All news with #ai security tag

🔒 This Special Report examines the distinct security challenges of cloud environments, the current threat landscape organizations face, and how rapid AI adoption is amplifying those risks. It highlights common hidden exposures across configurations, data stores, and APIs. The report also presents practical strategies and best practices for improving cloud posture, governance, and operational controls to reduce overall attack surface.

⚠️Tenable has revealed three vulnerabilities in Google's Gemini platform, collectively dubbed the "Gemini Trifecta," that enable indirect prompt injection and data exfiltration through integrations. The issues allow attackers to poison GCP logs consumed by Gemini Cloud Assist, inject malicious entries into Chrome search history to manipulate the Search Personalization Model, and coerce the Browsing Tool into fetching attacker-controlled URLs that leak sensitive query data. Google has patched the flaws, and Tenable urges security teams to treat AI integrations as active threat surfaces and implement input sanitization, output validation, monitoring, and regular penetration testing.

🔒 Databricks has introduced Data Intelligence for Cybersecurity, an AI-driven platform that unifies fragmented security telemetry on its Lakehouse architecture to provide real-time, context-rich threat detection. The offering includes Agent Bricks to build governed AI agents, conversational dashboards, and natural-language queries for nontechnical stakeholders. Early adopters such as Arctic Wolf, Palo Alto Networks, and SAP report sharper detection, lower costs, and faster operations, while Databricks expands integrations across a broad partner ecosystem to challenge established SIEM and analytics vendors.

🔒 CISOs must now prioritize integrity protection as AI introduces new attack surfaces such as data poisoning, prompt injection and adversarial manipulation. Shadow AI — unsanctioned use of models and services — increases risks of data leakage and insecure integrations. Defenses should combine Security by Design, governance, transparency and compliance (e.g., GDPR, EU AI Act) to detect poisoned data and prevent model drift.

🔍 Security leaders report a breaking point as daily alert volumes average 960 and large enterprises exceed 3,000, forcing teams to leave many incidents uninvestigated. A survey of 282 security leaders shows AI has moved from experiment to strategic priority, with 55% deploying AI copilots for triage, detection tuning, and threat hunting. Organizations cite data privacy, integration complexity, and explainability as primary barriers while projecting AI will handle roughly 60% of SOC workloads within three years. Prophet Security is highlighted as an agentic AI SOC platform that automates triage and accelerates investigations to reduce dwell time.

⚠️ Notion 3.0 introduces AI agents that, the author argues, create a dangerous attack surface. The vulnerability exploits Simon Willson’s lethal trifecta—access to private data, exposure to untrusted content, and the ability to communicate externally—by hiding executable instructions in a white-on-white PDF that instructs the model to collect and exfiltrate client data via a constructed URL. The post warns that current agentic systems cannot reliably distinguish trusted commands from malicious inputs and urges caution before deployment.

🔐 Agent Payment Protocol (AP2) is an open trust layer that enables AI shopping agents to complete purchases without ever handling raw payment credentials. AP2 enforces a role-based separation—shopping agent, merchant endpoint, credential provider, and payment processor—and relies on verifiable credentials to produce cryptographic proof of intent and approval. It defines three mandate types (Cart, Intent, Payment) to support both human-present and human-not-present flows. Developers can adopt AP2 as an extension to A2A and MCP to reduce PCI scope and improve accountability.

🛡️ Microsoft flagged a targeted phishing campaign that used AI-assisted code to hide malicious payloads inside SVG files. Attackers sent messages from a compromised business account, employing self-addressed emails with hidden BCC recipients and an SVG disguised as a PDF that executed embedded JavaScript to redirect users through a CAPTCHA to a fake login. Microsoft noted the SVG's verbose, business-analytics style — flagged by Security Copilot — as likely produced by an LLM. The activity was limited and blocked, but organizations should scrutinize scriptable image formats and unusual self-addressed messages.

⚠️ Organizations eager to deploy generative AI often underestimate the cybersecurity risks, from AI-driven phishing to model manipulation and deepfakes. The article, sponsored by Acronis, warns that many firms—especially smaller businesses—lack processes to assess AI security before deployment. It urges embedding security into development pipelines, continuous model validation, and unified defenses across endpoints, cloud and AI workloads.

🛡️ A Gartner survey found 29% of security leaders reported generative AI applications in their organizations were targeted by cyberattacks over the past year, and 32% said prompt-structure vulnerabilities had been deliberately exploited. Chatbot assistants are singled out as particularly vulnerable to prompt-injection and hostile prompting. Additionally, 62% of companies experienced deepfake attacks, often combined with social engineering or automated techniques. Gartner recommends strengthening core controls and applying targeted measures for each new risk category rather than pursuing radical overhauls. The survey of 302 security leaders was conducted March–May 2025 across North America, EMEA and Asia‑Pacific.

