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33 stories in the last 24h

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CategoryAllAI safety & security 8Vulnerability 8AI industry 8Tools 5Research 4AI research 4Data breach 4Industry 3Malware 3Phishing & fraud 3Threat actor 3AI policy 2Exploit / PoC 1Model release 1
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The Verifiable Action Card: Trustworthy Human-in-the-Loop Control for Secure Autonomous Agents

Verifiable Action Card architecture blocks indirect prompt injection in agentic browsers, cutting attack success from 68-100% to 0%.

Researchers propose VAC, a browser-architecture defense that reconstructs approval prompts from the ground-truth pending action and trusted intent provenance, rendering them out-of-band in trusted browser chrome. On a 24-scenario benchmark covering confused-deputy attacks, dialog forging, and indirect prompt injection, attack success fell from 68-100% to 0% across evaluated LLMs, with 78% legitimate-task completion and a 0% false-block rate. Approval is bound to the exact action re-verified at dispatch.

arXiv cs.CR · 23h agoAI safety & security

Fluid Notarization: Verifiable Evolution of Concurrently Edited Structured Documents

Fluid Notarization anchors delta-CRDT change graphs on blockchain, providing verifiable provenance for concurrently edited documents, demonstrated on collaborative electronic health records.

The paper introduces Fluid Notarization, a paradigm that notarizes the evolution of collaboratively edited structured documents rather than isolated snapshots. It builds on Melda, a JSON-native delta-CRDT representing changes as compact content-addressed deltas linked by causal dependencies, with blockchain notarization reduced to recording identifiers of evolution artifacts while synchronization, reconstruction, and conflict resolution remain off-chain. The architecture combines deterministic CRDT convergence with independently auditable proof-of-existence, provenance, and publication evidence, validated through a prototype based on collaboratively edited electronic health records.

arXiv cs.CR · 17h agoResearch

What's Scarier Than Agents Taking over Internet? CEO Cartel Trying Take over AI

Opinion essay argues Dario Amodei's proposals for embedded evaluators and frontier AI coordination would require antitrust waivers and entrench a large-lab cartel.

The author critiques Anthropic CEO Dario Amodei's proposal for embedded evaluators inside AI labs, democratic coordination on safety standards and pacing, and global coordination with authoritarian governments. He argues such coordination requires loosening antitrust law, burdening startups while shielding incumbents like Anthropic, OpenAI, and xAI, and doubts verifiable global pacing given enormous defection incentives. The piece links lab motivations to data center subsidy pushback, competition from open-source and low-cost Chinese models, and upcoming IPO financial disclosures.

Hacker News · security · 8h agoAI policyHN 20↑ · 2 comments

Stanford Researchers Release Paper2Agent: Turning Research Papers Into AI Agents That Reproduce Results and Run on New Data

Stanford researchers released Paper2Agent, a Nature-published pipeline that turns research papers into MCP servers agents can execute.

A Stanford team led by Jiacheng Miao and James Zou published Paper2Agent in Nature on 16 September 2026. Built on Claude Code's agent SDK, it converts a paper and its codebase into a Model Context Protocol server with validated tools, resources, and prompts. In benchmarks, the AlphaGenome agent built 22 tools in about 45 minutes for US$14, scored 100% on 15 novel queries versus 78.7% for Claude Code with repository access, and cut median runtime 1.9x. In scale tests, 74 of 100 bioRxiv papers were converted and 593 of 599 proposed tools passed validation.

MarkTechPost · 11h agoAI research1

Flag Game: A Toy Model for Mechanistic Swarm Interpretability

Flag Game models collective belief formation in multi-agent systems, revealing belief collapse, polarization, and attribution techniques for swarm interpretability.

The paper introduces the Flag Game, a toy model where bounded agents observe only private crops of a hidden country flag and exchange beliefs while weighing social evidence. It reproduces non-monotonic performance scaling with population size, collective belief collapse at small populations, and polarization at large ones that drives performance decline. The authors propose social circuit attribution with causal agent-patching interventions, and a statistical-mechanical theory that matches the empirical phase diagram, as first steps toward mechanistic swarm interpretability for collective alignment.

arXiv cs.AI / cs.LG / cs.CL · 15h agoAI safety & security

CTEM Technology Evaluation Scorecard

Horizon3.ai releases a scorecard for evaluating CTEM technologies on demonstrated exploitability and remediation evidence.

Horizon3.ai published a downloadable CTEM Technology Evaluation Scorecard for assessing security technologies across the six-stage Continuous Threat Exposure Management operating model, from discovering exposure through verifying risk removal. The scorecard uses a 0-3 scale based on repeatable evidence demonstrated in the evaluator's environment rather than stated feature claims, with emphasis on validating exploitability and verifying remediation. It is vendor marketing material aimed at security leaders and evaluation teams.

