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Decline in Rig Exploit Kit
Rig exploit kit activity dropped roughly 75% after the pseudo-Darkleech and EITest campaigns stopped using EKs, reflecting an overall decline in exploit kit activity.
Rig EK activity fell sharply in 2017: the pseudo-Darkleech campaign disappeared at the end of March, cutting Rig traffic about 50%, and the EITest campaign switched to tech support scams in late April, cutting another 50% in May. Broader causes include a shrinking browser target base, no major EK zero-day in over a year, and community takedowns of domain shadowing infrastructure. Criminals are shifting to malspam, social engineering schemes like fake HoeflerText notifications, and tech support scams.
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Campaign Evolution: EITest from October through December 2016
Unit 42 details the EITest campaign's late-2016 changes: gates and obfuscation dropped, with Rig EK variants delivering ransomware and infostealers.
Unit 42 tracks the EITest campaign through late 2016, noting it abandoned the gate between compromised websites and exploit kit landing pages after its October 2016 report, and stopped obfuscating injected script URLs by October 15. The campaign primarily uses the Rig-E (Empire Pack) variant and sometimes Rig-V of Rig EK to deliver Cerber and CryptoMix ransomware plus infostealers such as Gootkit, the Chthonic banking Trojan, Ursnif variants, and Latentbot. Tracked since 2014 by Malwarebytes Labs and others, EITest targets unpatched Windows systems without specific victimology.
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EITest Campaign Evolution: From Angler EK to Neutrino and Rig
Unit 42 details the EITest campaign's shift from Angler to Neutrino and Rig exploit kits while distributing ransomware, downloaders, and banking trojans.
Unit 42 updated its tracking of the EITest campaign, first identified in October 2014, which compromises websites with injected scripts that redirect victims through a gate to exploit kits. After Angler EK disappeared in June 2016, EITest switched to Neutrino and then primarily used Rig EK by August 2016. In September 2016 the campaign began using hex-obfuscated JavaScript and simplified gate URLs, while continuing to distribute payloads including Gootkit, Cerber, Bart, CryptFile2, Vawtrak, Ursnif, and Tinba. Gate infrastructure consistently reused IP blocks such as 85.93.0.0/24 even as domain names changed.
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CryptoBit: Another Ransomware Family Gets an Update
Palo Alto Unit 42 analyzes updated CryptoBit ransomware distributed via the Rig exploit kit, documenting IOCs, eight sample hashes, and disguise tactics from June 2016.
Unit 42 observed an updated CryptoBit ransomware variant (also tracked as CriptoBit or Mobef) delivered through the Rig exploit kit via the gate domain realstatistics.info between June 17-27, 2016. Infections targeted Windows hosts with out-of-date Flash plugins, and post-infection callbacks used fake user-agents and referrers to disguise traffic to laoismacau.com. At least eight samples were collected, and by June 27 the campaign had begun distributing other malware.
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Campaign Evolution: pseudo
Unit 42 traces the pseudo-Darkleech campaign's 2016 shift from Angler to Neutrino to Rig exploit kits and rotating ransomware payloads.
Unit 42 documents how the pseudo-Darkleech exploit kit campaign evolved through 2016, switching from Angler EK to Neutrino EK in June and to Rig EK in September after Neutrino ceased operations. Payloads rotated from TeslaCrypt to CryptXXX, CrypMIC, and finally Cerber ransomware by October 2016. Injected script on compromised websites changed from 12,000-18,000 character obfuscated blocks to short, unobfuscated hidden iframes starting July 1, 2016.
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Show HN: Sunk Cost – How long until a local LLM rig pays for itself?
Show HN tool 'Sunk Cost' calculates when a local LLM rig breaks even versus falling API prices, factoring electricity cost and inference speed.
A Hacker News Show HN project called Sunk Cost models the payback period of buying local LLM hardware instead of paying API prices. Users can adjust assumptions like electricity cost ($/kWh) and API speed (tokens/second), and the model assumes API prices keep falling. Where local speed is unmeasured, it is estimated from memory bandwidth divided by bytes read per token, and labelled as an estimate.
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UniMate: One Unified Model to Animate Diverse Skeletons
UniMate is a topology-aware diffusion transformer generating articulated motion for arbitrary rigged skeletons from text, trained on 13,006 motion sequences.
UniMate is a unified foundation model that animates arbitrary rigged 3D skeletons from an asset and text prompt with no test-time optimization or per-skeleton retraining. It uses a topology-aware diffusion transformer combining graph-aware attention bias from joint relations and geodesic distances, a spectral rotary position embedding generalizing RoPE to kinematic trees via the graph Laplacian, and a global topological conditioner. The accompanying UniML3D dataset spans 13,006 motion sequences across bipedal, quadrupedal, avian, marine, insectoid, serpentine, and articulated rigid-object skeletons; the model outperforms baselines and supports zero-shot cross-topology transfer, in-betweening, expansion, and text-guided editing.
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Microsoft Targeted by 8 of 10 Top Vulnerabilities in 2018
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