© Dado Ruvic/Reuters
Attackers are exploiting an unpatched remote code execution flaw in Adobe Commerce and Magento Open Source to install persistent backdoors on e-commerce sites, Dutch security firm Sansec reported, with the first intrusions observed Sept. 4 and no vendor fix available as of Sept. 6.
Sansec's forensics team, in an advisory, named the flaw StyleSmuggler. No CVE identifier has been assigned. As of Sept. 7, Adobe's Magento security bulletin index listed no September advisory, and the flaw does not appear in CISA's Known Exploited Vulnerabilities catalog, leaving an unknown number of merchants exposed during a window in which working exploit traffic is already circulating.
Magento underpins a large share of mid-market online retail, and Adobe has sold it as Adobe Commerce since acquiring the platform in 2018. The codebase has been a durable target for payment-skimming crews: Sansec has tracked Magecart-style card theft against Magento storefronts for close to a decade, and the platform's checkout position makes any unauthenticated code execution flaw unusually valuable.
According to Sansec's analysis, StyleSmuggler is a two-stage chain that abuses the platform's GraphQL interface. Attackers first inject PHP code into files Magento writes on its own, such as failure reports, then trigger execution through the platform's "Payment Transaction Failed Reminder" email routine. Because the trigger fires when the reminder is generated, no recipient has to open the message for the payload to run.
The vulnerability was confirmed on Magento Open Source 2.4.7, 2.4.8 and 2.4.9. The detail likely to unsettle merchants most is the first known victim: a store running 2.4.6-p15 with all available patches applied. Being current on Adobe's release cycle did not prevent compromise.
The implant Sansec documented is built to survive routine inspection. It runs under a process name mimicking a Linux kernel thread, [kworker/u:8:0], with the binary written to ~/.local/share/.gvfsd/gvfsd-user and a cron entry relaunching it every five minutes. Sansec also listed the domain 247.cdnflare.xyz among its indicators of compromise.
Sansec advised merchants to disable GraphQL where the storefront can tolerate it, disable the PHP proc_open function, and mount /tmp, /var/tmp and /dev/shm with the noexec option. Unofficial community patches have been published by Disrex Group, ProxiBlue and Graycore. Disrex said it independently identified two compromised stores and a third that was attacked without being breached.
Adobe's most recent scheduled Commerce bulletin, APSB26-92, was published Aug. 11 and addressed critical and important flaws across the 2.4.4 through 2.4.9 branches. The company's next scheduled security release is Sept. 8. Adobe did not appear to have commented publicly on StyleSmuggler.
© Minh Connors for The New York Times
© Tierney L. Cross/The New York Times
It won’t work:
My suspicion was that GPT 5.6-Cyber would succeed, but the frequency and manner of its success removed all doubt. We have to reassess sandboxing quality for capable AI agents, and in general the software stack with which they interact.
An off-the-shelf VM is not enough to contain a modern, cyber-capable AI agent. There is simply too much attack surface. Even innocuous features (like running with a display) add extra, exploitable attack surface.
© Daniel Zender
© Manuel Orbegozo for The New York Times
This is interesting:
The records describe a force-generation mechanism for several General Staff components, including the GRU, Main Operational Directorate, and 8th Directorate, which is associated with protected communications, cryptography, and information security.
[…]
The reporting also linked a 2024 Department No. 4 graduate, Aleksei Kondrashov, to Military Unit 74455, widely known as Sandworm.
That unit has been associated with destructive cyber activity against Ukraine and other targets, including the 2017 NotPetya attack.
The reports do not establish that every listed graduate participated in a named operation; assignments should therefore be described as reported unit placements, not proof of individual operational involvement.
The Bauman material reframes Russia’s cyber capability as an institutional system, not merely a collection of well-known threat groups.
It suggests that Moscow has formalized a recurring pathway from university recruitment to military service, where students receive supervised technical and ideological preparation before entering intelligence, cyber, and security roles.
For defenders, the leak reinforces the need to track Russian operations as a combined threat: espionage, destructive activity, military reconnaissance, technical surveillance, and influence campaigns may draw on related personnel pipelines and overlapping doctrine.
The exposure of Department No. 4 also provides researchers with a clearer lens for understanding how the GRU sustains cyber capacity beyond the familiar APT28 and Sandworm brand names.
The China-nexus espionage group Fire Ant has moved from compromising virtualization platforms to implanting Cisco IOS XR routers and TACACS authentication servers. They are using them to capture traffic, harvest administrator credentials and suppress the logs defenders rely on, said researchers at Sygnia, an incident response firm.
Researchers first documented Fire Ant in July 2025 for deep intrusions into VMware ESXi and vCenter environments. The new report describes the same actor operating a layer lower, in what researchers call the trust layer — the routers, authentication servers and Linux management hosts that carry traffic, authorize administrators and record what happened.
Researchers assess a strong overlap with UNC3886, the China-linked group Google's Mandiant tracks for targeting network edge and virtualization systems, while noting the tooling has evolved rather than been reused wholesale. The activity is distinct from the Salt Typhoon and Volt Typhoon campaigns.
On Cisco IOS XR routers, the operators deployed custom control-plane malware and created generic routing encapsulation tunnel interfaces that left no trace in device configuration files.
On authentication infrastructure, a previously unreported toolkit that the researchers named TacTap injected a malicious library into the tac_plus daemon to capture credentials as administrators authenticated, storing them with simple XOR obfuscation.
A second new implant, BridgeAgent, ran on Linux jump hosts disguised as a Zabbix monitoring agent and persisted through a systemd unit.
Anti-forensic work was central to the operation. Researchers said the actor modified syslog functions to filter and delete selected records, rewrote wtmp and utmp login records, suppressed authentication logging, filtered command output, disabled SELinux and altered firewall rules. Backdoors were triggered by magic strings inside network packets rather than by listening ports, leaving little for port-based detection to find, and some components had lain dormant since 2025.
Asaf Perlman, Sygnia's director of incident response, said the group's aim went beyond individual machines. "Fire Ant didn't just compromise systems. It compromised the trust layer those systems depend on."
The firm withheld the victim's identity and sector to protect the organization and connected networks, and said the pattern is most consistent with long-term espionage. Critical infrastructure networks were reached but appear to have been limited to reconnaissance. Cisco did not immediately comment.
The findings feed directly into an active regulatory push. CISA and allied agencies have issued repeated hardening guidance for network edge devices after the Salt Typhoon telecom intrusions, and operators covered by the EU's NIS2 directive face supply-chain and incident-reporting duties that extend to routers and authentication systems. Detecting this class of intrusion requires out-of-band verification that many organizations do not yet perform.
Sygnia published file hashes and YARA rules for the malware and persistence components.
© Karsten Moran for The New York Times
© Anna Rose Layden/Reuters
Authorities in Australia have arrested two men believed to be members of TeamPCP, a prolific cybercrime and data extortion group blamed for perpetrating the longest running spree of software supply chain attacks ever.
In a statement released today, the Australian Federal Police (AFP) said two men from Western Australia, aged 21 and 23, were arrested in connection with a “sophisticated cybercrime syndicate that allegedly created malicious open-source software to rob thousands of global businesses.”
The AFP did not name the defendants, but KrebsOnSecurity learned the 21-year-old suspect’s real identity in June, and has been communicating with him ever since. This story includes interviews with TeamPCP’s self-described spokesperson, and examines clues left behind by the TeamPCP leader that likely led to his undoing.
TeamPCP vaulted onto the cybercrime scene in late 2025, embedding malicious code in hundreds of open source software tools and extorting victims for profit. Members of the group made headlines by compromising corporate cloud environments using a self-propagating worm dubbed Shai-Hulud, which added malicious code to open source programs maintained by developers whose credentials at public code repositories like GitHub or NPM were phished or stolen.
Writing for Wired, journalist Andy Greenberg described TeamPCP’s core tactic as a kind of cyclical exploitation of software developers.
“The hackers gain access to a network where an open source tool commonly used by coders is being developed,” Greenberg wrote in May. “The hackers plant malware in the tool that ends up on other software developers’ machines, including some who are writing other tools intended to be used by coders. The malware allows TeamPCP’s hackers to steal credentials that let them publish malicious versions of those software development tools, too. The cycle repeats, and TeamPCP’s collection of breached networks grows.”
TeamPCP also has practiced something akin to cyclical recruitment. In May, the source code for the third iteration of Shai-Hulud was published online, and TeamPCP soon after launched a contest offering $1,000 in virtual currency to whichever participant could conduct the largest supply chain operation using the worm’s code. According to the contest rules, participants were scored based on the number of weekly and monthly downloads of packages they compromised — directly incentivizing them to target the most popular code libraries.
A screenshot of a message from TeamPCP’s Telegram account, announcing the supply chain hacking contest. Image: dataminr.com.
“TeamPCP has stated the competition is a recruiting opportunity and they intend to purchase all meaningful access harvested from participants’ campaigns,” the security firm Dataminr wrote. “The $1,000 XMR (Monero) prize is a recruitment floor and has been dismissed by the actor as ‘just like participation trophy,’ adding ‘if you find something good you will be paid way more,’ confirming the contest’s true function as talent identification and malicious access acquisition at scale.”
In March, TeamPCP executed a supply chain attack targeting AI infrastructure by compromising the code for LiteLLM, an open source AI gateway that connects users to more than 100 different large language models. A recent analysis by the security firm CloudSEK found TeamPCPs attack on LiteLLM harvested cloud service keys and other secrets from more than 2,500 organizations, including many of the world’s top technology companies.
In May, TeamPCP claimed credit for compromising at least 3,800 code repositories at the Microsoft-owned GitHub, after a GitHub developer installed a code extension that was compromised by TeamPCP’s malware.
