US EditionPublished • loading... • Updated
RCMP charges 7 suspects from the GTA in dark web bust
The RCMP seized 75 kilograms of narcotics and 10,000 pills from the 'RoadRunna' network that shipped about 400 drug packages weekly across Canada, officials said.
- On Thursday, the Royal Canadian Mounted Police said it dismantled one of the largest known Canadian dark web drug trafficking operations and arrested seven suspects from the Greater Toronto Area.
- After a dark web marketplace takedown by German authorities, the RCMP says the Serious and Organized Crime Unit in Milton, Ontario, took over the investigation following initial cyber referrals.
- Officers executed several search warrants that uncovered 75 kilograms of various narcotics, 10,000 prescription and non-prescription pills, electronic devices, and 'RoadRunna' branded drug distribution materials.
- Those arrested now face charges including conspiracy, trafficking, weapons offences, and possession of proceeds of crime involving Kevin Lau and Raphael Magdales.
- Insp. Nicole Noonan said `Criminals are finding increasingly sophisticated and modern ways to evade the law, but we will continue to identify, disrupt, and dismantle these types of networks`, while the RCMP says the dark web is encrypted and uses cryptocurrency.
Insights by Ground AI
23 Articles
23 Articles
Multiple suspects charged in dark web drug trafficking network: Ontario RCMP (Canada)
Mounties in Ontario have made seven arrests in what they say is one of the largest known dark web drug trafficking operations in Canadian history. The RCMP says the investigation began after a "takedown" of a dark web marketplace by German authorities, who contacted the force about several...
·Kelowna, Canada
Read Full Article
The RCMP reports that it dismantled a large drug trafficking network that used the hidden web (dark Web) and shipped its packages across Canada
·Montreal, Canada
Read Full Article
Coverage Details
Total News Sources23
Leaning Left13Leaning Right0Center5Last UpdatedBias Distribution72% Left
Bias Distribution
- 72% of the sources lean Left
72% Left
L 72%
C 28%
Factuality
To view factuality data please Upgrade to Premium