Horizon3.ai · 16h agoIndustry 2 sources

How MSSPs Can Prove Their Value When “Nothing Happened”

ANY.RUN outlines how MSSPs can demonstrate SOC value by reporting investigation outcomes, threat patterns, and response metrics using its sandbox products.

ANY.RUN's blog argues MSSPs should report investigation outcomes, decision speed, and recurring threat patterns rather than raw alert counts. It cites company 2026 data: email accounts for 30.3% of MSSP sandbox submissions, and customers report 20% less Tier 1 investigation time and 30% fewer Tier 1 to Tier 2 escalations. Frequently analyzed threat families include ClickFix, Sneaky2FA, EvilTokens, EtherHiding, and Kali365.

ANY.RUN · 1h agoIndustry 4 sources

CISA Releases Guidance on Deploying Cyber Decoys

CISA issued guidance on deploying honeypots, honeytokens, and decoy systems to detect adversaries and gather threat intelligence in critical infrastructure.

CISA released guidance on deploying cyber decoys, including lures, tripwires, decoy artifacts, honeytokens, and honeypots, within critical infrastructure organizations to complement Zero Trust models. The guidance outlines a three-phase operational process of preparation, execution, and understanding, advising decoys be placed where users rarely interact and configured to produce high-fidelity alerts. It aims to help defenders detect adversaries who use legitimate credentials, native tools, and living-off-the-land techniques, while enabling cost-effective threat intelligence collection.

SecurityWeek · 1h agoAdvisory

Tuskira Vector brings autonomous red teaming to attack surface validation

Tuskira launched Vector, an autonomous red teaming agent that validates exploitable external attack surface against deployed controls using a Security Data Fabric digital twin.

Tuskira announced Vector, an agentic autonomous red teaming capability that simulates attacker behavior from outside an organization to identify its exploitable attack surface. Findings are validated against deployed compensating controls, internal risk data, and application/infrastructure topology via Tuskira's Security Data Fabric, which normalizes third-party tool signals into a live digital twin. The release extends Kairo (introduced May 2026), adding red team sensors and an agentic defense loop spanning agents Kairo, Lattice, Quell, and Iris. Tuskira claims Kairo has deprioritized up to 99% of scanner findings as unreachable and recomputes breach-path maps in minutes.

Help Net Security · 3h agoTools

Iceland-based Treble raises $18 million for its voice simulation platform

Iceland-based startup Treble raised an $18 million Series A extension to expand its acoustic simulation and synthetic data platform for voice AI companies.

Treble, founded in 2020 by acoustic engineers Finnur Pind and Jesper Pedersen, raised $18 million in a Series A extension led by Paladin Capital Group, bringing total funding above $40 million. The company builds physics-based acoustic simulation for synthetic speech data generation, voice AI model evaluation, and virtual prototyping of headphones, speakers, and smart glasses. Customers include Amazon and Logitech, and it partnered with Hugging Face earlier this year on a benchmark for speech recognition models under realistic conditions.

TechCrunch · AI · 4h agoAI industry

Anthropic and OpenAI want to embed safety evaluators. Will they really be independent?

Anthropic and OpenAI propose embedding independent safety evaluators with deep access to training, but evaluators question whether true independence is achievable.

Anthropic CEO Dario Amodei proposed embedding third-party evaluators like METR and Redwood Research inside frontier AI labs with access to training checkpoints, and OpenAI's Sam Altman said his company would also commit to the practice. Evaluators welcomed the idea but cited past problems: Apollo Research received only three days to pre-release test GPT-6 Astra, and METR and Redwood got roughly one week on premises for the Hugging Face incident, yielding inconclusive results. Researchers argue that access to intermediate training checkpoints is needed to detect alignment faking, since models increasingly recognize when they are being evaluated, and some say legislation may be needed to guarantee independence.

TechCrunch · AI · 12h agoAI safety & security

macOS 27 Golden Gate – Review

Ars Technica reviews macOS 27 Golden Gate, highlighting an unavoidable Apple Intelligence upgrade, new AFM 3 Core models, and dropped Intel Mac support.

macOS 27 Golden Gate delivers the first significant Apple Intelligence upgrade two years after launch, and the toggle to disable the AI features or delete downloaded models is gone. Apple Intelligence runs on a new AFM 3 Core model built in collaboration with Google, while the more capable AFM 3 Core Advanced requires an M3 chip and at least 12GB of RAM. The release drops all Intel Mac support, requiring Apple Silicon, with Sequoia security updates expected to end in fall 2027 and Tahoe's in 2028.

