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Observing Attacks Against Hundreds of Exposed Services in Public Clouds ![Clock Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-clock.svg) 7 min read Related Products [![Prisma Cloud icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/prisma_RGB_logo_Icon_Color.png)Prisma Cloud](https://unit42.paloaltonetworks.com/product-category/prisma-cloud/ "Prisma Cloud") * ![Profile Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-profile-grey.svg) By: * ![Published Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-calendar-grey.svg) Published:November 22, 2021 * ![Tags Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-category.svg) Categories: * [Cloud Cybersecurity Research](https://unit42.paloaltonetworks.com/category/cloud-cybersecurity-research/) * [Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) * ![Tags Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-tags-grey.svg) Tags: * [Honeypot](https://unit42.paloaltonetworks.com/tag/honeypot/) * [Misconfigurations](https://unit42.paloaltonetworks.com/tag/misconfigurations/) * [Public cloud](https://unit42.paloaltonetworks.com/tag/public-cloud/) * [![Download Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-download.svg)](https://unit42.paloaltonetworks.com/exposed-services-public-clouds/?pdf=download&lg=en&_wpnonce=edee969a51 "Click here to download") * [![Print Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-print.svg)](https://unit42.paloaltonetworks.com/exposed-services-public-clouds/?pdf=print&lg=en&_wpnonce=edee969a51 "Click here to print") Share![Down arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/down-arrow.svg) * ![Link Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-share-link.svg) * [![Link Email](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-sms.svg)](mailto:?subject=Observing%20Attacks%20Against%20Hundreds%20of%20Exposed%20Services%20in%20Public%20Clouds&body=Check%20out%20this%20article%20https%3A%2F%2Funit42.paloaltonetworks.com%2Fexposed-services-public-clouds%2F "Share in email") * [![Facebook Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-fb-share.svg)](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Funit42.paloaltonetworks.com%2Fexposed-services-public-clouds%2F "Share in Facebook") * [![LinkedIn Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-linkedin-share.svg)](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Funit42.paloaltonetworks.com%2Fexposed-services-public-clouds%2F&title=Observing%20Attacks%20Against%20Hundreds%20of%20Exposed%20Services%20in%20Public%20Clouds "Share in LinkedIn") * [![Twitter Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-twitter-share.svg)](https://twitter.com/intent/tweet?url=https%3A%2F%2Funit42.paloaltonetworks.com%2Fexposed-services-public-clouds%2F&text=Observing%20Attacks%20Against%20Hundreds%20of%20Exposed%20Services%20in%20Public%20Clouds "Share in Twitter") * [![Reddit Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-reddit-share.svg)](https://www.paloaltonetworks.com//www.reddit.com/submit?url=https%3A%2F%2Funit42.paloaltonetworks.com%2Fexposed-services-public-clouds%2F&ts=markdown "Share in Reddit") * [![Mastodon Icon](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-mastodon-share.svg)](https://mastodon.social/share?text=Observing%20Attacks%20Against%20Hundreds%20of%20Exposed%20Services%20in%20Public%20Clouds%20https%3A%2F%2Funit42.paloaltonetworks.com%2Fexposed-services-public-clouds%2F "Share in Mastodon") ## Executive Summary An insecurely exposed service is one of the most commonly seen [misconfigurations](https://www.paloaltonetworks.com/prisma/unit42-cloud-threat-research) in cloud environments. These services are discoverable on the internet and can pose a significant risk to cloud workloads in the same infrastructure. Notorious ransomware groups such as [REvil](https://unit42.paloaltonetworks.com/revil-threat-actors/) and [Mespinoza](https://unit42.paloaltonetworks.com/gasket-and-magicsocks-tools-install-mespinoza-ransomware/) are known to exploit exposed services to gain initial access to victims' environments. Using a honeypot infrastructure of 320 nodes deployed globally, researchers aim to better understand the attacks against exposed services in public clouds. Unit 42 researchers deployed multiple instances of remote desktop protocol (RDP), secure shell protocol (SSH), server message block (SMB) and Postgres database in the honeypot infrastructure. \*\*Researchers found that 80% of the 320 honeypots were compromised within 24 hours and all of the honeypots were compromised within a week.