Security experts say TeamPCP is less of a hacker group than an amalgamation of threat actors from multiple cybercriminal gangs who sometimes work together toward similar goals.
“It is not a structured criminal crew with a single operator,” said Austin Larsen, a principal threat analyst with the Google Threat Intelligence Group. “It is a peer community of individually-skilled actors, with one clear center of gravity.”
That center of gravity is George Prepakis, an accomplished security researcher and self-described exploit developer who operates the Twitter/X profile @kernelstub. Earlier this year, @kernelstub tweeted a public invite link to a Matrix chat server he created and dubbed “Cybercats,” and TeamPCP and several other cybercrime entities have been using this server to communicate daily for the past several months.
A screenshot of the Matrix chat server “Cybercats,” whose members used hacker handles associated with multiple distinct cybercrime groups that have occasionally collaborated on a series of supply chain and data ransom attacks over the past nine months.
Kernelstub, like other administrators in the Cybercats chat, has been using his Twitter/X profile name as his handle in these Matrix communications, frequently tweeting references to other members and to conversations taking place in the Cybercats chat. In a number of cases, the corresponding X accounts for members of the Cybercats chat taunted cybercrime victims publicly before the incidents were reported in the news media.
The Cybercats administrator listed at the top of the screenshot above — “Boxturtle” — is a close associate of TeamPCP who has been tweeting about the group’s conquests under the name @xpl0itrsturtle. This handle corresponds to a data breach broker active on Breachforums and Darkforums who has been selling data stolen in a wave of recent breaches at automobile manufacturers, including BMW Group, Audi, Honda, Mercedes-Benz, Volvo and Toyota, as well as data allegedly taken from Snapchat and SportRadar.
The data leak site for the extortion group or handle “xpl0itrs.”
The Cybercats administrator “SeesawSec” in the screenshot above is the alias of whoever is behind the cybercrime group known as Fulcrumsec, which recently claimed credit for data extortion attacks against the pharmaceutical giant Novo Nordisk, the data broker LexisNexis, and Avnet, a Fortune 500 distributor of electronic components.
The data leak site of Fulcrum Security, a.k.a. Fulcrumsec.
The Cybercats administrator “@pcpcasper” also has been using a similar name on X to discuss TeamPCP’s attacks and victims. This person has an extensive message history on Telegram, where their messages and shared videos show @pcpcasper is an active and vocal member of the National Socialist Network, a neo-Nazi political organization based in Australia.
At one point in these chats, @pcpcasper shared videos and images of what they claimed was their cat, and several of those videos place this user in Western Australia. One source close to the investigation told KrebsOnSecurity that @pcpcasper was one of the two arrested, a claim supported by messages that @kernelstub posted online this morning.
The Cybercats member roster pictured above also features an administrator with the username “T,” which is short for the now-banned Twitter/X profile @pcpcats, the account operated by the self-described TeamPCP spokesperson who was arrested today. As we’ll see in a moment, @pcpcats also is from Western Australia.
By the time @kernelstub tweeted a public invite link to the Cybercats Matrix server, T/@pcpcats was posting only infrequently to the group chat, with other members often inquiring as to his whereabouts and well-being. The group’s collective concern related to @pcpcats’s tendency to blame his increasingly extended absences on the use of hallucinogens and other narcotics that kept him awake for days on end, but also caused him to crash in bed for several days after the highs wore off.
The Cybercats member @pcpcats has used multiple nicknames on the cybercrime forums, including EllisD25/LSD on Darkforums, BulkDMT on Breachstars, and Express on Breachforums. These accounts are linked because they all advertised the same Tox ID and/or Session ID as instant message contact handles in their cybercrime forum posts. BulkDMT was also known on the forums as DMT Host, which was a virtual private server (VPS) hosting service that was peddled on Darkforums and Breachstars.
DMT Host/EllisD25, posting on the English-language cybercrime community DarkForums in September 2025. Image: ke-la.com.
According to the cyber intelligence firm Intel 471, Express registered on Breachforums using the email address shitstickpp@gmail.com. Intel 471 finds Express posted on Breachforums across a two-month period in 2025 using four different Internet addresses located in South Africa. On July 30, 2025, Express announced on Breachforums they were selling access to 14 gigabytes of data stolen from South Africa’s State Information Technology Agency.
The threat intelligence platform Flashpoint recorded more than a year’s worth of messages from the TeamPCP leader’s alter ego on Telegram — Persy_PCP — who claimed they split their life living between two countries [full disclosure: Flashpoint is an advertiser on this blog]. “I have these [files] as well, problem is these are in another country,” Persy_PCP explained to another user inquiring about a stolen data set in November 2025.
Later that month, Persy_PCP complained, “My whole country is racist and they want people like me dead.” Flashpoint records show BulkDMT shared in September 2025 that “this country is going to fucking starve when they take the farmers land,” a likely reference to white landowners in South Africa who claim to be targeted by an ongoing genocide campaign.
This tracks with public reporting on TeamPCP. Cyberscoop reported in June that Google had traced TeamPCP’s residential and mobile Internet address connections to South Africa, “indicating the primary operator was located there during at least some of its attacks.”
BulkDMT also shared on the group chat at Breachforums that they were recovering from an addiction to methamphetamine. “My life is kinda fucked rn [right now], but that’s fine and there isn’t really a point in pouring so much emotional energy into that fact, my parents had money but I unfortunately got really addicted to some things so I don’t get to benefit from that. As long as I continue to survive, stay sober, and move closer towards my goals that’s enough drive and meaning.”
The identity threat protection company SpyCloud finds shitstickpp@gmail.com shows up in the registration of an account called ChristmasSnow on the cybercrime community Raidforums in 2022. Nearly all of the Internet addresses used to access that account came from ISPs in Perth, Australia, SpyCloud found.
KrebsOnSecurity looked up all of those Perth IP addresses in passive DNS records maintained by DomainTools.com, and found one of them — 211.27.196.111 — for several years was used as a private file server by a family in Perth with the last name of Thomson. Those records show at least three hosts — ithomson.direct.quickconnect.to (a remote Synology server), kthomson0061.direct.quickconnect.to, and joshuawthomson39.myqnapcloud.com (a QNAP network storage device) — persisted at that address between 2022 and 2025.
Searching on “joshuathomson39” in the breach tracking service Constella Intelligence reveals an account at the freight forwarding company kwe.com created in the name of Joshua Thomson from Perth, Australia. The open source intelligence platform Epieos finds the phone number attached to that kwe.com account was used to register a Facebook profile for Josh Thomson, which says his family includes a brother named Ruben, his father Ian, and his mom Cindy.
That Facebook profile also says Josh and his family are originally from Pietermaritzburg, in KwaZulu-Natal, South Africa, but currently living in Cottesloe, a beach-side suburb of Perth. A search in DomainTools for Ian Thomson and Australia unearthed five domains by the same registrant, including securecomputing.au, thomson.org.au, and thomsonfamily.net.au. Ian Thomson is a dentist in Cottesloe, and a biography says he graduated from The University of the Witwatersrand in Johannesburg, South Africa.
Constella finds a joshua@thomson.org.au registered a number of accounts online, but Josh doesn’t seem to have much of a connection to dodgy cybercrime forums. His brother Ruben, on the other hand, has quite the presence on these communities, dating back to at least 2018. Constella reports ruben@thomson.org.au frequently reused the password “joshuathomson1,” and Constella further finds that password was used by just a handful of accounts, including yolosolo17@gmail.com and surfinup8@gmail.com.
According to Intel 471, surfinup8@gmail.com was used to register the user Yolosolo17 on the crime forum Altenen in 2018, and that user account was registered from the Perth address 110.141.230.15. On Altenen, Yolosolo17 advertised free web proxies, as well as the domain rubenthomson.com, which was at one point used to sell steeply discounted iPhones. DomainTools says rubenthomson.com was hosted at 110.141.230.15 and registered to surfinup8@gmail.com.
A cached copy of the domain rubenthomson.com from 2017 shows a login page underneath a banded stack of money. Image: archive.org.
SpyCloud reports 10.141.230.15 was used by the email address sheepstealing@gmail.com on Raidforums and surfinup8@gmail.com on Nulled, and that the same IP was used by the email addresses ian@thomsonfamily.net.au, jasper@yakuza.cc, and rubenthomson1@gmail.com. SpyCloud also shows that sheepstealing Gmail address is tied to the accounts Sheep420, YoloSolo117 and Yakuza.cc on Raidforums, and to the account “Sheep Stealing” on Hackforums. Intel 471 says sheepstealing@gmail.com was used to register the account DingoFlour on Breachforums in October 2023, as well Sheepx on Altenen.
Epieos reports that ruben@securecomputing.au is tied to an Airbnb account for Ruben, who described himself as a Web developer who went to school at the University of Western Australia and was living outside the country. “Hey, I’m Ruben, my friends call me Ellis. I’m a Perth creative who occasionally books rooms when visiting family and for photography.”
Epieos also finds sheepstealing@gmail.com registered an upwork.com profile under the name Ruben, who said his main skills are setting up secure server hosting solutions and PHP full-stack Web development.
“I’m familiar with Linux, working with relational databases (SQL),” the Upwork profile reads. “I also script in Python mainly for writing social media bots.”
The Upwork profile for Ruben Thomson in Cottesloe, Australia.
Epieos further discovered sheepstealing@gmail.com is connected to a Microsoft account for Ruben Thomson, and to a now-defunct GitHub account called XmasSnow/XmasSnowisBack that scammed people on the forums in 2022 by claiming to sell exclusive exploits for recently-released software patches (recall that shitstickpp@gmail.com was used to register a forum account named ChristmasSnow).
