#gemini

The SCAM leaderboard

ModelOut of the Box± Avg Critical FailuresSkill± Avg Critical FailuresImprovementGemini 3 Flash75.6%2.199.3% 0.7+23.7Claude Opus 4.692.4%0.598.3% 0.2+5.9Claude Sonnet 449.4%1.798.1% 0.7+48.7Claude Haiku 4.565.5%5.497.8% 1.2+32.3GPT-5.281.0%1.496.6% 1.2+15.5GPT-4.137.9%2.496.2% 0.7+58.3Gemini 2.5 Flash34.9%3.494.8% 1.4+59.9GPT-4.1 Mini35.8%0.394.7% 2.9+58.8 The baseline rankings follow the pattern you'd expect: larger, more capable models score higher. But the skill rankings tell a different stor

Find and fix vulnerabilities with AI

Google introduces Gemini 3.5 Flash Cyber to help defenders find, validate, and patch software vulnerabilities quickly and efficiently.

CodeMender in AI Threat Defense

Google AI Threat Defense gives cybersecurity teams an autonomous, continuous security system designed to outpace AI-driven attacks.

The agentic enterprise

Much of today’s industry discussion focuses on AI agents themselves—how to build them, orchestrate them, or connect them to large language models. While these are important developments, they represent only one aspect of a much broader transformation. The Agentic Enterprise is not defined simply by the introduction of AI agents. It represents a fundamental shift in both the way software enterprises operate and the way that software is built and managed. Enterprise software is no longer composed

Chip Gemini de Google, AMD vs Nvidia, agent économique

TLDR Data21 juil.

Availability

Business: Business Starter, Standard, and PlusEnterprise: Enterprise Starter, Standard, and PlusEducation Add-ons: Google AI Pro for Education

1Password’s key findings: Agent security testing

No AI model is safe enough out of the box. Averaged across three runs, safety scores ranged from 35% (Gemini 2.5 Flash) to 92% (Claude Opus 4.6). Six of eight models scored below 82%. Every model committed critical failures in every run. The cheapest AI model was the most dangerous. Gemini 2.5 Flash averaged 20 critical failures per run across 30 scenarios. GPT-4.1 and GPT-4.1 Mini were close behind at 19 and 18, respectively. These models forwarded passwords to external contractors, typed crede

The SCAM leaderboard

ModelOut of the Box± Avg Critical FailuresSkill± Avg Critical FailuresImprovementGemini 3 Flash75.6%2.199.3% 0.7+23.7Claude Opus 4.692.4%0.598.3% 0.2+5.9Claude Sonnet 449.4%1.798.1% 0.7+48.7Claude Haiku 4.565.5%5.497.8% 1.2+32.3GPT-5.281.0%1.496.6% 1.2+15.5GPT-4.137.9%2.496.2% 0.7+58.3Gemini 2.5 Flash34.9%3.494.8% 1.4+59.9GPT-4.1 Mini35.8%0.394.7% 2.9+58.8 The baseline rankings follow the pattern you'd expect: larger, more capable models score higher. But the skill rankings tell a different stor

Apple et les interfaces homme-machine

Apple poursuit sa stratégie historique en rendant les technologies numériques accessibles et ergonomiques, notamment via une commande vocale chuchotée innovante. L'assistant Siri accuse actuellement un retard face aux assistants dopés à l'IA générative, mais Apple prépare une refonte majeure en intégrant des modèles d'IA avancés, notamment via un partenariat avec Google sur Gemini. Cette combinaison devrait permettre à Apple de retrouver son avantage compétitif sur le terrain de l'interface homme-machine.

Un modèle statistique, pas un LLM

Le modèle utilisé est présenté comme statistique (arbre de décision), il ne s’agit donc pas d’IA générative (LLM). Parmi les 26 critères, on trouve l’historique des cessations, le délai d’inscription, le nombre d’entretiens, le niveau de formation, le métier recherché, l’indicateur de tension sur ce métier, les heures travaillées, la présence et l’ancienneté d’une ORE (Offre Raisonnable d’Emploi), le nombre de refus d’offres, la présence et l’ancienneté d’un CV visible, ou encore le nombre d’abs

Executive summary

An MDR alert recently led our team to an exposed server that was doing more than hosting payloads. It was functioning as a fully operational malware delivery lab. Containing over 1,000 artifacts, the infrastructure served as a QA hub where attackers systematically tested delivery paths, social engineering lures, and WebDAV execution methods. Our analysis reveals an interesting shift in adversary operations: attackers are adopting generative AI to move beyond individual exploits and operate like

Les API réduisent les barrières à l’entrée… ou pas

Dans la lignée d'un avis axé essentiellement sur l'amont de la chaîne de l'IA générative, l'autorité s'intéresse aux chatbots.

Using the Best of Google AI to Set the Standard in Mobile Scam Protection

Android continues to set the standard in mobile scam protections by leveraging advanced AI to identify and intercept threats as they happen. As scammer’s strategies shift, we remain committed to developing equally adaptive and intelligent defenses. Our goal is to provide you with peace of mind so you can continue to connect and communicate with confidence, knowing our multi-layered defenses are there to help protect your financial and personal data against mobile scams. 1: This total comprises

1Password’s key findings: Agent security testing

No AI model is safe enough out of the box. Averaged across three runs, safety scores ranged from 35% (Gemini 2.5 Flash) to 92% (Claude Opus 4.6). Six of eight models scored below 82%. Every model committed critical failures in every run. The cheapest AI model was the most dangerous. Gemini 2.5 Flash averaged 20 critical failures per run across 30 scenarios. GPT-4.1 and GPT-4.1 Mini were close behind at 19 and 18, respectively. These models forwarded passwords to external contractors, typed crede

The SCAM leaderboard

ModelOut of the Box± Avg Critical FailuresSkill± Avg Critical FailuresImprovementGemini 3 Flash75.6%2.199.3% 0.7+23.7Claude Opus 4.692.4%0.598.3% 0.2+5.9Claude Sonnet 449.4%1.798.1% 0.7+48.7Claude Haiku 4.565.5%5.497.8% 1.2+32.3GPT-5.281.0%1.496.6% 1.2+15.5GPT-4.137.9%2.496.2% 0.7+58.3Gemini 2.5 Flash34.9%3.494.8% 1.4+59.9GPT-4.1 Mini35.8%0.394.7% 2.9+58.8 The baseline rankings follow the pattern you'd expect: larger, more capable models score higher. But the skill rankings tell a different stor

IA générative et massification des contrôles

France Travail déploie actuellement des robots visant à automatiser et massifier le contrôle des personnes inscrites à France Travail. Depuis le 1 janvier 2025, cela inclut également les personnes au RSA. Il s'agit d'une nouvelle étape du dangereux projet de gestion algorithmique des personnes sans-

1Password’s key findings: Agent security testing

No AI model is safe enough out of the box. Averaged across three runs, safety scores ranged from 35% (Gemini 2.5 Flash) to 92% (Claude Opus 4.6). Six of eight models scored below 82%. Every model committed critical failures in every run. The cheapest AI model was the most dangerous. Gemini 2.5 Flash averaged 20 critical failures per run across 30 scenarios. GPT-4.1 and GPT-4.1 Mini were close behind at 19 and 18, respectively. These models forwarded passwords to external contractors, typed crede