\*\*Some findings that stand out are: * SSH was the most attacked application. The number of attackers and compromising events was much higher than for the other three applications. * The most attacked SSH honeypot was compromised 169 times in a single day. * On average, each SSH honeypot was compromised 26 times daily. * One threat actor compromised 96% of our 80 Postgres honeypots globally within 30 seconds. * 85% of the attacker IPs were observed only on a single day. This number indicates that Layer 3 IP-based firewalls are ineffective as attackers rarely reuse the same IPs to launch attacks. A list of malicious IPs created today will likely become outdated tomorrow. The speed of vulnerability management is usually [measured in days or months](https://www.cisa.gov/publication/remediate-vulnerabilities-internet-accessible-systems). The fact that attackers could find and compromise our honeypots in minutes was shocking. This research demonstrates the risk of insecurely exposed services. The outcome reiterates the importance of mitigating and patching security issues quickly. When a misconfigured or vulnerable service is exposed to the internet, it takes attackers just a few minutes to discover and compromise the service. There is no margin of error when it comes to the timing of security fixes. [Prisma Cloud](https://docs.paloaltonetworks.com/prisma/prisma-cloud/prisma-cloud-admin-compute/vulnerability_management.html)can identify and prevent vulnerabilities and misconfigurations across the entire application lifecycle while prioritizing risk for your cloud native environments. [VM-Series](https://live.paloaltonetworks.com/t5/vm-series-in-the-public-cloud/bd-p/AWS_Azure_Discussions) firewalls can help detect and defend against malicious activities in virtualized environments. ## Methodology Between July 2021 and August 2021, Unit 42 researchers deployed 320 honeypots across North America (NA), Asia Pacific (APAC) and Europe (EU). The research analyzed the time, frequency and origins of the attacks observed in our honeypot infrastructure. Four types of applications, SSH, Samba, Postgres and RDP, were evenly deployed across the honeypot infrastructure. We intentionally configured a few accounts with weak credentials such as admin:admin, guest:guest, administrator:password. These accounts grant limited access to the application in a sandboxed environment. A honeypot will be reset and redeployed when a compromising event is detected, i.e., when a threat actor successfully authenticates via one of the credentials and gains access to the application. To analyze the effectiveness of blocking network scanning traffic, we blocked a list of [known scanner IPs](https://unit42.paloaltonetworks.com/cloud-network-scanning-traffic/) on a subset of honeypots. The firewall policies were updated once a day based on the observed network scanning traffic. Depending on the applications and days, each firewall policy might block 600-3,000 known scanner IP addresses. The logs from all the honeypots were aggregated on an Elasticsearch cluster. A controller server continuously monitored the logs and checked the health of each honeypot. If a compromising event was detected or a virtual machine became unresponsive, the controller redeployed the virtual machine and application. Figure 1 illustrates the architecture of the honeypot infrastructure. ![The diagram illustrates the honeypot infrastructure we used to measure attacks against insecurely exposed services in North America, Europe and Asia Pacific. It shows how the logs from all the honeypots were aggregated on an Elasticsearch cluster and how a controller server continuously monitored the logs and checked the health of each honeypot.](https://unit42.paloaltonetworks.com/wp-content/uploads/2021/11/word-image-11.png) Figure 1. Honeypot infrastructure. ## Attack Patterns Figures 2-5 analyze the timing, frequency and origins of the attacks. We define *time-to-first-compromise* as the time that an application stays intact until being compromised the first time. Figure 2 shows the mean *time-to-first-compromise* of all 320 honeypots. *Time-to-first-compromise* is the time that attackers take to discover and compromise a new service on the internet. It also resembles the time IT administrators have to respond to a security alert on exposed services before being attacked. *Time-to-first-compromise* varies with applications. In general, it is inversely proportional to the number of attackers targeting the application (Figure 4). When the number of attackers increases, the time-to-first compromise of this application decreases. ![Mean time to first compromise for the honeypots, measured in minutes. sshd: 184; postres: 511; rdp: 667; samba: 2485](https://unit42.paloaltonetworks.com/wp-content/uploads/2021/11/chart-1.png) Figure 2. The time between the honeypot deployment and its first compromising event. The *mean time-between-compromise* is the average time between two consecutive compromising events of a targeted application. Figure 3 shows the *mean time-between-compromise* of each honeypot application during the 30 days. A vulnerable service on the internet is usually compromised multiple times by multiple different attackers. To compete for the victim's resources, attackers commonly attempt to remove malware or backdoors left by other cybercriminal groups (e.g., [Rocke](https://unit42.paloaltonetworks.com/pro-ocean-rocke-groups-new-cryptojacking-malware/), [TeamTNT](https://unit42.paloaltonetworks.com/black-t-cryptojacking-variant/)). *Mean