Scam.SG Community Report Bulletin
Scam report intelligence derived from the Scam.SG community report dataset · January – March 2026
Segment 1 — Overview
SourceScam.SG community scam report data, Q1 2026 & Q4 2025
Segment 2 — Scam-Type Volume & QoQ Trend
Percentages are calculated as a share of the report volume of the top-5 scam types only.
Q1 2026 top-5 reports
70
Jan – Mar 2026
Q4 2025 top-5 reports
52
Oct – Dec 2025
QoQ volume change
+34.6%
Volume of Top-5 Scam Types, Q4→Q1
#1 scam type Q1 2026
Job Scam
28.57% · 20 reports
| # | Scam type | Q1 2026 count | Q1 % of top-5 | Q4 2025 count | Q4 % of top-5 | Trend |
|---|---|---|---|---|---|---|
| 1 | Job Scam | 20 | 28.57% | 12 | 23.08% | +8 reports |
| 2 | Investment Scam | 19 | 27.14% | 6 | 11.54% | +13 reports |
| 3 | Online Shopping Scam | 18 | 25.71% | 19 | 36.54% | -1 report |
| 4 | Supplier Scam | 8 | 11.43% | 8 | 15.38% | Flat |
| 5 | Impersonation Scam | 5 | 7.14% | 7 | 13.46% | -2 reports |
SourceScam.SG community scam report data % calculated on top-5 scam types based on report volume only. Money loss rate by report volume is 100% for both quarters
Segment 3 — Scam-Type by Source Profile
Scam sources describe the channel through which a scammer made contact with or reached the victim — e.g. Internet, WhatsApp, In Person, Facebook.
Q4 2025 — Top 5
| # | Type — Source | Count |
|---|---|---|
| 1 | Online Shopping Scam — Internet | 9 |
| 2 | Supplier Scam — In Person | 5 |
| 2 | Job Scam — WhatsApp | 5 |
| 2 | Impersonation Scam — Phone (voice) | 5 |
| 5 | Online Shopping Scam — Facebook | 4 |
Q1 2026 — Top 5
| # | Type — Source | Count |
|---|---|---|
| 1 | Job Scam — Internet | 15 |
| 2 | Online Shopping Scam — Internet | 12 |
| 3 | Investment Scam — Social / Forums | 5 |
| 4 | Supplier Scam — In Person | 4 |
| 5 | Job Scam — In Person | 3 |
Key shift observed
In Q4 2025, scam delivery was fragmented across Internet, WhatsApp, In Person, Phone (voice), and Facebook. By Q1 2026, Internet became the dominant channel — accounting for the top two type–source pairings (Job via Internet: 15; Online Shopping via Internet: 12). WhatsApp dropped out of the top-5 entirely. This consolidation around Internet-based delivery suggests scammers increasingly relied on broad web exposure (job boards, search ads, fake listings) rather than direct messaging to reach victims.
SourceScam.SG community scam report data
Segment 4 — Scam-Type Deep Dive #1
All observations and inferences below are derived from Scam.SG community report data and Scam.SG scam-type definitions. No external data sources are used in this section.
Why Job Scams rank #1 in Q1 2026
Steepest quarter-on-quarter surge
Job Scam reports jumped from 12 (Q4 2025) to 20 (Q1 2026) — a 66.7% increase. No other top-5 scam type showed a comparable absolute rise in report volume within the Scam.SG dataset.
January hiring cycle vulnerability
Q1 (January–March) aligns with the post-Chinese New Year and new-year hiring period in Singapore — a time when more people are actively job-seeking and companies accelerate recruitment to fill up manpower gaps. Scam.SG's definition of Job Scams covers fake employment opportunities to deceive individuals into providing personal information or paying upfront fees for roles that do not exist; this seasonal context creates a fertile environment for volume uplift.
Internet as the primary delivery channel
15 of 20 Job Scam reports in Q1 2026 were sourced via the Internet — the single largest type–source combination in the entire dataset. This means 75% of Job Scam reports in Q1 came through broad web-based channels (job portals, search listings, advertisements) rather than direct messaging platforms.
In-person contact as a secondary vector
3 Job Scam reports in Q1 2026 came via In-Person contact — making it the fifth-largest type–source pairing overall. This dual-channel pattern (Internet + In Person) is distinctive to Job Scams and was not observed for Investment or Online Shopping Scams in Q1.
Observed scam patterns from Scam.SG community reports
Pattern 1 — Scripted recruiter outreach via WhatsApp
Multiple Scam.SG reports describe receiving near-identical unsolicited WhatsApp messages from individuals claiming to represent Singapore-registered employment agencies — citing real UEN numbers to establish credibility. The scripts follow a consistent structure: an introductory greeting referencing a hiring role, a claim to have sourced the recipient's contact through a company database, and a request to forward details to a "Singapore person in charge." Community reporters flagged that the sending numbers were non-Singapore (+502, +56 area codes) despite the local UEN claims, and that follow-up contact either ceased or escalated to fee requests.
Pattern 2 — Task-based commission trap with escalating deposits
A recurring pattern in Scam.SG reports involves victims being onboarded to a proprietary online platform or website and assigned "promotional tasks" — such as rating products, completing brand surveys, or submitting daily check-ins — with promised daily commissions (S$50–S$500) and monthly salaries (up to S$8,750 cited in one report). An initial payout is made to build trust. Subsequently, victims are told their platform wallet has gone negative, or that a deposit is required to unlock the next task set. Deposits escalate with each round. Reports describe funds being transferred to bank accounts that change between transactions, and contact going silent after a threshold is crossed. One reporter described being guided through the process by a named "trainer" who directed them to a specific login URL.