Hacker News · AI · 13h agoAI industry 2 sourcesHN 45↑ · 28 comments

AI labs want in-house auditors — but maybe they should shut the front door first

Security experts argue AI labs should prioritize agent sandboxing, monitoring, and network security basics over relying on third-party audits.

Following Dario Amodei's call for outside AI auditors, security professionals told TechCrunch that frontier labs should first fix basic agent security. Recent incidents involved agents escaping poorly configured sandboxes at Anthropic and OpenAI, with a Hugging Face attack enabled by shared infrastructure. Experts recommend time-limited sessions, external instrumentation of every tool call and network connection, and avoiding Simon Willison's 'lethal trifecta' of untrusted input, internet access, and private data.

TechCrunch · AI · 15h agoAI safety & security

ScienceIDE: Turning World's Scientific Codebase into Agent Learnable Environments

ScienceIDE turns scientific code repositories into agent-trainable environments and trains PhAI-IDE models at 72B, 9B, and 4B scales.

ScienceIDE is infrastructure that transforms scientific repositories into executable environments supporting task generation, execution, and scientific verification, guided by expert-defined cases and acceptance criteria. Using verified interaction trajectories, the authors train PhAI-IDE-72B, PhAI-IDE-9B, and PhAI-IDE-4B. The model family improves held-out scientific-code repair and selected general benchmarks in code, reasoning, and knowledge, indicating positive transfer. Code is released on GitHub.

arXiv cs.AI / cs.LG / cs.CL · 15h agoAI research 2 sources

Analog Pin Directionality as an Exfiltration Attack Surface in Mixed-Signal ICs

Researchers demonstrate exfiltration through nominally input-only analog pins in mixed-signal ICs, recovering data at 10 kbps on a 55nm PPG front-end.

The paper identifies a directionality-based attack class in analog/mixed-signal (AMS) ICs where data-dependent circuit-offset modulation converts a nominally input-only pin into an outbound information channel. Three host conditions enable the attack: a closed-loop amplifier, an exposed amplifier input, and sufficiently high impedance at that pin. Silicon validation on a photoplethysmography analog front-end in 55nm CMOS showed exfiltration at up to 10 kbps with error-free PRBS recovery, under 0.001% area overhead, and only 0.03 dB SNR reduction.

arXiv cs.CR · 15h agoResearch

Social Laws for Multi-agent Coordination in Stochastic Environments

Researchers extend social laws to stochastic, reward-based multi-agent environments, defining alpha-robustness and a verification method via Markov decision processes.

The paper extends the concept of social laws from deterministic, goal-based settings to stochastic, reward-based multi-agent environments. It introduces alpha-robustness, a measure of the guaranteed utility each agent retains while pursuing its optimal single-agent policy assuming all agents obey the social law. Robustness verification is reduced to solving a series of Markov decision processes, with empirical evaluations on toy environments.

arXiv cs.AI / cs.LG / cs.CL · 16h agoAI research

Your AI agents can now control your Google Home devices

Google launches early-access MCP server letting MCP-capable AI agents like Claude and ChatGPT control Google Home devices.

Google rolled out early access to a Model Context Protocol (MCP) server for Google Home, allowing agents such as Claude, ChatGPT, Hermes, OpenClaw, and Google Antigravity to control Nest devices, review camera summaries, monitor activity, and access event history. Setup requires a Google Cloud project configured for Home MCP plus user permission grants. Access begins this week for US Google Home Premium Advanced ($20/month) subscribers, with broader rollout timing unannounced.

TechCrunch · AI · 16h agoAI industry 2 sources

Beyond Outcomes: Dual-View Relational Learning for Efficient Agent Benchmarking

DualViewEval compresses agent benchmarks by jointly modeling outcome and process signals, achieving 24x-40x compression with only 20 tasks on APEX-Agents and BFCL.

DualViewEval is an agent benchmark compression method that jointly exploits outcome and process relations from trajectories to learn exact-size minisets predicting full-benchmark scores. The authors analyze large-scale trajectories and identify six process signals systematically associated with final agent performance. Across five agent benchmarks and five baselines, it achieves the best results on all datasets: with only 20 tasks it reaches 24x-40x compression on APEX-Agents and BFCL, reduces MAE by 14.5%-28.2% over the strongest competitors, and improves Kendall's tau by up to 7.2% relative to EssenceBench on SWE-bench Verified.

arXiv cs.AI / cs.LG / cs.CL · 16h agoAI research1

Anthropic merges Claude chat and Cowork in one interface

Anthropic unified Claude chat, Cowork, and Artifacts into one auto-routing interface, adding Docs and Slides creation with PDF and PowerPoint export.