time-between-compromise* resembles an attacker's time on a compromised system before the next attacker shows up. Similar to *time-to-first-compromise* , *the mean time-between-compromise* of an application is also inversely proportional to the number of attackers targeting the application. ![The mean time-between-compromise is the average time between two consecutive compromising events of a targeted application. Figure 3 shows the mean time-between-compromise of each honeypot application during the 30 days of our study of exposed services.](https://unit42.paloaltonetworks.com/wp-content/uploads/2021/11/chart-2.png) Figure 3. The average time between two consecutive compromising events of an application. Figure 4 shows the average number of unique attacker IP addresses observed on each honeypot during the 30 days. The number also indicates the number of times that each honeypot was compromised. Note that this is *not* the number of attacker IPs observed globally. As most attacker IPs reach only a small subset of our honeypots, the number of globally observed attacker IPs is much higher. In our experiment, only 18% of the attacker IPs reached more than one honeypot. ![Figure 4 shows the average number of unique attacker IP addresses observed on each honeypot during the 30 days. The number also indicates the number of times that each honeypot was compromised. Note that this is not the number of attacker IPs observed globally.](https://unit42.paloaltonetworks.com/wp-content/uploads/2021/11/chart-3.png) Figure 4. The average number of unique attacker IPs observed on a honeypot in 30 days. Figure 5 shows the percentage of attacker IP addresses repeatedly observed on different days. **During the 30 days covered in this research, 85% of the attacker IPs were observed only on a single day.** **The number indicates that the Layer 3 IP-based firewall is ineffective as attackers rarely reuse the same IPs to launch attacks. A list of malicious IPs created today will likely become outdated tomorrow.** ![Figure 5 shows the percentage of attacker IP addresses repeatedly observed on different days. During the 30 days covered in this research, 85% of the attacker IPs were observed only on a single day. The number indicates that the Layer 3 IP-based firewall is ineffective as attackers rarely reuse the same IPs to launch attacks. A list of malicious IPs created today will likely become outdated tomorrow.](https://unit42.paloaltonetworks.com/wp-content/uploads/2021/11/chart-4.png) Figure 5. The percentage of attacker IPs that were observed in one or multiple days. ## Firewall Effectiveness The [network scanning activity project](https://unit42.paloaltonetworks.com/cloud-network-scanning-traffic/) identified over 700,000 scanner IPs daily. We were curious whether proactively blocking the network scanning traffic could prevent attackers from discovering the honeypots and reduce the number of attacks. To test the hypothesis, we created an experimental group of 48 honeypots and applied firewall policies to block IPs from known network scanners. The firewall policy blocks the IPs that have been scanning a specific application daily in the past 30 days. Figure 6 compares the number of attacks observed on each honeypot between the control group (no firewall) and the experimental group (with firewall). **We could not see a significant difference between the two groups, meaning blocking known scanner IPs is ineffective in mitigating attacks.** ![Figure 6 compares the number of attacks observed on each honeypot between the control group (no firewall) and the experimental group (with firewall). We could not see a significant difference between the two groups, meaning blocking known scanner IPs is ineffective in mitigating attacks.](https://unit42.paloaltonetworks.com/wp-content/uploads/2021/11/chart-5.png) Figure 6. The average number of unique attacker IPs observed on each honeypot with or without a firewall. ## Regional Effects We are also curious if services deployed in different geolocations are attacked differently. Figure 7 compares the number of attacks observed on each honeypot in different regions. There is no significant difference for the Samba, Postgres and RDP honeypots deployed in different regions. However, we see a very different attack intensity on SSH honeypots in different regions. The number of SSH attacks against APAC-based honeypots is 50% higher than those in NA and 263% higher than those in EU. These numbers are also interestingly correlated to the origins of the attacks, as shown in Figure 8. 50% of the attacker IP addresses originate from APAC, 20% from NA and less than 10% from EU. **The result indicates that SSH services deployed in the APAC region are more likely to be attacked than those in other regions.