All news with #ai security tag

⚠️ Google’s Threat Intelligence Group (GTIG) says the North Korea-linked actor UNC2970 and other state-aligned groups abused Gemini for target profiling, reconnaissance, and campaign planning. GTIG found use cases ranging from synthesizing OSINT and crafting tailored phishing personas to automating vulnerability analysis and debugging exploit code. Researchers identified malware such as HONESTCUE, which queries Gemini’s API to generate C# stage-two loaders compiled in memory, and an AI-built phishing kit called COINBAIT. Google also reported and mitigated large-scale model extraction activity aimed at replicating Gemini’s behavior.

🛡️ Google Threat Intelligence Group (GTIG) reports rising adversarial use of AI in Q4 2025, including widespread model extraction, AI-augmented reconnaissance, social engineering, and trials of agentic tooling. GTIG and Google DeepMind detected and mitigated numerous extraction attempts, protected internal reasoning traces, and disabled abusive assets in real time. The update describes AI-enabled proofs-of-concept (for example HONESTCUE and COINBAIT), abuses of shareable chat outputs, underground proxy toolkits, and published IOCs to support defenders.

🔒 In the 100th episode of the Threat Vector podcast, Nikesh Arora warns that the biggest risk from AI is organizational: teams rush to deploy models and treat security as an afterthought. He describes leaders jerry-rigging controls while massive infrastructure and energy spend accelerates adoption. Arora urges building security in from day one with platform-level visibility and real-time detection rather than bolting it on later.

⚠️ OpenClaw is a rapidly adopted local agent orchestration tool (formerly Clawdbot/Moltbot) that integrates with chat apps, operating systems, smart-home devices, browsers and productivity platforms and can be configured to use any LLM backend. Its GitHub repo and the Moltbook social layer saw millions of visits and hundreds of thousands of agents and downloads in recent weeks. Security researchers warn the tool is insecure-by-default: exposed instances, authentication bypasses, plaintext credentials and malicious third-party skills create serious enterprise risk. Organizations are advised to block traffic, rotate credentials and restrict experimentation to isolated, managed environments.

🤖 In episode 454 of the Smashing Security podcast Graham Cluley and guest Iain Thomson examine the Moltbook saga — an AI-only social network that sparked doomsday talk but largely reflected humans role-playing as bots. They also warn that “vibe coding” can be a dangerous design choice when security researchers can easily peek into private messages, API keys and databases. The show touches on pro-Russian hacker activity around the Winter Olympics and cites reporting from Forbes, Wired, Reuters, The Record and the BBC.

🛡️ Google Cloud outlines an AI-driven approach to operational resilience for financial institutions, using Gemini Enterprise to generate context-aware incident scenarios based on a customer's real production data. The Technical Account Management team ingests logs, architecture, SLAs and support history to craft bespoke timelines that test cross-functional response and communication. The program supports DORA readiness and has driven immediate remediation actions and process changes.

🔍 The Strategic SIEM Buyer’s Guide recommends that security leaders replace fragmented toolchains with a unified, cloud‑native platform that makes it inexpensive to ingest and retain telemetry, automatically shapes data into analysis‑ready form, and enriches it with graph‑driven intelligence. It highlights accelerating detection and response through real‑time correlation, automated investigation, and adaptive orchestration so analysts and AI can act faster. The guide also stresses rapid time‑to‑value via prebuilt connectors and turnkey content, and cites Microsoft Sentinel as an example of an AI‑ready end‑to‑end platform.

🤖 AI is now central to cybersecurity strategies, accelerating detection and automation while also enabling more sophisticated attacks. The 2025 Global Cybersecurity Skills Gap report finds 97% of organizations use or plan to use AI, but 48% cite lack of AI expertise as their biggest implementation challenge. Organizations must pair AI tooling with human oversight, training, and validation to avoid misconfiguration and false confidence. Fortinet highlights training and certifications to help close the gap.

⚠️ New research introduces CHAI, a prompt-injection technique that embeds deceptive natural-language instructions into visual inputs to hijack embodied AI agents. The method systematically searches token space, builds prompt dictionaries, and crafts Visual Attack Prompts to mislead LVLM-powered systems. Experiments on drones, autonomous driving stacks, aerial tracking, and a real robotic vehicle show CHAI outperforms prior attacks and highlights the limits of conventional adversarial robustness.

🔐 Fortinet and UC Berkeley's CLTC led the third AI-enabled cybercrime tabletop, Operation Black Ice, to test governance and executive decision-making under compressed timelines. The exercise showed AI accelerates impersonation and extortion, turning trust dependencies into primary attack surfaces. Key lessons: identity verification must be multi-channel, third-party disclosures must be predefined, and ransom choices require rehearsed coordination rather than improvisation.