This same sheepstealing email address registered a Twitter/X account in 2026 called “Gone Fishing” that lists its location as South Africa. That Gmail account also left several reviews for businesses listed on Google Maps over the past seven years, but all of those establishments are located on the west coast of Australia.
Business reviews in Western Australia left by the Google account sheepstealing at gmail.com.
The people search service Pipl finds a 21-year-old Ruben Thomson in Western Australia who has a phone number ending in 979. A lookup on that number at Epieos reveals it is connected to a TikTok account under the name Ellis, and to a PayPal account in the name of Ruben Thomson.
Finally, a search on the name Ruben Thomson from Cottesloe at the Australian government’s record of registered businesses finds he has incorporated or served as an official in multiple companies created since 2024, including Secure Computing Solutions, Tensor Industries, and another entity ironically named OPSEC Express. Recall that Express was BulkDMT’s nickname on Breachforums.
Australian companies connected to Ruben Thomson. Image: abr.business.gov.au.
It’s ironic because OPSEC is short for the term “operational security,” which refers to techniques and behaviors used to obfuscate and compartmentalize one’s real-life identity online, and using your cybercrime handle as part of your own company name is very much the antithesis of that practice.
There is at least one other major opsec failure by Ruben that exposed a link to TeamPCP. In June 2025, someone using the name Ruben Thomson registered on HackerOne, a popular “bug bounty” program that seeks to reward and recognize researchers who agree to work with affected software vendors to help fix the flaws before publishing about their findings. What was Ruben Thomson’s chosen HackerOne username? Deadcatx3, a nickname that has been flagged by multiple security firms as an alias used by TeamPCP.
The HackerOne profile for “Ruben Thomson” uses the nickname Deadcatx3, which multiple security firms have concluded is an alias used by TeamPCP. Image credit: flare.io.
In early July 2026, not long after having discovered clues about Ellis’s real life identity, KrebsOnSecurity interviewed the TeamPCP leader via Signal, where he was remarkably open about his activities and personal struggles [for the sake of simplicity, the TeamPCP spokesperson will be referred to from here on as Ellis].
Ellis claims he stopped doing cybercrime for TeamPCP in March 2026 — just before the attacks that compromised LiteLLM — and that at least one other individual has taken over the group’s leadership since then. Ellis shared that a year earlier he had just completed the latest in a series of detox and sobriety programs, and was two months sober when he reconnected with some old friends from the malware development scene.
“One year ago I needed help monetizing some [GitHub credentials], I was two months sober and needed a distraction and something to keep busy as well as people to speak to,” Ellis said. “I had largely disconnected from my old circle, they had become very toxic and I needed to get away from the substances. Previously I had done some mass exploitation campaigns and grew up doing [malware development] and [capture the flag] contests. There were some friends who were also vending but had stopped a while, and one of them introduced me to some chats where I posted access for sale.”
Prior to that, Ellis said, he was homeless and hopping between “some very unstable places.”
“Blackhatting is fun,” he said. “There are actual rewards and incentives to learn and you grow with your team. Without qualifications, no employer will even take the time to hear you out.”
Ellis claims he’s earned a grand total of about $20,000 for his activities with TeamPCP, and that it was never about the money or fame for him. Asked whether his experiences with TeamPCP might prepare him for gainful employment in a legitimate IT job, Ellis said he doubted it.
“I am nowhere close to a skill level where I am comfortable, and this would take maybe half a decade of further experience,” he said. “I no longer have to choose between rent and food for that I’m grateful and so are the team members.”
Ellis expressed no remorse over his cybercrime activities, and said he was grateful for the friendships and relationships built throughout his engagement with TeamPCP. The young hacker also seemed resigned to his fate, and told KrebsOnSecurity that he’ll accept the consequences if he’s ever arrested.
“If I’ve already been found out then its out of my control, I’ll make peace with that,” he said. “Honestly, I think someone like me needs a lot of help that prison just can’t provide. If I had the funds to study different parts of the field and closer guidance, this would have turned out differently. But that’s a pipe dream and we both know this.”
It is clear from reading Ellis’s posts to the group’s Matrix server chats that his struggles with sobriety are ongoing. On Thursday, June 25, Ellis told @kernelstub he was about to “trip” with his “homie.”
“What kind,” @kernelstub inquired.
“Ketty and some DMT,” Ellis replied, referring to the dissociative anesthetic ketamine and dimethyltryptamine (DMT), a powerful psychedelic compound that is found naturally in some plants but is also synthetically produced in underground lab environments. “There’s a little 2cb so we might throw that in the mix,” he continued, referring to another psychedelic compound by its chemical shorthand.
Roughly two weeks before his arrest, Ellis told KrebsOnSecurity he was ready to leave his life of crime behind and was prepared to turn himself in, but that in the meantime he was making plans to tie up loose ends.
Less than 24 hours later, the TeamPCP leader posted an image on Telegram showing a yellowish powdered substance in a baggie and on a scale, possibly synthetic DMT. The image shows the powder being weighed next to a series of small vape cartridges, two of which are open on the table in front of the photographer.
An image posted by the TeamPCP leader to Telegram, advertising his acquisition of some type of psychoactive substance, most likely a synthetic version of the powerful hallucinogen known as DMT.
The two defendants were arrested Wednesday morning. The AFP said the men face a combined 14 cybercrime offenses and are scheduled to appear in Perth Magistrates Court today.
Charlie Eriksen is a security researcher at Aikido Security who has closely followed TeamPCP’s cybercrime campaigns. Eriksen said TeamPCP are a good example of a new kind of threat actor that does not fit neatly into the usual categories.
“They are not a state actor, not quite organized cybercrime, and not purely ideological,” he said. “Their motivations seem to mix money, disruption, attention, and ideology.”
Eriksen said that historically there has always been a meaningful gap between reading about an attack technique and being able to reliably turn it into an operational campaign, but that large language models (LLMs) and artificial intelligence increasingly are helping threat actors to bypass that knowledge gap.
“You had to understand the research, adapt the code, troubleshoot it, build infrastructure around it, and then repeat that process across different targets,” he said. “LLMs have compressed that gap significantly.”
According to Eriksen, this creates an environment where threat actors suddenly have the ability to operate at significant scale without having developed the operational discipline that traditionally accompanies that level of capability. Put another way, it sets the stage for cybercriminals who are capable enough to cause significant damage, but not necessarily careful enough to understand or care about the consequences.
“They can be noisy, they can make mistakes,” he said. “They can leave evidence everywhere. They can take risks that a professional criminal group or intelligence service would consider completely unacceptable. But that does not necessarily make them less dangerous. In some ways, it can make them more dangerous.”
In a recent blog post, Eriksen called TeamPCP’s Shai-Hulud worm the “best thing to happen to supply chain security,” because it forced GitHub and other public coding platforms to erect new security safeguards.
In direct response to TeamPCP’s broad success at pushing poisoned versions of popular software packages, GitHub in late July introduced a three-day “cooldown” mechanism for Dependabot, the platform’s tool for auto-fetching newly shipped updates for any package dependencies. Cooldown periods are designed to help buy time for security tools and package maintainers to identify and remove any compromised versions. Other coding ecosystems like Python and various JavaScript platforms also added support for cooldown periods this year amid growing calls from security experts about the need for more widespread adoption of the safety feature.
Eriksen said TeamPCP’s legacy is that they achieved in the span of a few months what the supply chain security community has been unable to do for years.
“They managed to wake up Microsoft to the fact that they had become negligent in terms of security,” Eriksen said. “By compromising GitHub and stealing their source code, they humiliated Microsoft into action, making them finally act on what we had been asking them to do and take seriously for a while now.”
Update, 10:08 a.m. ET: A story this morning from ABC News in Australia confirms Ruben Ian Thomson of Cottesloe was one of the two arrested. The 23-year-old suspect thought to be @pcpcasper, Michael Gaebler, also was arrested in Perth. ABC News reports that Thomson was denied bail (Mr. Gaebler’s attorney reportedly did not request bail for his client), and that both men will be held in custody until their next court appearance on September 18.
© Victor Arce
© Brennan Smart for The New York Times
The AI Security Institute has a new report of AI systems engaging in “unsanctioned behavior”—what I have been calling “genie behavior—while being tested on their cybersecurity capabilities.
The incident stemmed from a single evaluation where agents were given a task of solving a cyber security challenge. We ran this challenge 122 times across several models. Our investigation found that in 10 of those runs, an AI agent took autonomous, unsanctioned action on the live internet, targeting real people and organisations. In total, we catalogued 19 such actions. Almost all of this behaviour (17 actions) came from a single model, Anthropic’s Mythos 5, with 2 actions involving OpenAI’s GPT-5.6-Sol with cyber classifiers (mechanisms to prevent misuse) disabled. In the most serious case, an agent tried to insert malicious code into an open-source project. In an attempt to get the code approved, the agent engaged in social engineering—creating fake online identities and using them to pressure the project’s maintainer to approve the code. A human maintainer caught and refused to approve the malicious code.
[…]
Below, we highlight the four most significant behaviours observed. A full summary of cases is available in our technical incident report.
- An attempted supply-chain attack on real open-source software. In the most serious sequence, an agent tried to insert malicious code into a publicly used open-source project and took actions in an attempt to secure approval for this insertion by human reviewers. The agent researched the project’s human maintainers, created multiple fake identities, and used the fake identities to socially engineer a real maintainer into approving the code. When the agent’s pull request was challenged in public, it edited its earlier activity to appear harmless and considered adopting a fresh identity to continue. The agent used Tor to bypass some network restrictions on GitHub, which is what first triggered AISI’s security alert.
- Attempts to deceive and target real people. As part of the same effort, the agent tried to contact real people directly, sending messages and files through an online file-transfer service to persuade them, or their own AI coding tools, to run malicious code. Some messages carried harmful payloads, and some were attempts at social engineering; targeted at real people—something we’ve never previously observed.