** ![Figure 7 compares the number of attacks on insecurely exposed services observed on each honeypot in different regions. There is no significant difference for the Samba, Postgres and RDP honeypots deployed in different regions. However, we see a very different attack intensity on SSH honeypots in different regions. The number of SSH attacks against APAC-based honeypots is 50% higher than those in NA and 263% higher than those in EU.](https://unit42.paloaltonetworks.com/wp-content/uploads/2021/11/chart-6.png) Figure 7. The average number of unique attacker IP addresses observed on a honeypot in different regions. ![50% of the attacker IP addresses we observed originate from APAC, 20% from NA and less than 10% from EU. The result indicates that SSH services deployed in the APAC region are more likely to be attacked than those in other regions.](https://unit42.paloaltonetworks.com/wp-content/uploads/2021/11/chart-7.png) Figure 8. The top 10 countries where the attacker IP addresses originated. ## Conclusion The problem of insecurely exposed services is not new to public cloud, but the agility of cloud infrastructure management makes the creation and replication of such misconfigurations faster. The research highlights the risk and severity of such misconfigurations. When a vulnerable service is exposed to the internet, opportunistic attackers can find and attack it in just a few minutes. As most of these internet-facing services are connected to some other cloud workloads, any breached service can potentially lead to the compromise of the entire cloud environment. This type of misconfiguration, however, is not difficult to prevent and remediate with cloud-native approaches. Some strategies that system administrators can take are: * Create a guardrail to prevent privileged ports from being open. For example, use [AWS Service Control Policies](https://docs.aws.amazon.com/organizations/latest/userguide/orgs_manage_policies_scps_examples.html) or [Azure Firewall Management](https://azure.microsoft.com/en-us/services/firewall-manager/#overview). * Create audit rules to monitor all the open ports and exposed services. For example, use [AWS Config](https://aws.amazon.com/blogs/mt/using-aws-config-security-analysis-resource-administration/), [Checkov](https://github.com/bridgecrewio/checkov), or [Cloud Security Posture Management](https://docs.paloaltonetworks.com/prisma/prisma-cloud/prisma-cloud-admin/prisma-cloud-policies.html)tools * Create automated response and remediation rules to fix misconfigurations automatically. For example, consider [AWS Security Hub](https://aws.amazon.com/solutions/implementations/aws-security-hub-automated-response-and-remediation/) or [Prisma Cloud Automated Remediation](https://docs.paloaltonetworks.com/prisma/prisma-cloud/prisma-cloud-admin/manage-prisma-cloud-alerts/configure-prisma-cloud-to-automatically-remediate-alerts.html). * Deploy next-generation firewalls in front of the applications, such as [VM-Series](https://live.paloaltonetworks.com/t5/vm-series-in-the-public-cloud/bd-p/AWS_Azure_Discussions) or [WAF](https://www.paloaltonetworks.com/prisma/cloud/web-application-API-security) to block malicious traffic. Back to top ### Tags * [Honeypot](https://unit42.paloaltonetworks.com/tag/honeypot/ "honeypot") * [Misconfigurations](https://unit42.paloaltonetworks.com/tag/misconfigurations/ "misconfigurations") * [Public cloud](https://unit42.paloaltonetworks.com/tag/public-cloud/ "public cloud") [Threat Research Center](https://unit42.paloaltonetworks.com "Threat Research") [Next: A Peek into Top-Level Domains and Cybercrime](https://unit42.paloaltonetworks.com/top-level-domains-cybercrime/ "A Peek into Top-Level Domains and Cybercrime") ### Table of Contents * ### Related Articles * [IAM-Deescalate: An Open Source Tool to Help Users Reduce the Risk of Privilege Escalation](https://unit42.paloaltonetworks.com/iam-deescalate/ "article - table of contents") * [Network Scanning Traffic Observed in Public Clouds](https://unit42.paloaltonetworks.com/cloud-network-scanning-traffic/ "article - table of contents") * [Highlights From the Unit 42 Cloud Threat Report, 2H 2021](https://unit42.paloaltonetworks.com/cloud-threat-report-2h-2021/ "article - table of contents") ## Related Cloud Cybersecurity Research Resources ![Pictorial representation of bucket hijacking technique for cloud data exfiltration. 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Lessons From Building an Autonomous Cloud Offensive Multi-Agent System](https://unit42.paloaltonetworks.com/autonomous-ai-cloud-attacks/) * [AI](https://unit42.paloaltonetworks.com/tag/ai/ "AI") * [Cloud](https://unit42.paloaltonetworks.com/tag/cloud/ "Cloud") * [Data exfiltration](https://unit42.paloaltonetworks.com/tag/data-exfiltration/ "data exfiltration") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/autonomous-ai-cloud-attacks/ "Can AI Attack the Cloud? Lessons From Building an Autonomous Cloud Offensive Multi-Agent System") ![Pictorial representation of passwordless authentication. Futuristic cityscape with skyscrapers surrounded by glowing, neon-lit pathways and digital clouds. The sky is vibrant with pink and orange hues, giving a