Pattern 3 — Overseas placement with upfront fee extraction
Several Scam.SG reports originate from victims in India, Sri Lanka, and Bangladesh who were approached — often through a manpower consultant or via a family referral — with offers of Singapore-based employment. Victims received official-looking offer letters on company letterheads and were asked to pay fees labelled as MOM processing charges, insurance premiums, or visa costs (amounts ranging from INR 15,000 to INR 60,000 cited across reports). After payment, contact was severed and numbers blocked. In at least one case, a victim was physically directed to travel to a different Indian state for a supposed handover meeting, at which point the scammer disappeared. The Singapore companies named in these reports were either unverifiable, had no traceable presence, or were impersonated entities.
Pattern 4 — IPA submitted without worker knowledge
A distinct cluster of Scam.SG reports — originating primarily from Bangladeshi nationals — describes In-Principle Approvals (IPAs) for Singapore work passes being submitted by construction and engineering companies without the workers' knowledge or consent. Reporters state they did not authorise any company to apply on their behalf, do not recognise the prospective employer, and in some cases object to the salary offered. This pattern suggests a possible intermediary layer — brokers or agents in the origin country — submitting IPA applications using workers' passport details without proper authorisation, potentially as part of a broader deceptive placement scheme.
Pattern 5 — Platform-hopping to evade detection
Scam.SG reports reflect a consistent tactic of moving victims across platforms during the scam lifecycle: initial contact via WhatsApp or Facebook, handoff to Telegram for operational communication, and task completion via a standalone proprietary website or app. Reporters note that Telegram chat histories disappeared after they reported the matter to police, removing evidence. In one case, a reporter described an entirely AI-generated recruiter persona on Telegram that deflected all requests for a phone call and failed to provide a verifiable company address when pressed. The internet-based nature of these handoffs — rather than sustained single-channel communication — is consistent with the Scam.SG data showing Internet as the dominant job scam source in Q1 2026.
SourceScam.SG community report narratives — patterns observed across reports spanning Q4 2024 to Q1 2026. All patterns are inferred from reporter-submitted narratives on scam.sg and do not constitute verified findings or legal determinations.
What consumers should do
What businesses should do
SourceAll guidance rooted in Scam.SG platform data and scam-type definitions — Scam Types / Job Scams
Segment 5 — Regulatory Context
The following regulatory actions by Singapore authorities provide context for the scam environment reflected in Q4 2025 and Q1 2026 Scam.SG community reports.
Facility Restriction Framework — operationalised 1 October 2025
The Singapore Police Force (SPF), together with the Monetary Authority of Singapore (MAS), the Infocomm Media Development Authority (IMDA), and GovTech Singapore, operationalised the Facility Restriction Framework for scam mules on 1 October 2025. As at 9 February 2026, the framework had resulted in 550 money mules, 801 SIM card mules, and 51 corporate entities being placed under restrictions. Under this framework, scam mules may face restrictions on banking services (including digital banking, ATM services, and card-based transactions), restrictions on subscriptions to new mobile lines, and restrictions on accessing existing Corppass accounts and the use of Singpass to register for high-risk services. Restrictions on Corppass and Singpass are being implemented in a later phase.
SourceSPF 2025 Annual Scams and Cybercrime Brief — SPF Annual Brief (Annual 2025)
Targeted public advisories
In July 2025, SPF collaborated with the Ministry of Finance to disseminate anti-scam advisories warning the public about fake SG60 voucher advertisements on social media and phishing websites. In a separate initiative, SPF partnered with Ticketmaster to alert the public about concert ticket scams linked to BLACKPINK's Deadline World Tour Concert in November 2025. These targeted, event-specific advisories demonstrate a shift toward proactive, context-sensitive scam prevention aligned with specific high-risk consumer moments.
SourceSPF Publications — SPF Police Advisory On Phishing Scams & SPF Police Advisory On Scams Involving The Sale Of Concert Tickets
Relevance to Scam.SG Q1 2026 report data
The Facility Restriction Framework's focus on money mule infrastructure is directly relevant to the continued presence of Job Scams at #1 in Q1 2026. Scam.SG's Job Scam type definition notes that some victims are unknowingly drawn into facilitating criminal activity — a mechanism consistent with money mule recruitment. The sustained volume of Job Scam reports in the Scam.SG dataset across both Q4 2025 and Q1 2026 suggests that mule recruitment operations continued to target Singapore residents even as regulatory enforcement ramped up.
The sharp rise of Internet as a scam source in Q1 2026 (displacing WhatsApp) may also partly reflect scammer adaptation — moving activity to less-regulated web channels as mobile-line restrictions (SIM card mule controls, IMDA barring measures) increased friction on phone-based approaches.
NoteRegulatory information sourced from SPF. Observations linking regulatory context to Scam.SG report data are editorial inferences by Scam.SG and do not constitute SPF or government determinations.
Segment 6 — Methodology
Data Period
Data Source
Scam-Type Definitions
Scam Source Definition
Percentage Calculation
Loss Rate
Exclusions
Terminology