☁️This article introduces a pre-built Tines workflow—Investigate AWS issues with CLI data using agents—that brings AWS CLI output directly into cases, removing repetitive console logins and syntax guesswork. A lightweight, read-only agent executes context-aware CLI commands and returns results safely to the workflow. Optional AI-driven formatting or Tines transformations convert dense JSON into concise, human-readable summaries. The template can be imported, connected to an AWS credential, customized, tested, and will append findings into Tines Cases for auditability and team collaboration.

⚠️ Check Point Research reports a global increase in cyber attacks in January 2026, with organizations experiencing an average of 2,090 attacks per organization per week — a 3% increase from December and 17% above January 2025. The rise is driven by expanding ransomware operations and mounting data‑exposure risks linked to widespread GenAI adoption. Critical sectors are under intensified pressure as threat activity accelerates and adversaries move faster.

🔐 This week's briefing highlights attackers abusing trust across AI agents, update channels, and developer ecosystems. OpenClaw announced a partnership with VirusTotal to scan ClawHub skills after researchers discovered malicious packages and explosive typosquatting growth. High‑impact incidents include a 31.4 Tbps AISURU DDoS, a Notepad++ updater compromise delivering the Chrysalis backdoor, and an RCE in Docker's Ask Gordon AI assistant. Security teams should prioritize update integrity, supply‑chain controls, and agentic AI hygiene.

🔒 OpenClaw has integrated VirusTotal malware scanning into its ClawHub skills marketplace to automatically vet published skills. Packages are hashed and analyzed with Code Insight (powered by Gemini); benign skills are auto-approved, suspicious ones receive warnings, and confirmed malicious skills are blocked and re-scanned daily. The move responds to documented malicious extensions and unauthorized enterprise deployments, though OpenClaw stresses scanning is not a complete defense against prompt injection or logic abuse.

🛡️ Infinity Global Services reports a clear shift in cybersecurity training procurement from 2023 to 2025, with organizations moving away from individual course purchases toward team-based subscription models. Technical expertise remains essential, but the rise of AI-driven threats is driving demand for collective, SOC-wide training approaches. The data indicates a 33% decline in solo purchases and a marked increase in squad-level subscriptions, signaling a strategic pivot to collaborative workforce development.

⚠️ Researchers at Sysdig uncovered an attack that fully compromised an AWS environment in under eight minutes by exploiting a cloud misconfiguration and using LLMs to accelerate reconnaissance and exploitation. Attackers reused credentials found in public S3 buckets, modified a Lambda function to escalate privileges, moved laterally across numerous principals, and disabled model-call logging in Amazon Bedrock. Security experts warn that AI-enabled automation compresses attack timelines and reduces defenders' reaction windows.

🔒 Glean and Prisma AIRS have integrated to provide real-time AI threat protection that neutralizes prompt injections, blocks toxic or biased outputs, and inspects generated code and URLs for malicious patterns. The integration enforces organizational policy across chats and agent interactions and immediately blocks risky requests while notifying users. Deployment is designed to be frictionless—enable protection in three clicks by pasting a Prisma AIRS runtime API key into the Glean admin console.

🛡️ Microsoft has developed a scanner to detect hidden backdoors in open-weight language models, focusing on triggers and malicious behaviors inserted during training or fine-tuning. The tool flags three observable signatures — attention hijacking, leakage of poisoned training fragments, and sensitivity to partial triggers — and runs using forward passes only without retraining or backpropagation. It is designed to work with most causal, GPT-style models and to serve as an added layer of supply-chain security for enterprises using third-party or open-source models.

🔒 OpenClaw is an open-source, agentic AI assistant that can run locally or on servers, connect to LLMs and external APIs, and autonomously perform actions such as sending email or controlling browsers. Its local storage of config and broad access (files, terminals, sometimes root) makes misconfigured deployments attractive as backdoors. CrowdStrike observed rapid adoption and internet-exposed instances, and recommends discovery, runtime guardrails, and automated removal integrated into detection workflows.

🔒 Microsoft’s SDL is expanding to secure AI-powered systems by treating AI risks as dynamic, cross-disciplinary challenges rather than a static checklist. The update highlights AI-specific threats—prompt injection, data poisoning, memory and cache leakage, and malicious tool interactions—and stresses the need for telemetry-driven detection and faster feedback loops. Microsoft emphasizes developer-friendly policy, automation, and collaborative threat modeling to integrate security into everyday engineering practice.