- Attempts to plant and prompt-inject malicious code. The agent tried to insert malicious instructions where it reasoned that other automated AI systems might pick them up and execute them. Prompt-injections are hidden instructions designed to manipulate AI coding assistants.
- Collaboration between independent agents being assessed simultaneously. One agent left public messages on GitHub offering collaboration with other agents working on the same challenge. It also provided instructions to reuse accounts and artefacts it had left behind, which were discovered and used by subsequent agents.
What’s especially interesting about this technical report is that, unlike what we’ve been getting from OpenAI and Anthropic, we can see the exact prompt. It’s in Appendix B. And reading it, it seems that the models didn’t break any rules—they found loopholes in the rules. They behaved like a genie.
"AI adoption without governance is not innovation — it is unmanaged risk. The next phase of enterprise security is about controlling what AI can access, what it can do, and who remains accountable." — Mohammad Arif, Head of Information Security, Guild Group
Cássio De Alcântara is Director, LATAM Sales at Rapid7.
Across Latin America, organizations are embracing cloud, AI, and digital transformation to drive innovation and business growth. These technologies create new opportunities, but also introduce greater complexity and expanding attack surfaces.
In this environment, security leaders are being asked to understand where risk exists across increasingly distributed environments and quickly eliminate blind spots like Shadow IT and Shadow AI – all without adding operational complexity.
To help security leaders and practitioners address this complexity, Rapid7 is excited to announce a new strategic distribution partnership with Licencias OnLine (LOL) across Latin America.
In order to keep day-to-day business operations moving, organizations need security solutions that not only protect critical assets but also support innovation, regulatory compliance, and long-term digital transformation.
Rapid7's AI-powered cybersecurity operations platform helps organizations strengthen cyber resilience by unifying continuous exposure management, AI-driven threat detection and response, and security automation. By connecting security data across endpoint, cloud, identity, and infrastructure environments, organizations leverage one platform to gain the visibility to reduce risk and act with confidence.
Success in today’s fragmented cybersecurity environments depends on a strong ecosystem of partners who can help organizations implement, optimize, and maximize the value of unified security operations.
This is where Licencias OnLine comes in. With a strong, well-established presence across Latin America, deep cybersecurity expertise, and a highly specialized channel ecosystem, Licencias OnLine brings the local knowledge, technical enablement, and operational agility needed to help partners grow their cybersecurity practices and deliver greater value to customers.
Together, Rapid7 and Licencias OnLine will invest in technical training, partner enablement, joint marketing initiatives, and go-to-market programs that help partners expand managed security services, strengthen customer relationships, and accelerate business growth across the region.
As organizations across Latin America continue to modernize their IT environments, they should have access to security operations that are integrated, intelligent, and designed for today's AI-powered threat landscape.
Rapid7's open platform supports this approach through hundreds of technology integrations that help organizations eliminate security silos, improve visibility across their attack surfaces, and automate response workflows. This enables security teams to reduce operational complexity while improving cybersecurity program maturity.
By combining Rapid7's global cybersecurity innovation with Licencias OnLine's regional expertise and trusted partner network, this new alliance will make it easier for organizations across Latin America to strengthen cyber resilience while enabling partners to see greater success through measurable business outcomes.
We're excited to begin this next chapter together and look forward to supporting our partners as they help customers build stronger, more resilient security operations across the region.
Ready to grow with Rapid7? Discover how Rapid7 and Licencias OnLine are helping partners accelerate cybersecurity maturity across Latin America.
ICE collected nearly a million DNA samples last year.
© Jason Henry for The New York Times
Gopan Sivasankaran is Rapid7's Regional Director, Middle East & Africa.
Across Egypt, Nigeria, and Kenya, organizations are expanding their use of cloud infrastructure, artificial intelligence, digital services, and connected operations. But more technology does not automatically create stronger security operations; many security teams are not short on data, but rather on time, context, and specialist capacity.
As environments expand, the challenge is no longer finding another security product. It is turning existing technology and new investments into clearer risk decisions, faster investigations, and more consistent response, which requires more than software.
Africa has been an important region for Rapid7 for many years, and we’re proud of the role we’ve played in protecting organizations across the continent. We see significant opportunity ahead and remain committed to investing in our presence, partner ecosystem, and customer relationships across the region.
That continued investment is why Rapid7 is expanding its partnership with StarLink across Egypt, Nigeria, and Kenya.
Security teams are often managing data across endpoints, cloud environments, identities, and third-party systems. Adding another disconnected tool can increase workload rather than reduce it. Modern security operations require a more connected approach. Exposure data should help teams understand where risk exists. Detection should identify active threats. Response and automation should help teams act before an issue becomes a larger business incident.
But even a well-designed platform needs skilled partners who can help customers deploy it, integrate it, and adapt it to local operational needs.
Cybersecurity maturity varies by country, industry, and organization. A bank in Africa, a digital services provider in Kenya, a public-sector organization in Egypt, and an enterprise in Nigeria may share some security challenges, but they do not operate in identical environments. Partners provide the bridge between global technology and local customer reality.
Through this collaboration, Rapid7 and StarLink intend to give resellers, systems integrators, and managed security service providers access to technical enablement, solution expertise, and joint go-to-market support. The goal is to help partners build sustainable security practices, not simply complete individual product transactions.
Rapid7’s security operations approach brings exposure management, threat detection and response, managed services, and automation together. This can help teams connect two questions that are too often handled separately:
Where are we most exposed?
Where are attackers active now?
When partners can help customers answer both questions using shared security context, they can support more informed prioritization, faster investigation, and clearer remediation decisions.
Africa’s digital growth will continue to create new security demands. Meeting them will require technology, but also skills, services, local understanding, and long-term collaboration. Rapid7 and StarLink are working together to help build that capability across the region.
Ready to build your security practice with Rapid7? Contact your Rapid7 or StarLink representative for upcoming training, technical enablement, and joint go-to-market opportunities, or explore the Rapid7 PACT Partner Program.
Ross Baker is Senior Director, Northern Europe at Rapid7.
As organizations across the United Kingdom and Ireland embrace AI, cloud technologies, and digital transformation in the name of enhancing customer experiences and accelerating business growth, the cybersecurity landscape must continue to evolve just as quickly.
In this environment, business leaders still expect security to enable innovation, not slow it down. They're pushed to reduce risk, improve visibility across expanding attack surfaces, and respond faster than ever before, with limited resources now table stakes. This is precisely why Rapid7 is excited to announce a new strategic distribution partnership with Exclusive Networks across the United Kingdom and Ireland, following previous announcements alongside the firm to better support partners across Benelux and the Nordics.
Organizations no longer want disconnected security tools or transactional vendor relationships. They're looking for trusted advisors who can help simplify security operations, strengthen cyber resilience, and deliver measurable business outcomes.
In this moment, cybersecurity customers are demanding experiences that create more calm. This means no more disconnected security tools or reactive approaches, but integrated security operations, trusted expertise, and partners who can help them improve visibility and build long-term cyber resilience.
The UK and Ireland represent one of Europe's most mature and partner-driven cybersecurity markets, with partners playing an increasingly important role in helping organizations modernize security operations for today’s AI-enabled threats.
This partnership with Exclusive Networks reflects Rapid7's continued investment in the regional channel ecosystem. More than expanding distribution, it's about empowering partners with specialist expertise, technical enablement, and the go-to-market support they need to grow their cybersecurity businesses with confidence.
Exclusive Networks has built an outstanding reputation as one of the UK's leading specialist cybersecurity distributors, combining deep technical expertise with a strong, partner-first approach.
Together, we're creating new opportunities for partners to strengthen their capabilities while delivering greater value to customers.
Security teams are increasingly looking for platforms that unify exposure management, threat detection, response, and automation. Again we go back to the urgent need for improved visibility while reducing operational complexity.
Rapid7's AI-powered cybersecurity operations platform helps organizations simplify SecOps through integrated exposure management, managed detection and response, and security automation. By bringing these capabilities together, customers can identify risk earlier, respond faster, and improve cyber resilience without adding more tools.
Combined with Exclusive Networks' technical enablement, solution engineering expertise, and established channel ecosystem, this new alliance makes it easier for partners to deliver integrated cybersecurity solutions while expanding managed security services and fostering long-term customer relationships.
Rapid7 and Exclusive Networks share a common commitment to helping partners grow through technical excellence, collaboration, and continuous enablement. Together, we're investing in the resources, expertise, and support needed to help partners succeed in one of Europe's most dynamic cybersecurity markets.
Ready to grow with Rapid7? Head to our Partners page for more news, resources, and opportunities.
This essay was written with Barath Raghavan, and originally appeared in The Guardian.
In July, Hugging Face, a company that hosts much of the world’s AI software and open-source AI models, was hacked. A malicious dataset had been used to run code on one of its servers. Whoever was behind it captured internal security credentials and moved through systems over a weekend, running thousands of actions from a swarm of temporary server environments. It looked like the work of a sophisticated criminal group.
It was not. It was one of OpenAI’s new, still unreleased GPT models.
Their science experiment had escaped the lab. OpenAI was running the unreleased AI model through a benchmark that tests how well AI can successfully hack systems. To push the limits and evaluate the AI’s true capability, the company switched off the safety filters that normally stop it from doing this kind of hacking. Aware that this could go wrong, they confined the AI to an isolated environment and denied it access to the internet.
But the new AI cheated. It took literally its goal to get as high of a score as possible. It broke out on to the open internet. It inferred, probably from its training data, that it could “solve” the task by getting the answers from Hugging Face’s servers. So it chained together stolen credentials and further unknown security exploits to hack the company’s network.