surreal, cyberpunk aesthetic.](https://unit42.paloaltonetworks.com/wp-content/uploads/2026/03/02_Cloud_cybersecurity_research_Overview_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) March 23, 2026 [#### Google Cloud Authenticator: The Hidden Mechanisms of Passwordless Authentication](https://unit42.paloaltonetworks.com/passwordless-authentication/) * [Google](https://unit42.paloaltonetworks.com/tag/google/ "Google") * [Google authenticator](https://unit42.paloaltonetworks.com/tag/google-authenticator/ "google authenticator") * [Google Chrome](https://unit42.paloaltonetworks.com/tag/google-chrome/ "Google Chrome") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/passwordless-authentication/ "Google Cloud Authenticator: The Hidden Mechanisms of Passwordless Authentication") ![Close-up of a black woman with glasses examining colorful computer code on a screen. The scene is illuminated by various lights, creating a focused and analytical atmosphere.](https://unit42.paloaltonetworks.com/wp-content/uploads/2026/02/13_Cloud_cybersecurity_research_Overview_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) February 6, 2026 [#### Novel Technique to Detect Cloud Threat Actor Operations](https://unit42.paloaltonetworks.com/tracking-threat-groups-through-cloud-logging/) * [API](https://unit42.paloaltonetworks.com/tag/api/ "API") * [IAM](https://unit42.paloaltonetworks.com/tag/iam/ "IAM") * [MITRE](https://unit42.paloaltonetworks.com/tag/mitre/ "MITRE") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/tracking-threat-groups-through-cloud-logging/ "Novel Technique to Detect Cloud Threat Actor Operations") ![Pictorial representation of Azure OpenAI DNS resolution issue. Futuristic cityscape illustration with luminous structures and floating cloud elements, showcasing advanced technology and a dynamic, digitally enhanced environment.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/06/02_DNS_Overview_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) January 20, 2026 [#### DNS OverDoS: Are Private Endpoints Too Private?](https://unit42.paloaltonetworks.com/dos-attacks-and-azure-private-endpoint/) * [Microsoft Azure](https://unit42.paloaltonetworks.com/tag/microsoft-azure/ "Microsoft Azure") * [Networking](https://unit42.paloaltonetworks.com/tag/networking/ "networking") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/dos-attacks-and-azure-private-endpoint/ "DNS OverDoS: Are Private Endpoints Too Private?") ![Pictorial representation of cloud discovery with AzureHound. A digital representation of a cloud composed of blue light particles, superimposed over a blurred background of server racks in a data center.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/10/08_Cloud_cybersecurity_research_Overview_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) October 24, 2025 [#### Cloud Discovery With AzureHound](https://unit42.paloaltonetworks.com/threat-actor-misuse-of-azurehound/) * [Control plane](https://unit42.paloaltonetworks.com/tag/control-plane/ "control plane") * [Curious Serpens](https://unit42.paloaltonetworks.com/tag/curious-serpens/ "Curious Serpens") * [Data plane](https://unit42.paloaltonetworks.com/tag/data-plane/ "data plane") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/threat-actor-misuse-of-azurehound/ "Cloud Discovery With AzureHound") ![Pictorial representation of a gift card fraud campaign. A glowing skull and crossbones on a circuit board.](https://unit42.paloaltonetworks.com/wp-content/uploads/2025/10/07_Cybercrime_Category_1920x900-786x368.jpg) [![category icon](https://unit42.paloaltonetworks.com/wp-content/uploads/2024/06/icon-threat-research.svg)Threat Research](https://unit42.paloaltonetworks.com/category/threat-research/) October 22, 2025 [#### Jingle Thief: Inside a Cloud-Based Gift Card Fraud Campaign](https://unit42.paloaltonetworks.com/cloud-based-gift-card-fraud-campaign/) * [CL‑CRI‑1032](https://unit42.paloaltonetworks.com/tag/cl-cri-1032/ "CL‑CRI‑1032") * [Microsoft](https://unit42.paloaltonetworks.com/tag/microsoft/ "Microsoft") * [Phishing](https://unit42.paloaltonetworks.com/tag/phishing/ "phishing") [Read now ![Right arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/icon-right-arrow-withtail.svg)](https://unit42.paloaltonetworks.com/cloud-based-gift-card-fraud-campaign/ "Jingle Thief: Inside a Cloud-Based Gift Card Fraud Campaign") * ![Slider arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/slider-arrow-left.svg) * ![Slider arrow](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/slider-arrow-left.svg) ![Close button](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/icons/close-modal.svg) ![Enlarged Image]() ![Newsletter](https://unit42.paloaltonetworks.com/wp-content/uploads/2026/03/unit42-footer-subscribe-desktop.png) ![UNIT 42 Small Logo](https://unit42.paloaltonetworks.com/wp-content/themes/unit42-v6/dist/images/palo-alto-logo-small.svg) Get updates from Unit 42 ## Peace of mind comes from staying ahead of threats. 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