INTERPOL Operation First Light Nets 5,811 Arrests and Seizes $293 Million


INTERPOL Operation First Light Nets 5,811 Arrests and Seizes $293 Million

Pierluigi Paganini
July 09, 2026

INTERPOL’s Operation First Light 2026 led to 5,811 arrests, blocked $293M in criminal assets, and disrupted global fraud and money laundering networks.

INTERPOL coordinated a four-month operation across 97 countries and territories that ended with 5,811 arrests and the interception of USD 293 million in illicit assets. Operation First Light 2026 ran from January 15 to April 30, 2026, targeting social engineering scams and the money laundering operations that process the proceeds. Over 142,000 victims were identified globally during the operation.

“A global anti-fraud operation involving 97 countries and territories has led to the arrest of 5,811 individuals and the interception of USD 293 million in illicit assets.” reads the press release by INTERPOL.”Operation First Light 2026 (15 Jan 2026 – 30 April 2026), coordinated by INTERPOL, focused on combatting social engineering scams and associated money laundering activities.”

The operation covered business email compromise, romance scams, investment fraud, sextortion, and impersonation schemes. In total, 152,808 cases were analyzed, 31,014 bank accounts blocked, and 15,606 suspects identified.

Some of the individual cases stand out.

“In Eswatini, police arrested 82 people and dismantled a criminal network running illegal online gambling, money laundering and elaborate impersonation scams. Authorities seized 240 electronic devices, foreign currency and a realistic replica of a Brazilian police station, complete with fake uniforms, signage and equipment.” continues the press release.

The scammers posed as Brazil’s Federal Police on video calls, convincing targets they were victims of a crime and needed to transfer funds for “safekeeping.” INTERPOL deployed an Operational Support Team to help Eswatini authorities handle the scale and complexity of the digital forensics involved.

The financial flows traced in Thailand were equally striking.

In Thailand, police made two arrests and uncovered a money laundering scheme that funneled illicit funds from romance scams into various cryptocurrencies, utilizing cross-chain token swaps to obscure the financial trail. Investigations showed that the digital wallet of one of the suspects, aged 20, had processed more than USD 122.5 million in just 10 months. states the law enforcement agency.

Twenty years old, $122 million in ten months. Either the career counseling failed somewhere, or this was always the plan.

INTERPOL’s stop-payment mechanism, I-GRIP, also proved its value in real time.

“Authorities in Singapore and Oman utilized I-GRIP to block a USD 6.6 million illicit transfer linked to a Business Email Compromise scam. In this case, a Singapore-based commodity trading firm was targeted by criminals impersonating a supplier.” continues the announcement.

In Macao, a public anti-fraud outreach campaign uncovered an active fraud in progress: a participant was in the middle of being manipulated by a criminal group impersonating officials, and police intervened before nearly USD 372,000 left the victim’s account. In Palau, 22 individuals were deported after authorities dismantled two scam centers operating out of hotels, running online fraud schemes using cryptocurrency and illegal gambling platforms against victims in other countries.

“Social engineering scams continue to pose a significant threat to our society.” said Tomonobu Kaya, Director of the INTERPOL Financial Crime and Anti-Corruption Centre. “Criminal syndicates exploit human psychology to manipulate their targets, and no nation can stay safe unless all countries are equipped and committed to jointly fighting back. INTERPOL is dedicated to supporting member countries in building a comprehensive, coordinated strategy to tackle cyber-enabled financial crimes, organized criminal networks and the money laundering that fuels them.”

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Pierluigi Paganini

(SecurityAffairs – hacking, Operation First Light)







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Meta stripped NameTag facial recognition code from its AI app one day after WIRED exposed it on 50 million phones. Meta says no decision has been made.

Meta removed nearly all traces of an unreleased facial recognition system from its smart glasses companion app on Friday, one day after WIRED reported that the software had been quietly embedded in an app installed on more than 50 million phones. The feature, which Meta internally called NameTag, was designed to convert faces captured by the company’s Ray-Ban smart glasses into unique biometric signatures and compare them against a database stored on the user’s device. WIRED also found that faces the system failed to recognise were cropped, indexed, and stored locally for future processing.

Andy Stone, Meta’s vice president of communications, told WIRED on Monday that the feature is “purely exploratory,” adding that no final decision has been made on what to do with it. That characterisation sits uneasily with the evidence WIRED documented. The version of Meta AI published the day of WIRED’s Thursday report contained several code libraries explicitly named for face recognition, a process for running the NameTag recognition pipeline, and a “Person recognised” alert the app would have shown if someone were identified.

Friday’s release stripped all of it out, along with a folder where the app would have stored the cropped images and biometric signatures of unrecognised faces. Meta did not answer WIRED’s questions about why the code was removed or whether the changes were planned before the story was published. A few fragments remain in the latest version, including an internal debug menu label and a dormant link meant to open a recognised person’s profile, pointing to parts of the system that are no longer there.

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The gap between Meta’s public statements and the code WIRED found is the central tension. Before the Thursday report, Stone dismissed the findings by writing that the company could not answer questions about how the system would work because “the feature does not exist.” Andrew Bosworth, Meta’s chief technology officer, called the reporting “incredibly misleading” and “absolutely dishonest.” Yet the code was functional enough to include three AI models, one to detect faces, another to crop them, and a third to encode them as biometric data, all embedded in the companion app for a product already at the centre of a mounting privacy crisis.

Meta declined to answer ten questions WIRED posed before publishing, including whether it had already created the database of face profiles NameTag uses, how long the app retains photographs and biometric data of unrecognised people, and whether that data would ever be sent back to Meta’s servers. The company also did not respond to questions about whether it was building NameTag for blind or low-vision users, or to criticism from privacy advocates who warned the system could let stalkers and abusers identify strangers in public.

NameTag first surfaced in February, when The New York Times, citing internal Meta documents, reported that the company was developing face recognition for its smart glasses and considering a launch as early as this year. One internal memo reportedly described releasing the feature during a “dynamic political environment” when privacy and civil liberties advocates would be distracted by other concerns. WIRED subsequently found that much of NameTag’s machinery had been built into the Meta AI app as early as January, months before any public acknowledgement, adding another layer to the company’s pattern of shipping first and disclosing later when it comes to its smart glasses.

Kade Crockford, director of the technology for liberty programme at the American Civil Liberties Union of Massachusetts, said the removal does not undo the original decision to ship the code and pointed to it as evidence that consumer privacy needs stronger legal protection than Congress has been willing to provide. The Massachusetts House of Representatives last week unanimously passed a consumer privacy bill that, if enacted as written, would impose strong enforcement provisions including a private right of action allowing aggrieved users to sue. “State lawmakers need to do their job and step up to protect consumer privacy,” Crockford said.

Meta’s sneaky tactics in slipping the face-recognition code into its smart glasses show exactly why data privacy bills need the teeth of strong enforcement,” Crockford added. “Companies like Meta prioritise their bottom line, so lawmakers need to speak in the only language its C-suite understands.” Whether a code removal prompted by investigative reporting constitutes a victory or merely a tactical retreat depends on what Meta does next, and on whether the regulatory pressure building on both sides of the Atlantic produces enforceable consequences before the feature quietly returns under a different name.



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