🔐 At Fal.Con 2025, CrowdStrike CEO George Kurtz outlined a shift from reactive SOCs to an agentic model where intelligent agents reason, decide, act, and learn across domains. CrowdStrike introduced seven AI agents within its Charlotte framework for exposure prioritization, malware analysis, hunting, search, correlation rules, data transformation and workflow generation, and is enabling customers to build custom agents. The company highlights a proprietary "data moat" of trillions of telemetry events and annotated MDR threat data as the foundation for training agents, and announced the acquisition of Pangea to protect AI agents and launch AIDR (AI Detection and Response). The vision places humans as orchestrators overseeing fleets of agents, accelerating detection and response while preserving accountability.

⚠️ Research and expert interviews indicate that AI coding assistants cut trivial syntax errors but increase more costly architectural and privilege-related flaws. Apiiro found AI-generated code produced fewer shallow bugs yet more misconfigurations, exposed secrets, and larger multi-file pull requests that overwhelm reviewers. Experts urge preserving human judgment, adding integrated security tooling, strict review policies, and traceability for AI outputs to avoid automating risk at scale.

🔒 At DEF CON 33, Google and Airbus hosted the GenSec Capture the Flag (CTF) to promote human–AI collaboration and accelerate adoption of AI in cybersecurity workflows. Nearly 500 participants completed introductory challenges, 23% used AI for security for the first time, and 85% found the event useful for learning practical AI applications. The CTF also featured Sec-Gemini as an optional assistant in the UI; 77% of respondents rated it very or extremely helpful, and organizers are incorporating feedback into future iterations.

🛡️ Bugcrowd's annual "Inside the Mind of a CISO 2025: Resilience in an AI-Accelerated World" report warns that rapid, AI-assisted development is expanding the attack surface and exposing foundational weaknesses. Published September 23, the study links faster release cycles to gaps in access control, data protection and hardware security, and highlights rising API and network vulnerabilities. It calls for continuous offensive testing and collective intelligence to mitigate escalating risks.

🔐 Selecting an AI platform is necessary but insufficient; successful enterprise adoption hinges on how the system is introduced, integrated, and supported. CISOs must publish a clear, accessible AI use policy that defines permitted behaviors, off-limits data, and auditing expectations. Provision access by default using SSO and SCIM, pair rollout with vendor-led demos and role-focused training, and provide living user guides. Build an AI champions network, harvest practical productivity use cases, limit unmanaged public tools, and keep governance proactive and supportive.

🛡️ AI is being applied across security operations in novel ways to predict, simulate, and deter attacks. Experts from BforeAI, NopalCyber, Hughes, XYPRO, AirMDR, and Kontra outline six approaches — predictive scoring, GAN-driven attack simulation, AI analyst assistants, micro-deviation detection, automated triage and response, and proactive generative deception — that aim to reduce alert fatigue, accelerate investigations, and increase attacker costs. Successful deployments depend on accurate ground truth data, continuous model updates, and significant compute and engineering investment.

🤖 AI-driven phishing campaigns are increasingly using convincing fake CAPTCHA pages to bypass security filters and trick users into revealing credentials. Trend Micro found these AI-generated pages hosted on developer platforms such as Lovable, Netlify, and Vercel, with activity observed since January and a renewed spike in August. Attackers exploit low-friction hosting, platform credibility, and AI coding assistants to rapidly clone brand-like pages that first present a CAPTCHA, then redirect victims to credential-harvesting forms. Organizations should combine behavioural detection, hosting-provider safeguards, and phishing-resistant authentication to reduce risk.

🔒 Falcon Cloud Security provides end-to-end protection for AI development pipelines by embedding AI detection into CI/CD workflows, scanning container images, and surfacing AI-related packages and CVEs in real time. It extends visibility to cloud model services — including AWS SageMaker and Bedrock, Azure AI, and Google Vertex AI — revealing model provenance, dependencies, and API usage. Runtime inventory ties build-time detections to live containers so teams can prioritize fixes, govern models, and maintain delivery velocity without compromising security.

🔓 Radware disclosed ShadowLeak, a zero-click vulnerability in OpenAI's ChatGPT Deep Research agent that can exfiltrate sensitive Gmail inbox data when a single crafted email is present. The technique hides indirect prompt injections in email HTML using tiny fonts, white-on-white text and CSS/layout tricks so a human user is unlikely to notice the commands while the agent reads and follows them. In Radware's proof-of-concept the agent, once granted Gmail integration, parses the hidden instructions and uses browser tools to send extracted data to an external server. OpenAI addressed the issue in early August after a responsible disclosure on June 18, and Radware warned the approach could extend to many other connectors, expanding the attack surface.

🚀 Managed Lustre on GKE is a managed parallel file system with a CSI driver that brings low-latency, high-throughput POSIX storage to Kubernetes for demanding AI and HPC workloads. It is recommended for training, checkpointing, and small-file patterns where GPUs/TPUs must stay utilized, while Cloud Storage is an alternative for large, higher-latency files. The article presents five operational best practices—data locality, tiering, networking, provisioning, and using Kubernetes Jobs with a shared PVC—to maximize performance and control costs.