Telus Digital, the business process outsourcing (BPO) arm of Canadian telecom giant Telus, is currently investigating a massive data breach claimed by the notorious hacking group ShinyHunters. The threat actors allege they have exfiltrated nearly a petabyte (1,000 TB) of data over several months and are demanding a $65 million ransom. The stolen data reportedly includes sensitive information from Telus Digital's clients—which span banking, technology, and government—as well as customer data and call records from Telus's consumer division. The initial access vector is believed to be a supply chain attack, where attackers leveraged stolen Google Cloud Platform credentials obtained from a prior breach at Salesloft Drift. This incident underscores the cascading risk of supply chain security failures and the immense scale of modern data breaches.
The threat actor, ShinyHunters, is a well-known and financially motivated group famous for large-scale data breaches and selling stolen data on dark web forums. In this case, they targeted Telus Digital, a BPO provider with access to sensitive data from a wide array of prominent companies. The attackers claim to have maintained access to the network for an extended period, possibly since August 2025, allowing for the slow exfiltration of an enormous volume of data. The compromised data is said to affect 28 named companies that are clients of Telus Digital, posing a significant third-party risk to those organizations. The attackers are attempting to extort Telus Digital with a $65 million demand, fitting the pattern of a data theft and extortion campaign rather than a traditional ransomware attack.
Based on reports, the attack chain involved a sophisticated supply chain compromise:
T1195.002 - Compromise Software Supply Chain: Compromise Software Dependency or T1078.004 - Valid Accounts: Cloud Accounts obtained from a third party.T1537 - Transfer Data to Cloud Account and T1048 - Exfiltration Over Alternative Protocol.The use of a cybersecurity tool,
trufflehog, by the hackers is ironic. This open-source tool is designed to find leaked secrets and credentials in code repositories, suggesting the attackers may have used it to find further credentials within Telus Digital's environment to expand their access.
The potential impact of this breach is colossal. For Telus Digital, it represents a catastrophic security failure that could lead to immense financial loss from the ransom demand, incident response costs, regulatory fines, and loss of business. For the 28+ client companies, this is a severe supply chain breach that has exposed their customer data and internal information, leading to their own incident response efforts and reputational damage. For individuals whose data was compromised—including customers of Telus and its clients—the breach poses a high risk of identity theft, fraud, and targeted phishing attacks. The sheer volume of data (1 petabyte) suggests that the stolen information is likely comprehensive and highly sensitive.
To detect similar large-scale data exfiltration from a cloud environment:
storage.objects.get, storage.objects.list).trufflehogtrufflehog by unauthorized users or processes.storage.admin.Network Traffic Analysis (D3-NTA).In a cloud context, this translates to strict IAM policies. Enforcing least privilege on GCP service accounts would have limited the attacker's ability to access data beyond their intended scope.
Implementing strict egress filtering rules in the cloud VPC could have blocked or at least detected the massive data exfiltration.
Comprehensive logging and auditing of cloud API calls and network flows are essential for detecting anomalous activity like large-scale data exfiltration.
Using secret scanning tools like trufflehog proactively (by the defender) can find and remediate leaked credentials before attackers do.
To prevent a petabyte-scale exfiltration like the one claimed against Telus, strict outbound traffic filtering is essential. In the GCP environment, configure firewall rules to deny all egress traffic from storage and compute resources by default. Create explicit 'allow' rules only for necessary business traffic to known-good IP addresses and domains (e.g., patch repositories, trusted partner APIs). For data transfers, use private interconnects or VPNs instead of the public internet. Furthermore, leverage VPC Service Controls to create a service perimeter around sensitive projects and storage buckets, preventing data from being moved outside the trusted boundary, even by a compromised account with valid credentials. This would have made a slow, large-scale exfiltration over the public internet significantly more difficult and easier to detect.
The initial access via stolen third-party credentials highlights the need for rigorous third-party risk management and least-privilege access for all non-human identities. Any service account or credentials shared with a third party like Salesloft Drift must be scoped with the absolute minimum permissions required for its function. The compromised credentials should not have had broad access to Telus Digital's environment. Implement regular audits of third-party permissions and use IAM conditions in GCP to restrict access by time of day, source IP, or resource type. By tightly scoping third-party access, the 'blast radius' of a compromise in the supply chain is dramatically reduced, preventing a single stolen credential from leading to a catastrophic breach.
Detecting a slow-burn exfiltration requires advanced behavioral analysis. Implement tools that can baseline normal data access patterns within your cloud environment. For Telus Digital, this would mean establishing what a normal day/week of data access looks like for their applications and service accounts. A system like the one compromised by ShinyHunters, which began accessing and transferring massive volumes of data over several months, would create a significant deviation from this baseline. Security teams should configure alerts for when an identity (user or service account) accesses an anomalously high number of objects in a storage bucket or transfers an unusually large volume of data. This behavioral approach is critical for catching sophisticated attackers who are attempting to blend in with normal activity.

Cybersecurity professional with over 10 years of specialized experience in security operations, threat intelligence, incident response, and security automation. Expertise spans SOAR/XSOAR orchestration, threat intelligence platforms, SIEM/UEBA analytics, and building cyber fusion centers. Background includes technical enablement, solution architecture for enterprise and government clients, and implementing security automation workflows across IR, TIP, and SOC use cases.
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Observables and indicators of compromise (IOCs) have been extracted and cataloged. Risk has been assessed and correlated with known threat actors and historical campaigns.
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