Queensland Scam & Telecom Incident Report – June 2025

Overview of reported telecommunications incidents across Queensland in June 2025. This report captures community-sourced reporting activity between 1–30 June 2025, analysing scam classification patterns, regional distribution, and emerging safety signals.

Executive Summary

This report analyses community-submitted telecommunications safety data across Queensland between 1–30 June 2025. All classifications, trend observations, and regional patterns are derived from first-hand community intelligence aggregated through the Reverseau platform.

Queensland recorded 710 community reports across 481 unique phone numbers during the reporting period. Compared to May 2025, reporting volume showed a significant increase of 65%, while 481 numbers remained under active community monitoring throughout the month.

Scam remains the most frequently assigned community classification at 30% of categorised reports, with a scam classification ratio of 30% across all submissions. Scam maintained its position as the dominant classification in both periods, suggesting sustained targeting patterns rather than campaign rotation.

Geographically, reporting activity was concentrated in Brisbane, followed by Southport and Samford. Brisbane recorded more than double the reporting volume of the next most active locality (Southport), indicating concentrated campaign activity or higher community engagement within this area.

June marks the end of the Australian financial year, typically the peak month for tax-related scam activity. ATO and superannuation impersonation campaigns are at their most active.

Scam classifications account for 30% of reports, suggesting a mixed telecommunications activity landscape where non-scam reporting categories play a significant role in the overall safety picture. Residents are encouraged to report suspicious telecommunications activity and consult the QLD data dashboard for real-time classification and trend data.

Why This Matters

While scam classifications represent a smaller share of overall reporting at 30%, the diversity of classification categories observed across Queensland underscores the importance of community-driven monitoring. Telecommunications safety extends beyond scam detection — nuisance, telemarketing, and unknown classifications each contribute to a more complete picture of how phone numbers interact with the community. Continued reporting across all categories strengthens the analytical foundation that powers early detection and trend visibility.

Community Reports
710
vs May 2025 +65%
Unique Numbers Reported
481
Scam Classification Ratio
30%
Active Numbers Monitored
481

Scam Category Breakdown

Community classification distribution across QLD for the period 1–30 June 2025. Classifications are assigned by reporting users based on their direct experience with each number.

Scam30%
Suspicious25%
Spam22%
Uncertain15%
Legit7%

Scam accounted for 30% of categorised reports during June 2025. In May 2025, Scam held the top position with 55% of classifications. Scam maintained its position as the dominant classification in both periods, suggesting sustained targeting patterns rather than campaign rotation.

Most Affected Areas in Queensland

Localities with the highest concentration of community reports during 1–30 June 2025. Each locality links to its dedicated intelligence page with full classification breakdowns and number listings.

Brisbane recorded more than double the reporting volume of the next most active locality (Southport), indicating concentrated campaign activity or higher community engagement within this area. For detailed locality-level analysis, visit the individual area pages linked above or explore the QLD data dashboard.

Month-to-Month Comparison

Compared to May 2025, Queensland experienced a significant increase of 65% in community reporting volume. Overall activity has increased, with substantial monitoring coverage across the state.

Seasonal Context

June marks the end of the Australian financial year, typically the peak month for tax-related scam activity. ATO and superannuation impersonation campaigns are at their most active. The observed increase of 65% aligns with typical post-seasonal campaign escalation, where scam operators increase targeting activity in response to changing consumer behaviour patterns.

Classification Movement

Scam classifications accounted for 30% of categorised reports in June, with scam-specific reports representing 30% of all submissions. These shifts in community classification patterns may reflect evolving campaign tactics, changes in the types of numbers being reported, or natural variation in reporting behaviour between periods. Monitoring classification movement over consecutive months provides a more reliable indicator of genuine trend shifts than any single-month comparison.

Regional Variation

Despite the overall increase in reporting volume, Brisbane remained the primary reporting hub. Elevated reporting in Brisbane may reflect both population density effects and localised campaign activity rather than a uniform state-wide increase.

Service Type Distribution

Local Service100%

Local Service numbers account for 100% of reported activity, reflecting the broader national pattern where mobile-originated calls dominate community safety reports. Residents should exercise particular caution with unsolicited calls from unfamiliar local service numbers.

Emerging Trends & Observations

Several numbers exhibited accelerated reporting velocity within compressed time windows, followed by classification convergence toward scam designation.

Rapid Accumulation Signals

10 numbers within QLD accumulated multiple community reports within a compressed time window during 1–30 June 2025. This velocity pattern is consistent with active call campaigns or coordinated targeting activity. Numbers exhibiting rapid report accumulation frequently transition from initial “Unknown” or “Suspicious” classifications to confirmed “Scam” designation within days.

Numbers flagged for rapid accumulation averaged 6 reports each during the period, indicating sustained community engagement with these numbers rather than isolated encounters.

Several flagged numbers exhibited cross-locality reporting dispersion, with community submissions originating from multiple areas within QLD. This pattern suggests broadcast-style outbound activity rather than localised outreach, consistent with automated dialling campaigns that target numbers across geographic boundaries.

Divergent Classification Signals

Several numbers display mixed community classifications — receiving both scam and non-scam reports during June 2025. This divergence may indicate numbers transitioning between legitimate and illegitimate use, caller ID spoofing of legitimate business numbers, or community uncertainty about the nature of calls received. Numbers with divergent classifications warrant continued monitoring as community consensus develops.

Community Safety Guidance

  • Do not return missed calls from unknown 07 numbers without verification.
  • Verify any government agency claims through official websites or published contact numbers — the ATO, Centrelink, and Medicare will never threaten immediate action via phone.
  • Avoid clicking payment or delivery links received via SMS from unrecognised senders.
  • Report suspicious telecommunications activity to help build community safety intelligence for Queensland.
  • Check numbers on Reverseau before returning calls from unknown sources.

Data Methodology

This report is compiled from community-submitted telecommunications safety reports for the period 1–30 June 2025. All data is aggregated and anonymised before publication.

  • Source: First-hand community reports submitted via Reverseau.
  • Scope: Numbers with a registered allocation within Queensland (QLD).
  • Period: 1–30 June 2025 (calendar month).
  • Classifications: Assigned by reporting users based on their direct experience.
  • Limitations: Data reflects community perception, not verified telecommunications records. Reporting volumes are influenced by platform adoption and user engagement patterns.

For detailed methodology, see our methodology page. For the full analytical dataset, visit the QLD data dashboard.