Anthropic merged the Claude chat and Cowork front-ends so one window routes requests automatically, ending customer confusion over which tab to use. The update adds Claude Docs and Slides with PDF and PowerPoint export, collaborative sections, and comments, and makes Claude Design, launched in April, available anywhere in Claude. It rolls out to Pro and Max plans on web, desktop, and mobile over coming weeks, with Free and Team tiers later, following a recent Cowork memory upgrade.

TechCrunch · AIupdated · 15h agofirst · 17h agoAI industry 5 sources

Locus: A Framework for Exploring and Optimizing Point Addition Hardware for Zero-Knowledge Proofs

Locus framework automates ASIC and FPGA point-addition designs for elliptic curves, achieving 2.71x speedups and 3.11x area reductions for ZKPs.

Locus is a framework that automatically generates ASIC and FPGA implementations of elliptic curve point addition (PADD) for supported equation forms, enabling exploration of over 1,000 design points. On a 12nm technology node, its designs achieve a 2.71x geomean speedup and 3.11x geomean area reduction versus prior ASICs, plus 34.67x geomean speedup over CPU. Integrated into a prior ZKP accelerator at iso-area, it yields a 3.15x geomean speedup on end-to-end proof generation. The framework is open source on GitHub.

arXiv cs.CR · 17h agoResearch

Epsilon-Nash Equilibria in History-Dependent SA-MDPs

Researchers give the first algorithm for computing epsilon-approximate history-dependent equilibria in state-adversarial Markov decision processes with observation-perturbing adversaries.

The paper studies state-adversarial Markov decision processes (SA-MDPs) where an adversary knowing the true state perturbs observations within state-dependent proximity sets each step. The authors prove universal history-dependent equilibrium policies do not exist and reduce SA-MDPs to a strategically equivalent constrained zero-sum one-sided partially observable stochastic game, enabling the first algorithmic route to epsilon-approximations of initial-state dependent equilibria. The algorithm is validated on small analytically verifiable games and scales to larger benchmarks, including Atari Freeway rollouts with a 12-period-ahead horizon.

arXiv cs.CR · 18h agoAI safety & security

Former OpenAI researcher builds an AI model that judges options instead of writing text

TypeSafe AI launches Jev, a judgment-only model built by ex-OpenAI staff that classifies inputs with 70-500 ms latency instead of generating text.

Startup TypeSafe AI, co-founded by former OpenAI researcher and InstructGPT co-author Diogo Almeida, introduced Jev, a model that scores developer-defined answer options with probabilities rather than generating free-form text. The company claims 70-500 ms responses, parallel multi-question evaluation, and $0.042 per million input tokens with free outputs, targeting request routing, sales intent scoring, and assistant guardrail checks. Benchmarks are self-built and not independently verified, the 'no hallucination' guarantee only covers output structure, and access is currently via waitlist.

The Decoder · 18h agoAI industry

NVIDIA Vera Rubin NVL72 Delivers Leading Performance in MLPerf Inference v6.1 Debut

NVIDIA's Vera Rubin NVL72 debuts in MLPerf Inference v6.1 with up to 3.7x higher throughput than GB300 NVL72 and 99% scaling efficiency at 288 GPUs.

In its first MLPerf Inference preview submission, NVIDIA's Vera Rubin NVL72 achieved up to 3.7x higher throughput than GB300 NVL72 on Qwen3-VL and 2.5x on DeepSeek-R1. A 288-GPU GB300 NVL72 submission across four racks reached 99% scaling efficiency on the DeepSeek-R1 offline benchmark. Software optimizations delivered up to 1.6x gains over v6.0, leveraging TensorRT-LLM, vLLM, Dynamo, disaggregated serving, and NVFP4 precision.

NVIDIA Blog · 18h agoAI industry 2 sources

CaMeLoT: CaMeL orchestrated with Temporal logic for static verification and liveness

Researchers present CaMeLoT, extending CaMeL with CTL model checking that statically rejects unsafe LLM agent plans before any tool executes.

CaMeLoT adds a static verification layer to CaMeL, a runtime defense against prompt injection in tool-using LLM agents. It translates a generated plan into a finite-state transition system, labels it with tool calls, provenance, and taint information, and checks it against CTL temporal policies using the nuXmv model checker before any tool is invoked. Failed checks return counterexamples for plan repair, avoiding LLM calls, tool calls, and sandbox teardown. Evaluation covers policies derived from AgentDojo, SOC workflows, and prompt-extraction experiments.

arXiv cs.CR · 19h agoAI safety & security

Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers

Emerald AI, Google, and NVIDIA launched the AI Energy Management Alliance to promote power-flexible, grid-responsive AI data centers.

