Sun.Apr 17, 2022

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Enemybot, a new DDoS botnet appears in the threat landscape

Security Affairs

Enemybot is a DDoS botnet that targeted several routers and web servers by exploiting known vulnerabilities. Researchers from Fortinet discovered a new DDoS botnet, tracked as Enemybot, that has targeted several routers and web servers by exploiting known vulnerabilities. The botnet targets multiple architectures, including arm, bsd, x64, and x86. The researchers attribute the botnet to the cybercrime group Keksec which focuses on DDoS-based extortion.

CMS 126
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How to Limit Who Can Contact You on Instagram

WIRED Threat Level

It’s your account—you decide who’s allowed to see your vacation photos or slide into your DMs.

Privacy 70
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Stolen OAuth tokens used to download data from dozens of organizations, GitHub warns

Security Affairs

GitHub reported that threat actors used stolen OAuth user tokens to exfiltrate private data from several organizations. GitHub uncovered threat actors using stolen OAuth user tokens to gain access to their repositories and download private data from several organizations. Threat actors abused stolen OAuth user tokens issued to two third-party OAuth integrators, Heroku and Travis-CI, to download data from dozens of organizations, including npm.

Access 96
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Security Affairs newsletter Round 361 by Pierluigi Paganini

Security Affairs

A new round of the weekly Security Affairs newsletter arrived! Every week the best security articles from Security Affairs free for you in your email box. If you want to also receive for free the newsletter with the international press subscribe here. U.S. Gov believes North Korea-linked Lazarus APT is behind Ronin Validator cyber heist The unceasing action of Anonymous against Russia Threat actors target the Ukrainian gov with IcedID malware Threat actors use Zimbra exploits to target organizat

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.