindexed—and the TOR-accessible dark web hosts a high proportion of illicit material (a King’s College London study found ~57% of surveyed onion sites contained illicit content), underscoring why credential leakage and brand abuse often appear in places traditional monitoring doesn’t reach. Making these spaces high‑value for early warning signals when credentials or brand assets appear. Most notably, this includes your company’s reputation, assets like servers and systems, and top executives and employees at risk.

What changes for your team

Before:

  • Hundreds of findings, unclear what to start with
  • Reactive investigations triggered by incidents

After:

  • A prioritized backlog based on confidence score or exploit prediction assessment verification
  • Proactive verification of exposure with real-world risk without manual efforts

Confidence Score: Prioritize based on the use-case you care most about

What is it?

Confidence Score is a metric that expresses similarity of newly discover assets compared to the confirmed asset inventory. Several self-learning algorithms compare features of assets to be able to calculate a score.

Why it matters

Traditional Attack Surface Management tools treat all new discovery equally, making it unclear to your team how to identify the most important newly discovered assets, potentially causing you to miss a spoofing domain or shadow IT that could impact your business.

How it helps your team

We’re dividing newly discovered assets into separate insight buckets that each cover a slightly different business case.

  • Low scoring assets: to cover phishing & spoofing domains (like domain variants) that are just being registered and don't have content yet.
  • Medium scoring assets: have more similarities to your digital estate, but have better matching to HTML, brand names, keywords. Can still be phishing but probably with content.
  • High scoring assets: These look most like the rest of your confirmed digital estate, either it's phishing that needs the highest attention, or the asset belongs to your attack surface and requires asset state confirmation to enable the platform to monitor it for risks.

Smarter Exposure Management for CTEM Programs

Recent updates to Darktrace / Attack Surface Management directly advance the core phases of Continuous Threat Exposure Management (CTEM): scope, discover, prioritize, validate, and mobilize. The new Exploit Prediction Assessment helps teams validate and prioritize vulnerabilities based on real-world exploitability, while Deep & Dark Web Monitoring extends discovery into hard-to-reach areas where stolen data and credentials often surface. Together, these capabilities reduce noise, accelerate remediation, and help organizations maintain continuous visibility over their expanding attack surface.

Building on these innovations, Darktrace / Attack Surface Management empowers security teams to focus on what truly matters. By validating exploitability, it cuts through the noise of endless vulnerability lists—helping defenders concentrate on exposures that represent genuine business risk. Continuous monitoring for leaked credentials across the deep and dark web further extends visibility beyond traditional asset discovery, closing critical blind spots where attackers often operate. Crucially, these capabilities complement, not replace, existing security controls such as annual penetration tests, providing continuous, low-friction validation between formal assessments. The result is a more adaptive, resilient security posture that keeps pace with an ever-evolving threat landscape.

If you’re building or maturing a CTEM program—and want fewer open exposures, faster remediation, and better outcomes, Darktrace / Attack Surface Management’s new Exploit Prediction Assessment and Deep & Dark Web Monitoring are ready to help.

  • Want a more in-depth look at how Exploit Prediction Assessment functions? Read more here

Committed to innovation

These updates are part of the broader Darktrace release, which also included:

1. Major innovations in cloud security with the launch of the industry’s first fully automated cloud forensics solution, reinforcing Darktrace’s leadership in AI-native security.

2. Darktrace Network Endpoint eXtended Telemetry (NEXT) is revolutionizing NDR with the industry’s first mixed-telemetry agent using Self-Learning AI.

3. Improvements to our OT product, purpose built for industrial infrastructure, Darktrace / OT now brings dedicated OT dashboard, segmentation-aware risk modeling, and expanded visibility into edge assets and automation protocols.

Join our Live Launch Event

When? 

December 9, 2025

What will be covered?

Join our live broadcast to experience how Darktrace is eliminating blind spots for detection and response across your complete enterprise with new innovations in Agentic AI across our ActiveAI Security platform. Industry leaders from IDC will join Darktrace customers to discuss challenges in cross-domain security, with a live walkthrough reshaping the future of Network Detection & Response, Endpoint Detection & Response, Email Security, and SecOps in novel threat detection and autonomous investigations.

Continue reading
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