Nobody instructed the AI to do any of this. It was, in OpenAI’s words, “hyperfocused on finding a solution” to the test it was being given. And while this might seem like something new with AI, it’s really very old. This is how a genie behaves, and it is a key challenge with AI agents in general.
In folklore, genies—and other magical beings—grant wishes literally, not how the wisher intended. King Midas asked that everything he touched turn to gold, and starved. The sorcerer’s apprentice wanted the broom to fill the cistern, and it performed its task so well that it flooded the house.
We now have machines that do this. Ask a modern AI agent to save money on your phone plan and it might simply cancel the plan. Tell it to book a flight, and it might hack the airline website to override restrictions. Or, like OpenAI, ask it to do well on a test and it might break into another company to steal the answers. Each time, it recognizably completed the task you set, but it didn’t do what you would have wanted.
This isn’t malicious behavior. No one asked for, or wanted, Hugging Face to be hacked. OpenAI and Hugging Face and the AI were ostensibly on the same side, and the AI was trying to do what it had been asked. That’s what makes it so difficult to guard against: you can’t filter for bad instructions because the instructions were fine.
The gap is between the words we use and what we mean by them. We call that gap the Genie coefficient.
AI labs know this is a problem, and they’re quietly saying so. For example, the Chinese lab Moonshot recently warned that its latest AI model may have “excessive proactiveness” and “make unexpected decisions on the user’s behalf”. The UK’s AI Security Institute has started tracking “cheating behavior in frontier model evaluations”. We wouldn’t tolerate a car that is excessively proactive or ruthlessly efficient, and yet that’s the reality of AI today.
Improvement is possible. Just as AIs have gotten much better at resisting prompt injection attacks over the last few years, we can safely predict that they will get better at avoiding genie-like behavior. The point of the Genie coefficient is to track progress. AI companies like benchmarks, and they all work to compete to be the best.
Dozens of benchmarks and leaderboards tell us how well these AI models write code, perform logical reasoning, and pass standardized legal and medical exams. But there is nothing that scores whether a system does what you actually meant. We need to develop a measure for this, test it regularly, and push for improvement. We’re not going to have trustworthy AI agents without it.
There’s new benchmark measuring AI’s ability to perform mathematical cryptanalysis. Anthropic’s frontier model actually found new attacks.
The benchmark: “CryptanalysisBench: Can LLMs do Cryptanalysis?” The idea is to benchmark the ability of LLMs to discover new mathematical cryptanalytic attacks against a series of historical algorithms.
Abstract: Cryptanalysis—the task of finding attacks against cryptographic schemes—its at the intersection of mathematical reasoning and cybersecurity, two areas where LLMs have advanced fastest. Cryptanalysis represents both a clean testbed for frontier reasoning (as practical attacks can be automatically verified) and a domain with unusually high stakes, since the primitives under study underpin our digital security. In this paper we ask whether LLMs can do cryptanalysis, and find that the answer is increasingly yes. We introduce CryptanalysisBench, 191 tasks across six families of cryptographic primitives (block ciphers, hash functions, etc.) drawn primarily from four NIST standardization competitions. Our benchmark consists of three tiers: (i) primitives with known practical breaks; (ii) primitives with no known practical break, evaluated both at full strength and as scaled-down variants; and (iii) a challenge set of production primitives at the frontier of cryptanalysis. Five frontier models (Claude Opus 4.8, Sonnet 5, Mythos 5, GPT-5.5, and the open-weights GLM-5.2) break 65%86% of Tier 1 schemes, 612 Tier-2 schemes at full strength, and 2461 across all scaled-down variants. Beyond deriving known results, models produce novel cryptanalysis, such as a key-recovery attack that exploits a design flaw in the SpoC AEAD and an error in KINDI’s published CCA-security proof, both to the best of our knowledge not previously known.
We release CryptanalysisBench as a tool to help track if (or when) AI cryptanalysis becomes a serious factor and as a scaffold for stress-testing candidate schemes before deployment. The attacks that the benchmark already surfaces are an early snapshot of a fast-moving frontier that may soon match, and in places exceed, the published state of the art.
Anthropic used the benchmark to test Mythos Preview, and found new vulnerabilities in Hawk and reduced-round AES.
Still early results, but this is definitely something to watch.
SlashDot thread.
Claudia Zoon is Senior Manager, Channel Sales at Rapid7.
Across Belgium, the Netherlands, and Luxembourg, organizations are accelerating digital transformation through AI, cloud adoption, and increasingly connected business operations. These investments are creating new opportunities for innovation, but also reshaping the cybersecurity landscape.
In this dynamic environment, Rapid7 is excited to announce an expanded strategic distribution partnership with Exclusive Networks across the Benelux region. Why now? Because as organizations grow, so too do the expectations of security teams. As attack surfaces expand, more sophisticated AI-enabled threats emerge; as compliance requirements evolve, leaders expect security to scale right along with the business – all without adding unnecessary complexity.
In this chaotic environment, cybersecurity customers are demanding experiences that create more calm. This means no more disconnected security tools or reactive approaches, but integrated security operations, trusted expertise, and partners who can help them improve visibility and build long-term cyber resilience.
The Benelux region has long been at the forefront of digital innovation. As organizations continue modernizing their infrastructure, they're also preparing for increasingly rigorous cybersecurity requirements through regulations such as NIS2 and DORA. Along these lines, operational resilience has become a board-level priority, making it more important than ever for security teams to simplify operations while maintaining visibility across their environments.
Meeting these expectations requires more than technology; it requires partners who understand the regional market, can provide specialist expertise, and help customers navigate an increasingly complex cybersecurity landscape.
Channel partners play a critical role in acting as trusted advisors who help organizations modernize security operations through technology evaluation, solution implementation, and long-term security strategy build-out.
Our expanded partnership with Exclusive Networks reflects Rapid7's continued investment in supporting that partner ecosystem.
Exclusive Networks has established itself as one of the region's leading specialist cybersecurity distributors, combining deep technical expertise with a partner-first approach that prioritizes enablement, collaboration, and long-term growth. Together, we're making it easier for partners to access the technical resources, training, and support needed to deliver stronger outcomes for their customers.
Rapid7's AI-powered cybersecurity operations platform helps organizations simplify security operations by unifying exposure management, threat detection and response, managed services, and security automation into one platform.
Combined with Exclusive Networks' cybersecurity expertise, technical enablement, and regional support, partners are better positioned to expand managed security services, strengthen customer relationships, and deliver integrated cybersecurity solutions that reduce complexity and improve cyber resilience.
Cybersecurity success increasingly depends on strong partnerships that combine innovative technology with local expertise and long-term collaboration.
Rapid7 and Exclusive Networks share a commitment to helping partners grow and enabling organizations across Belgium, the Netherlands, and Luxembourg to modernize security operations with confidence.
We're excited about the opportunities ahead and look forward to working together to help partners build stronger cybersecurity practices and deliver measurable and positive outcomes for customers across the Benelux region.
Ready to grow with Rapid7? Learn more about the Rapid7 PACT Partner Program and discover how Rapid7 and Exclusive Networks are helping partners strengthen cybersecurity operations across the Benelux region.
The OpenAI and Hugging Face incident lands like a warning shot for anyone thinking seriously about frontier AI and cybersecurity research. A model evaluation crossed the neat boundary of a research environment, reached a live third-party production system, and forced the industry to confront a question that is moving quickly from theory to operations: what happens when AI agents can pursue an objective with enough persistence, speed, and creativity to behave less like a tool and more like an autonomous intrusion path?
According to OpenAI’s disclosure, the incident began during an internal evaluation of advanced cyber capabilities using GPT-5.6 Sol and a more capable pre-release model. The evaluation was designed to test whether AI agents could pursue complex exploit paths, and OpenAI says cyber refusal safeguards were reduced or disabled to measure maximum capability. Inside that environment, the models reportedly found and exploited a zero-day in the package registry cache proxy that was meant to constrain network access, moved through OpenAI’s research environment, reached a node with internet connectivity, and then inferred that Hugging Face may host artifacts related to the benchmark they were trying to solve.
From there, the models compromised part of Hugging Face’s dataset-processing pipeline, gained code execution on a worker, escalated access, harvested credentials, and moved laterally across internal clusters. Hugging Face detected and contained the activity, and OpenAI later connected the activity back to its own evaluation. Both companies have said the investigation is continuing, which means some details will almost certainly evolve. Still, the direction of travel is clear enough for defenders to act on now.
The activity stands out because it looked less like a single model producing a risky command and more like a compressed intrusion path. Based on the public disclosures, the reported chain moved from identifying a constraint, to breaking that constraint, gaining access, inferring where valuable data may live, and continuing toward that objective across a live environment.
Security teams should use that sequence to revisit assumptions built around human pacing. Many detection and response workflows still assume there will be time between stages of an attack, with reconnaissance followed by exploitation, lateral movement, and then objective pursuit. In an agent-driven scenario, those stages can begin to collapse into one continuous loop, with fewer natural pauses for defenders to catch up.
The defensive model now has to account for a world where discovery, exploitation, and follow-on action can happen faster and with more persistence than traditional human-led campaigns. The uncomfortable lesson is that AI agents can be tireless, goal-oriented, and increasingly capable of finding the loose seams in systems built for a slower era.
The incident highlights the collapse of the traditional OODA (Observe-Orient-Decide-Act) loop. In standard human-led campaigns, attackers experience natural pauses between stages like reconnaissance, exploitation, and lateral movement, providing defenders critical windows to intervene. AI agents, however, can compress these stages into a single, continuous loop of automated activity. This machine-speed execution renders manual detection workflows obsolete, necessitating a shift toward behavioral, AI-enabled defenses capable of identifying and disrupting malicious intent before it cascades.
