Sun.Jul 24, 2022

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A database containing data of 5.4 million Twitter accounts available for sale

Security Affairs

Threat actor leaked data of 5.4 million Twitter users that were obtained by exploiting a now patched flaw in the popular platform. A threat actor has leaked data of 5.4 million Twitter accounts that were obtained by exploiting a now-fixed vulnerability in the popular social media platform. The threat actor is now offering for sale the stolen data on a the popular hacking forum Breached Forums.

Sales 133
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How to Safely Lend Someone Else Your Phone

WIRED Threat Level

The next time someone wants to borrow your device to make a call or take a picture, take these steps to protect your privacy.

Privacy 96
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Is APT28 behind the STIFF#BIZON attacks attributed to North Korea-linked APT37?

Security Affairs

North Korea-linked APT37 group targets high-value organizations in the Czech Republic, Poland, and other countries. Researchers from the Securonix Threat Research (STR) team have uncovered a new attack campaign, tracked as STIFF#BIZON, targeting high-value organizations in multiple countries, including Czech Republic, and Poland. The researchers attribute this campaign to the North Korea-linked APT37 group, aka Ricochet Chollima.

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Security Affairs newsletter Round 375 by Pierluigi Paganini

Security Affairs

A new round of the weekly Security Affairs newsletter arrived! Every week the best security articles from Security Affairs for free in your email box. If you want to also receive for free the newsletter with the international press subscribe here. FBI seized $500,000 worth of bitcoin obtained from Maui ransomware attacks SonicWall fixed critical SQLi in Analytics and GMS products Account lockout policy in Windows 11 is enabled by default to block brute force attacks Hackers breached Ukrainian r

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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.