Inside Keitaro Abuse Part 2: One Platform, Many Threats
This analysis examines how threat actors abuse Keitaro, an advertising performance tracker, for various malicious purposes. The report covers a wide range of threats, including malware delivery, phishing, scams, and illegal content distribution. Key findings include the use of Keitaro for cloaking and traffic distribution in malvertising campaigns, spam operations leveraging Keitaro for cryptocurrency wallet draining, and the abuse of Keitaro in investment scams. The report also highlights specific threat actors and their tactics, such as domain hijacking for adult content delivery and the use of fake arrests as clickbait for investment scams. Overall, the analysis demonstrates how Keitaro's features make it attractive to cybercriminals seeking to maximize their reach with minimal effort.
Pulse ID: 69c643d531ed0d8ae740f7dc
Pulse Link: https://otx.alienvault.com/pulse/69c643d531ed0d8ae740f7dc
Pulse Author: AlienVault
Created: 2026-03-27 08:46:13
Be advised, this data is unverified and should be considered preliminary. Always do further verification.
#CyberSecurity #ICS #InfoSec #Malvertising #Malware #Nim #OTX #OpenThreatExchange #Phishing #RAT #Spam #bot #cryptocurrency #AlienVault
13-Mar-2026
#AI’s #gamePlaying still has flaws: #AlphaZero-style self-play tested on #Nim
Despite heavy training, agents show blind spots and can miss optimal moves

Games are often called the ‘Formula 1’ of AI: clear rules, clear winners. AlphaZero-style algorithms learn by self-play: a neural network predicts moves and guides tree search. We tested this recipe on Nim, a simple children’s matchstick game that has been mathematically solved. Because the correct move is known for every position, we can measure whether an agent plays optimally across the state space. We find a gap: learning can work on small boards, but blind spots remain and performance degrades as the board grows, with predictions approaching random. This suggests impartial games often need analytic representations, not pattern learning.
NVIDIA AI Developer (@NVIDIAAIDev)
Nemotron 3 Super가 워크스테이션부터 클라우드까지 다양한 환경에 배포 지원되며 API, OpenRouter, build.nvidia.com 경유로 접근 가능하다는 공지입니다. 주요 추론(inference) 플랫폼에서 NVIDIA NIM 패키지로 제공되어 배포와 사용이 용이해졌습니다.

@openclaw @perplexity_ai Ready to get started? Nemotron 3 Super supports deployment across environments, from workstations to the cloud, and can be accessed through API, OpenRouter, or https://t.co/fC1rz1G9c4. It is now live and available on major inference platforms, packaged as NVIDIA NIM: 📥