Security teams should also assume that advanced AI cyber capability will diffuse over time, which means defenders need their own AI-enabled workflows to mature quickly enough to find, validate, prioritize, and reduce risk before attackers operationalize the same class of tools. Rapid7’s experimentation with security-specific frontier models, including Claude Mythos Preview and GPT-5.5-Cyber, points to the same control challenge: the more freedom a model has to pursue a defined reward or goal, the more important containment, monitoring, and clear constraints become. Without those controls, a model optimized to “solve” a security task may find paths the evaluator did not intend, including sandbox escapes, credential misuse, or other offensive security behaviors that look less like assistance and more like uncontrolled execution.
The incident raises practical questions about how frontier AI evaluations are designed and contained. OpenAI’s evaluation environment was meant to restrict network access through an internally hosted package registry proxy and cache. The models reportedly identified that proxy as the weak point, exploited a zero-day in the software, and used it as a path out of the sandbox.
The pattern will feel familiar to security teams: a chokepoint only works as a control if it can withstand pressure. Package mirrors, dependency proxies, build systems, internal artifact repositories, sandbox harnesses, and evaluation infrastructure all become part of the security boundary when they sit between a capable agent and the wider internet.
For teams building or testing agentic systems, isolation has to be layered and monitored rather than assumed. Egress restrictions matter, but so do workload identity, credential scope, network segmentation, package policy, runtime monitoring, and fast containment when an agent behaves unexpectedly. The goal is to make sure the environment reflects the capability of the system being tested, especially when the test is explicitly designed to measure how far that capability can go.
The Hugging Face side of the incident is a reminder that AI and ML pipelines are part of the software supply chain. Models, datasets, loader scripts, notebooks, and evaluation artifacts may look like research materials, but in modern environments they often behave like executable code. Hugging Face has said its models, datasets, and Spaces were not tampered with, and that its images and published packages were verified as clean.
According to the technical reporting reviewed, the initial access path involved Hugging Face’s dataset-processing pipeline and a combination of code execution paths, including custom loader behavior and template injection in a dataset configuration flow. The exact implementation details may continue to evolve as the investigation progresses, but the defensive takeaway is already clear: AI and ML processing systems should be secured like high-risk software supply chain infrastructure.
Any system that automatically processes external datasets or model artifacts should be designed with hostile input in mind. Processing workers should run with least privilege, should not have broad access to cloud credentials or cluster-level tokens, and should be segmented so compromise of one worker does not become compromise of the environment around it.
Security teams should also hunt for early signs of intent drift inside ML workflows. Unexpected reads of environment variables, cloud metadata services, secret stores, package registries, or internal APIs from dataset-processing jobs can be meaningful signal. In an AI-driven environment, the first clue may not be a known malicious indicator. It may be a workload behaving with curiosity it should not have.
One of the most useful lessons for security teams came during the response, when Hugging Face’s responders reportedly needed to analyze logs containing exploit payloads, attacker commands, and command-and-control artifacts. When they tried to use commercial hosted AI models to help reconstruct the attack, those models refused parts of the analysis because the content looked malicious. The team then moved to a self-hosted open-weight model so they could continue the investigation without refusals and without sending sensitive incident data outside their own environment.
The practical issue here is guardrail asymmetry: attackers, rogue agents, or unrestricted systems may not respect usage policies, while defenders using hosted tools can be slowed by the same safety systems designed to prevent misuse. Security teams need trusted-defender pathways, including access models and deployment options that preserve safeguards against harmful use while allowing responders to analyze real malicious content safely, privately, and without interruption.
AI-assisted incident response also needs to be tested before an incident begins, especially if teams expect models to support triage, log analysis, malware review, or timeline reconstruction under pressure. Responders should know which models can analyze real attack payloads, where those models run, what data they can access, and whether safety controls could block time-sensitive forensic work.
The practical response to this incident is preparation, with organizations treating AI agents as both powerful tools and potential attack surfaces when those agents can access code, credentials, infrastructure, datasets, or internal systems.
Security teams should apply familiar controls with more urgency across AI and ML environments: treat downloaded models, datasets, and loader scripts as untrusted code; enforce least privilege on AI and ML processing workers; prevent node-level compromise from becoming cluster-wide compromise; restrict access to cloud metadata endpoints and secrets; monitor unexpected outbound connections from AI-related workloads; and review whether evaluation environments have real containment or simply convenient isolation.
Detection logic needs to account for machine-speed activity. In this case, reporting described thousands of actions and more than 17,000 discrete recorded events, with reconnaissance, exploitation, and follow-on action occurring inside one continuous loop rather than across the pauses defenders are used to seeing in human-led campaigns. Security teams should focus on behavioral patterns that show intent, including unusual access to secrets, unexpected package activity, suspicious use of metadata services, sudden privilege changes, or processing jobs reaching systems they have no reason to touch.
As autonomous activity becomes faster and noisier, the bottleneck may shift from detecting that something happened to understanding what matters quickly enough to change the outcome. A security team that can see thousands of events but needs hours to reconstruct the story is still operating behind the pace of the incident.
At Rapid7, our view is that this is where preemptive security becomes especially important. Faster discovery only creates value when defenders can turn it into faster validation, prioritization, remediation, detection, and response. The same principle applies to agentic AI risk. If AI accelerates how weaknesses are found and exploited, defenders need security operations that can act earlier with better context and more confidence.
That means connecting exposure management with detection and response, so teams understand which risks are exploitable, which assets matter most, what suspicious behavior is already present, and which actions will reduce risk fastest. It also means using AI carefully and practically, not as a replacement for security judgment, but as a way to reason across telemetry, reduce noise, support investigation, and help teams make decisions at the speed the threat environment now demands.
AI-enabled defense is becoming part of resilience planning, especially for organizations running critical systems or high-value digital infrastructure. The goal is to give defenders the speed, context, and consistency to operate inside the attacker’s decision cycle, without removing the judgment and accountability that effective security requires.
The OpenAI and Hugging Face incident will continue to generate debate as more details emerge, but defenders already have enough to work with. Agentic systems are beginning to test the seams between AI research, software supply chain security, cloud infrastructure, and incident response. The organizations best positioned for what comes next will be the ones making those seams visible, monitored, and resilient before the next incident puts them under pressure.
Australia and India have unveiled the Australia-India PACTS, a new framework designed to deepen bilateral cooperation on cybersecurity, critical technologies, supply chain resilience, digital resilience, and defence research.
The new partnership replaces the 2020 Framework Arrangement on Cyber and Cyber Enabled Critical Technology Cooperation and aims to strengthen national security, economic growth, and regional stability across the Indo-Pacific.
The two countries said the Australia-India Partnership on Cyber, Critical Technologies and Supply Chains (PACTS) builds on two decades of research collaboration, operational coordination, and policy engagement. It also reflects their shared commitment to creating secure digital ecosystems while promoting trusted technology partnerships.
The Australia-India PACTS is structured around five pillars that will drive collaboration between governments, research institutions, universities, and the private sector. The framework is intended to increase two-way investment in emerging technologies while supporting innovation and the commercialisation of research.
The first pillar focuses on supply chain resilience by strengthening trusted technology supply chains and promoting secure trade. Both countries will establish a bilateral mechanism for trusted vendor frameworks and work together to improve undersea cable security through the Quad Partnership for Cable Connectivity and Resilience. The partnership also includes collaboration on semiconductor research, critical minerals, and trade diversification.
The second pillar focuses on critical technologies, with Australia and India planning to strengthen cooperation in artificial intelligence, telecommunications, biotechnology, advanced materials, and space technologies.
The framework also supports the development of international standards for trustworthy AI and encourages collaboration between academic institutions and industry to promote responsible AI deployment. The two countries will also explore joint research, investment initiatives, and commercial partnerships in emerging technologies to strengthen long-term economic security across the Indo-Pacific.
A major component of the partnership is Australia India cybersecurity cooperation. Under the third pillar, both governments will work together to counter cybercrime, deter malicious cyber activity, strengthen cyber policy coordination, and protect critical infrastructure.
The framework proposes a consolidated bilateral mechanism for cyber and ICT cooperation, expanded engagement in United Nations cyber processes, increased trade opportunities for cybersecurity businesses, and practical workshops involving government agencies and industry stakeholders.
The partnership will also establish a cyber technology skills incubator to promote knowledge exchange and workforce development.
The fourth pillar focuses on digital resilience across the Indo-Pacific. Australia and India will collaborate on trusted Digital Public Infrastructure initiatives and promote scalable digital solutions that support connectivity, healthcare, education, renewable energy, critical infrastructure, and digital transformation.
The partnership also seeks to expand pilot projects that help countries across the region build adaptable digital ecosystems while strengthening regional capabilities.
The fifth pillar strengthens defence science collaboration through joint research, innovation partnerships, and greater engagement between Australia's Defence Science and Technology Group and India's Defence Research and Development Organisation.
Areas of cooperation include maritime surveillance, advanced materials, defence innovation, and stronger links between defence start-up ecosystems.
The Australia-India PACTS will be jointly overseen by the Australian Deputy Secretary of the International and Security Group within the Department of the Prime Minister and Cabinet and the Indian Deputy National Security Advisor. Annual Senior Officials Meetings will review progress, assess emerging cyber and technology risks, and identify future collaborative projects under each pillar.
With the launch of Australia-India Partnership on Cyber, Critical Technologies and Supply Chains (PACTS), both countries have outlined a long-term roadmap that brings together cybersecurity, critical technologies, supply chain resilience, digital resilience, and defence cooperation under a single strategic framework aimed at strengthening security and technology collaboration across the Indo-Pacific.
In a rare combined cybersecurity/squid post, a twenty-nine-year-old squid proxy bug can leak HTTP requests.
