Executive Summary
This report analyses community-submitted telecommunications safety data across Northern Territory between 1–30 September 2025. All classifications, trend observations, and regional patterns are derived from first-hand community intelligence aggregated through the Reverseau platform.
Northern Territory recorded 9 community reports across 6 unique phone numbers during the reporting period. Compared to August 2025, reporting volume showed a notable decrease of 61%, while 6 numbers remained under active community monitoring throughout the month.
Scam remains the most frequently assigned community classification at 67% of categorised reports, with a scam classification ratio of 67% 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 Darwin.
September often marks the beginning of delivery and parcel scam escalation as online shopping activity increases ahead of the holiday retail period.
The sustained dominance of scam classifications at 67% suggests structural targeting behaviour rather than isolated campaign spikes, warranting continued community vigilance. Residents are encouraged to report suspicious telecommunications activity and consult the NT data dashboard for real-time classification and trend data.
Why This Matters
Sustained scam classification dominance at 67% across consecutive reporting periods suggests structural targeting patterns rather than isolated campaign surges. When a single classification category maintains this level of prevalence, it indicates persistent, organised activity that is unlikely to self-correct without sustained community awareness. Continued monitoring across Northern Territory’s metropolitan and regional areas remains critical to early detection of coordinated telecommunications fraud and to building the community intelligence layer that enables faster classification convergence on emerging threats.
Scam Category Breakdown
Community classification distribution across NT for the period 1–30 September 2025. Classifications are assigned by reporting users based on their direct experience with each number.
Scam accounted for 67% of categorised reports during September 2025. In August 2025, Scam held the top position with 30% 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 Northern Territory
Localities with the highest concentration of community reports during 1–30 September 2025. Each locality links to its dedicated intelligence page with full classification breakdowns and number listings.
Month-to-Month Comparison
Compared to August 2025, Northern Territory experienced a notable decrease of 61% in community reporting volume. Overall activity has decreased, with limited but notable monitoring coverage across the state.
Seasonal Context
September often marks the beginning of delivery and parcel scam escalation as online shopping activity increases ahead of the holiday retail period. The observed decrease of 61% may reflect seasonal reporting variation, reduced campaign activity, or shifts in community engagement patterns during this period.
Classification Movement
Scam classifications accounted for 67% of categorised reports in September, with scam-specific reports representing 67% 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.
Service Type Distribution
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
1 number within NT accumulated multiple community reports within a compressed time window during 1–30 September 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.
Flagged numbers averaged 3 reports each, consistent with early-stage campaign detection where community awareness is still building.
Community Safety Guidance
- Do not return missed calls from unknown 08 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 Northern Territory.
- 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 September 2025. All data is aggregated and anonymised before publication.
- Source: First-hand community reports submitted via Reverseau.
- Scope: Numbers with a registered allocation within Northern Territory (NT).
- Period: 1–30 September 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 NT data dashboard.