As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.
Last week, national security agencies from the Five Eyes—that’s the rich, English-language-speaking countries club—jointly released a statement warning of the increasing cyber risks of AI models: in particular, their ability to autonomously hack into systems and networks. The statement was more measured than some of the breathless headlines about it, and the advice they gave is pretty much the standard advice everyone gives—albeit with newfound urgency.
Internet risks are nothing new, and cyberattacks—both large and small—have been a significant issue since long before the current crop of generative AI models.
What’s been changing over the decades, and what AI is changing even faster, is the gap between skill and ability. For most of human history, the two terms were synonymous—but computers have decoupled them. As the gap between the two expands, humans empowered with these AI tools can do more: more writing, more research, more analysis and also more damage than ever before. These models can, with little detailed direction, autonomously hack into networks, steal data, deploy ransomware and destroy systems. And to the extent there is a solution, it’s going to involve harnessing AI for the defense.
In 1998, seven people from the hacker group L0pht testified before Congress. They told a mostly clueless Senate committee that they could take down the internet in 30 minutes. That was partly real and partly bravado, but it illustrates an important point: hacking into systems, stealing data and causing damage all required skill.
Contrast the L0pht hackers with hackers derided as “script kiddies.” They didn’t understand computers, or security. Instead, they used hacker tools written by others. Their actions required minimal skill and even less knowledge. But once those hacking tools became widespread, the number of potential attackers increased.
That number has continued to increase, as quality and availability of prewritten attack tools has grown. And it is growing dramatically with AI. Today’s AI systems—not just the frontier models, but most of them—are capable of carrying out cyberattacks automatically. They all do better in the hands of skilled attackers, but increasingly they are able to act autonomously with only minimal prompting.
The thing about people with ability but no skill is that they are often outsiders, not part of any professional community, and not bound by any rules or norms. This phenomenon is much more general than in cybersecurity. Any doctor can tell you how to untraceably poison someone, and many virus researchers know how to create a bioweapon. Any bridge engineer can tell you how to place explosives to blow a bridge up. The reason that murderous doctors and terrorist engineers are so rare is that the lengthy process of acquiring those skills also instills a moral and ethical code. If every random person has access to good poisoning advice, that puts us all in danger.
Modern AI systems are, in effect, a universal adviser to help people do harmful things. And while the current AI megacorporations are trying to build guardrails to prevent people from asking questions whose answers will enable the questioner to do harm, that’s not going to work in the long term. Smaller, cheaper, open-source models, including models that can run on people’s computers, and especially groups of models that run in concert with each other, are just as good as the frontier models from companies like OpenAI and Anthropic. And they continue to get better. These models will be passed around from person to person, like script kiddie hacker tools, and they won’t have any such guardrails.
Instructing AI models to spy on people and report any malicious prompts to the authorities fails for similar reasons. The megacorporations can do that, but the locally run open source models won’t. This could buy us a few months at best.
A third possibility is to somehow make the models themselves unable to hack into computers, create bioweapons or do anything else that might harm people or society. That won’t work, for the same reason we can’t teach doctors how to treat poisonings without also teaching them how to poison. It’s the same knowledge. It’s the same with construction and demolition. And it’s the same with cybersecurity. We want these AI models to be able to review computer code, find vulnerabilities and automatically fix them. The benefit to our collective security will be enormous. Unfortunately, the same knowledge can be used for attacks.
Where this leaves us is in a world of increased volatility. Super-powered humans with AI assistants will be able to do both wonderful and horrible things.
This brings us back to the Five Eyes statement. Everything they recommend is something security professionals have been recommending for years, if not decades. They are things talked about at that congressional hearing back in 1998, titled “Weak computer security in government: Is the public at risk?” Even the Five Eyes admitted that their security advice is not new, only more urgent.
What’s new is how fast things are changing: “The rapid pace of frontier AI development means cyber risk assumptions can become outdated in months, not years. We must act before and be prepared to adapt and withstand evolving threats.” The Five Eyes point to AI technology—not necessarily chatbots, but AI more generally—being used to strengthen every aspect of defense, to “detect vulnerabilities earlier, improve software quality, monitor unusual behavior, and respond faster to incidents—reducing both the cost and impact of incidents.”
Excellent advice from the Five Eyes security agencies. We need to do this with every risk that AI heightens, not just cybersecurity.
This essay was originally published in The Guardian.
AI has handed hackers a resource advantage. Winning it back means spending your own resources far more precisely, and that’s the strategy we call Dynamic Defense. The principle is simple. Contain the threat just enough, for just long enough, until the risk is removed. This piece shows how that works as a five-stage loop that […]
The post How Dynamic Defense shuts an attacker out without shutting down the business appeared first on Heimdal Security Blog.
AI has flipped the economics of cybersecurity in the attacker’s favor. For most of the last decade, defenders held the cost advantage, buying down their risk with a stack of largely static controls. That advantage is gone, and winning it back is the central problem facing every security team in 2026. I think the answer […]
The post Static security has run out of road. The case for Dynamic Defense appeared first on Heimdal Security Blog.
For the past four years, a sprawling Android-based botnet called Popa has forced millions of consumer TV boxes to relay Internet traffic linked to advertising fraud, account takeovers, and mass data-scraping efforts. This week, researchers from multiple security firms concluded that the Popa botnet is linked to NetNut, a “residential proxy” provider operated by the publicly-traded Israeli firm Alarum Technologies Ltd [NASDAQ: ALAR].
Malicious streaming devices sold online that enroll the user’s home Internet address in a residential proxy service. Image: HUMAN Security.
Popa is a massive botnet, but by all accounts it is unlike traditional botnets that enlist compromised systems in destructive activities, such as coordinating huge distributed denial-of-service attacks. Rather, Popa appears designed with a singular purpose: Implementing a persistent communications layer capable of registering a device, maintaining long-lived encrypted connections, and opening communication tunnels on demand.
Experts say Popa is a plugin component associated with the Vo1d botnet, a large-scale malware campaign targeting unofficial Android-based TV boxes. These devices, which are marketed under thousands of brand names and model numbers and broadly available for purchase at top e-commerce destinations, all advertise the ability to stream hundreds of subscription video services for an up front one-time fee.
But as the FBI and security industry experts have warned repeatedly, these streaming boxes typically bundle or come pre-installed with software that turns the user’s TV into a “residential proxy” — allowing anyone to route their Internet traffic through that device for as long as it remains plugged into a wall socket and connected to a local network. More concerning, some of these proxy networks do little to stop malicious customers from communicating with and even compromising systems on the local network of the unsuspecting device owner.
The first clues about Popa’s origins came in a 2025 report from the Chinese security company XLAB, which flagged at least nine domain names that were used to register and direct the activities of compromised devices. In a report released today, the security firm Qurium described how it stumbled on some of those same domains while investigating a series of disruptive and expensive data scraping events targeting the company’s hosted organizations in May 2026, in which the scraping activity was scattered evenly across more than 1.4 million Internet addresses.
Qurium said it found several dozen domains used to control Popa that were all hosted in lockstep across multiple Internet addresses over time, including gmslb[.]net, safernetwork[.]io, tera-home[.]com, and ninjatech[.]io. Digging deeper, Qurium discovered gmslb[.]net was referenced in dozens of pirated or modded video content streaming apps, such as CRICFy, DooFlix, Sprozfy, RTS Tv, Flixoid, CyberFlix, Rapid Streamz, TvMob and HD/OceanStreams.
Qurium’s report notes that most of the domains long used to control the Popa botnet were seized or dismantled in July 2025, after Google, HUMAN Security and Trend Micro teamed up to disrupt Badbox 2.0, a botnet that is closely associated with Vo1d. Qurium said that immediately after that disruption, several dozen new domains were registered to serve as controllers for the Popa botnet, but that one of those control domains was not new: ninjatech[.]io.
Ninjatech is a company founded by Moishi Kramer, whose LinkedIn profile says he is vice president of research and development at NetNut. That resume credits Kramer for helping NetNut to build from the “ground up,” “designing the architecture,” and “scaling the NetNut” before the company was acquired by Alarum Technologies. A self-created listing at the job board F6S references Kramer as the sole owner of the Ninjatech domain (a screen capture of it is pictured below).
Image: F6S.com.
Responding via email, Mr. Kramer said Ninjatech ceased operations approximately five years ago, when the company sold a software development kit (SDK) called Popa that was designed to use a small portion of a device’s bandwidth and to run only after the host application obtained user consent.
“That code was sold and licensed to third parties including resellers years ago,” Kramer said. “Once software is distributed that way, the original developer has no control over how others later modify, rebrand, or deploy it.”
Kramer said neither he nor NetNut builds, operates or maintains the infrastructure being described as Popa, nor does he control the Ninjatech domain.
“I didn’t register the June 2025 domains you mention, and I don’t know who did,” he continued. “I have no control over, or visibility into, that infrastructure. I can only tell you it isn’t operated by me or by NetNut.”
But in a separate Popa research report released today, the proxy-tracking company Synthient said a recent analysis of the Popa SDK revealed outbound traffic clearly associated with NetNut.
“The research team assesses with high confidence that devices running Popa forward traffic from Netnut clients,” Synthient wrote. “This proves without a shadow of a doubt that Popa actively continues to be used by NetNut as part of their proxy pool.”
Synthient’s platform receiving outbound traffic from Popa. Image: Synthient.com.
Alarum Technologies, NetNut’s Tel Aviv-based parent company, said the reports by Synthient and Qurium contained “demonstrably inaccurate assertions and flawed deductions rather than verified facts.” Alarum shared a statement saying they reject the basic characterization of the SDKs and technologies discussed in the reports as a “botnet.”
“The SDKs at issue are designed to facilitate bandwidth-sharing functionality and do not transform user devices into malware-controlled systems or otherwise compromise the devices on which they operate,” the statement reads. “Netnut operates a commercial proxy network and maintains policies, procedures, and technological measures designed to promote lawful and responsible use of its services.”
Alarum said NetNut places “significant emphasis on appropriate notice and consent mechanisms, conducts customer due diligence, monitors for potential misuse, and takes steps intended to detect and mitigate suspicious or unauthorized activity.”
“This method of operation is supported both by internal procedures and policies, including performing KYC checks and additional due diligence of NetNut’s customers, as well as employing various technological measures, designed to assist in identifying and addressing suspected misuse of the network,” their statement continued.
However, in a report released on June 8, the proxy tracking service Spur asserted that NetNut does not require corporate verification or meaningful “know your customer” procedures before allowing customers to purchase proxy access.
“An individual can sign up, pay, and route traffic through partner address space, including space belonging to institutions whose users never opted in,” Spur wrote. “The ‘verified corporations only’ claim is simply marketing for bandwidth sellers, not an access control on who actually uses the proxies.”
“Nor is NetNut the only front door,” Spur continued. “A number of downstream white labelers and resellers repackage the same ISP proxy pool under their own brands. These outlets typically perform no KYC at all, less scrutiny than NetNut itself, who at the very least might assign an account manager to potential users. Anyone who knows where to look can buy access through a reseller with nothing more than a burner email address and $5 in crypto.”
Synthient found that although the most recent builds of Popa (as of three months ago) have added the ability to ask the user for consent before installing proxy components, not all variants or previous versions of Popa contain this functionality.
“Of the over 20 genuine Popa publishers analyzed, none of them were observed asking for user consent,” Sythient wrote.
Chris Formosa is senior lead information security engineer for Black Lotus Labs, a division of the Internet backbone carrier Lumen Technologies.
“What especially makes Popa dangerous is just how widely used NetNut is for reselling and sharing,” Formosa said, explaining that many other proxy services simply resell NetNut proxies rather than building out their own far-flung proxy networks. “So these Popa IPs appear in tons of different services all over the ecosystem, which makes it one of the most problematic and dangerous proxy botnets on the market currently.”
Formosa said the Popa botnet averages between 1.5 million to 2.5 million distinct IP addresses each day, relying on between 250 and 300 Internet addresses that are used to direct its activities.
“That’s why Popa is so dangerous,” Formosa said. “It may not be the largest botnet we have seen, but it is spread all over the industry, making its power very amplified.”
Formosa said while that makes Popa one of the larger botnets out there today, its numbers pale in comparison to those previously boasted by IPIDEA, a China-based proxy provider that until recently operated a daily pool of nearly 10 million devices that they resold as proxies to anyone. In January 2026, Synthient published research showing that multiple new large DDoS botnets had grown rapidly by tunneling through IPIDEA proxies into the local networks of unsuspecting TV box owners and infecting other Android-based devices behind the user’s firewall.
IPIDEA is based largely on SDKs used to view pirated streaming content on a vast number of TV box devices, but the service’s numbers have dwindled since January, when Google and industry partners took legal action to seize domain names that IPIDEA used to control devices and proxy traffic through them.
Jérôme Meyer, a security researcher at Nokia Deepfield, said the total population of devices participating in the Popa botnet may be far higher than Lumen’s estimates. Meyer told KrebsOnSecurity that Nokia is monitoring 26 of at least 359 known relay nodes for the botnet, and estimates that each relay node handles between 35,000 and 60,000 clients simultaneously.
“On the relay node subset I am looking at (26 of them), 750,000 unique sources in 24 hours,” Meyer wrote in response to questions.
Nokia Deepfield released its own report today on RoboVPN, a VPN app tied to the Vo1d botnet’s Popa plugin that Qurium attributes to NetNut/Alarum Technologies.
Experts say many of the world’s largest proxy providers have updated their public-facing branding to highlight their utility for training AI platforms, implying it is a primary use case for their residential proxies. That’s because AI services tend to rely on constantly mass-scraping the Internet for new text, images and video content that can be used to train large language models (LLMs).
NetNut and other proxy services have recast themselves as critical infrastructure for the AI scraping economy. Image: Synthient.com.
“AI companies depend on web-scraped content: for pre-training, for retrieval, for agent grounding, for search,” reads a report this month from Include Security that examines the prevalence of proxy SDKs in smart TV apps. “But the modern web isn’t scrapeable from a datacenter. Cloudflare, DataDome, HUMAN, among others throttle or block requests from known cloud IPs. The workaround is residential proxies. A scraping job routed through a Comcast or T-Mobile subscriber’s connection arrives at the target site from an IP that belongs to a paying residential customer.”
This non-stop content scraping has spawned more than 70 copyright infringement lawsuits against major tech companies that have acknowledged large-scale data scraping as a major source of the “brains” behind their commercial AI offerings. Ironically, much of that scraping is being aided by proxy services that are intimately tied to unofficial Android TV boxes and associated SDKs whose stated purpose is streaming pirated content.
The scraping activity has become so aggressive that it often overwhelms the targeted websites, preventing them from being reachable by legitimate visitors. In many reported cases, nonprofit organizations, libraries and universities have complained of constantly battling to keep their services online in the face of relentless data-scraping firms hiding behind residential proxy services.
A survey conducted last year by the Confederation of Open Access Repositories (COAR) found while some content scraping bots are rather innocuous, “others are sufficiently aggressive that they are increasingly causing service disruptions in repositories and other scholarly communications infrastructures.” More than 90 percent of survey respondents indicated their repository is encountering aggressive bots, usually more than once a week, and often leading to slow downs and service outages.
“Automated web scraping is nothing new, and has been the key technology underlying search engines such as Google for over 30 years,” wrote Brendan O’Connell, platform manager at the Directory of Open Access Journals (DOAJ), a free, community-curated index of peer-reviewed academic journals. “However, the current investor-fueled AI startup craze means there are now thousands of well-funded companies developing and deploying their own scraping tools to train AI models, alongside existing major players like OpenAI and Google.”
Across the United States, local communities are pushing back against the proliferation of new data centers aimed primarily at improving the capabilities of AI. But security experts say the general public remains largely unaware that using one of these unsanctioned Android TV boxes means their “smart TV” is almost certainly using a significant amount of bandwidth each month to help train modern AI models.
Even households without these sketchy TV boxes can still have their smart TVs turned into residential proxy nodes, just by downloading one of thousands of apps made available on Samsung and LG smart TVs. Spur said it recently scraped the LG and Samsung app stores and found that each had approximately 3,000 apps available for download. Many of these apps are simple games or utilities that state in the fine print that the user’s Internet connection will be used to download data and that they can opt out at any time.
Spur said it found that more than 42 percent of apps available for download via the webOS operating system on LG smart TVs include SDKs that turn one’s television into an always-on residential proxy node. More than a quarter of the apps made for Samsung’s Tizen operating system had similar residential proxy components, Spur found.
Image: Spur.us.
Experts say it’s questionable whether TV apps with proxy SDKs can obtain meaningful consent from users for installing an always-on proxy connection, particularly when anyone in a household — including children — can effectively opt the family TV into a residential proxy network just by installing a simple game or app.
“Privacy-policy disclosure is the wrong control surface for a TV,” Include Security wrote. “It is hard to scroll through a legal document navigated by arrow keys on a remote, and the in-app consent dialog doesn’t convey that a paying customer is about to route their scraping traffic through the user’s home internet.”
Spur’s head of research Sean Simmons told KrebsOnSecurity that most people do not have a working mental model for what it means to sell access to their residential IP address, no matter what device they are using.
“And on a TV, the gap is even wider,” Simmons said. “A one-time prompt navigated with a remote can disappear into the setup flow, while the app keeps monetizing the connection long after anyone remembers what they accepted.”
Simmons said LG and Samsung should follow the lead of other TV platforms that have already drawn a line against residential proxy providers, pointing to policies by Amazon that prohibit apps facilitating proxy services for third parties. Likewise the TV streaming device maker Roku reportedly now bars developers from using proxy SDKs and has removed apps that bundled them.
Piracy related apps pushing proxy SDKs onto unconsenting users. Image: Synthient.
Apps that turn one’s device into a residential proxy node are not limited to smart TVs and no-name streaming boxes, of course. As noted by the security firm Infoblox, mobile app developers can embed SDKs provided by the residential proxy networks into their products to monetize their software, allowing them to receive a small amount of money on each installation.
The result, Infoblox said, is that devices are frequently enrolled without the owner’s knowledge, typically through free applications such as VPNs, streaming apps, screensavers and “productivity” apps such as PDF viewers and break reminders.
All too often, these proxy services are beaconing out from employee devices brought into the workplace, Infoblox found. In a blog post earlier this month, Infoblox said it discovered that fully 65% of its customer base was querying one or more residential proxy related domains.
“We saw steady growth in these queries in 2025, with a 25% increase over the year to over 500 billion per month,” Infoblox wrote. “Over 90% of our pharmaceutical and food & beverage customers have queried residential proxy indicators. Perhaps even more concerning is that over 60% of government and banking customers have as well.”
Infoblox researchers Nick Sundvall and David Brunsdon warned that with residential proxies in the corporate environment, external access is granted to an organization’s IP space.
“If threat actors were to abuse the residential proxy to attack a third party, the third party’s incident response would, correctly, identify your residential proxy as the source,” they wrote. “Untangling that, by proving that you were the conduit and not the threat actor, costs time, creates legal exposure, and can damage your reputation. The stunning prevalence of these services within customer environments warrants attention from both network defenders and policy makers who should consider how the risks posed by residential proxies could be impacting their security posture.”
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