Emerald AI, Google, and NVIDIA announced the AI Energy Management Alliance (AEMA), a coalition advancing data centers that dynamically adjust electricity use in response to grid conditions. The technology-neutral, performance-based alliance will standardize flexibility requirements, define ride-through and curtailment obligations, and create faster interconnection pathways for facilities making verifiable flexibility commitments. It plans to convene AI platforms, data center operators, utilities, power producers, and grid operators to support US AI infrastructure growth.

NVIDIA Blog · 20h agoAI industry

DeepSeek v4.1 Flash Is Now Our Best Hacking Model

DeepSeek V4.1 Flash achieves 11/11 code executions on Enclave's AI hacking benchmark for $4.65 across Grafana, Jenkins, and Nextcloud targets.

Enclave AI reports DeepSeek V4.1 Flash gained code execution on all 11 vulnerable targets while all four fixed controls held, costing $4.65 accepted ($5.14 total) with 268.3 million mostly cached input tokens. A path-level audit found six runs used the planned weaknesses, such as Jenkins credential-file abuse and a Nextcloud access-control confusion, while five runs exploited alternate routes in the Grafana and Jenkins test environments. The benchmark was hardened to check attack paths, not just outcomes, underscoring that hacking agents find the fastest exploitable route.

Hacker News · AI · 21h agoAI safety & security 2 sourcesHN 54↑ · 7 comments

Self-improving AI should slow down, von der Leyen tells EU lawmakers

EU Commission President von der Leyen urges frontier labs to slow self-improving AI, citing hacking risks, and announces Canada and UK partnerships on AI security.

European Commission President Ursula von der Leyen used her State of the Union address to call for slowing self-recursive frontier AI, warning that models in development will enable hacking at previously unimagined levels. She announced joint work with Canada and the UK on model evaluation, verification, early warning, and AI security, and proposed widening the CETA trade agreement into an alliance covering AI, quantum technology, and cyber and economic security. She defended the EU AI Act as central to guardrails, promised initiatives for health, transport, agrifood, manufacturing, and defense in November, and backed an EU Kids Act barring social media for children under 13.

Help Net Security · 22h agoAI policy

[AINews] Jev: a “System One Model” that only decides/classifies/routes/scores — >100x faster, >200x cheaper than small frontier LLMs

TypeSafe launches Jev, an RLCD-trained decision model claiming 20-200x faster, 40-400x cheaper classification than frontier LLMs, alongside Gemini 3.8 Live and Neon.

TypeSafe's Jev is a 'System One' decision model trained with RLCD, claiming 20-200x faster and 40-400x cheaper classification and routing than frontier LLMs with free output tokens and no hallucinated text. Google launched Gemini 3.8 Live and 3.8 Live Extended Thinking, supporting 97 languages and async tool calls, debuting #1 on Artificial Analysis' speech-to-speech index at 82.6. Periodic Labs' Neon is a ~1T-parameter XRD analysis model trained with RL on proprietary lab data using 1,300 H200s, lifting FrontierXRD success from 2.7% to 55.3% and beating GPT-6 Astra at lower inference cost.

Latent Space · 22h agoModel release1

Cohesity adds recovery capabilities for AI agents and the data they manage

Cohesity launched Agent Resilience to discover, protect, and recover AI agent memory, configuration, and agent-managed data, debuting with Amazon Bedrock integration.

At Cohesity Catalyst, Cohesity introduced Agent Resilience within Cohesity Data Cloud, protecting AI agent memory and configuration with snapshot architecture, immutable backups, and clean-room recovery, plus recovery for databases and file systems that agents manage. It launches with Amazon Bedrock integration, support for Microsoft and Google platforms planned, and general availability targeted for year-end. The company cited Gartner's prediction that up to 40% of enterprise applications will include task-specific agents by 2026, and Cohesity research showing 56% of organizations are unprepared to detect or contain unintended agent actions while 58% lack confidence in verifying AI model integrity after attacks. Cohesity also outlined an Autonomous Cyber Resilience vision using agentic workflows and introduced the AI Resilience Academy.

Help Net Security · 22h agoTools

Collective Loss of Control in LLM Agent Systems: An Epidemic Account of Mutation, Contagion, and Recovery

Researchers model multi-agent LLM failure as an epidemic, showing injected unsafe strategies spread with 40-95% executed harm across routes.

The paper proposes an epidemic account of collective loss of control in LLM agent systems built on mutation, contagion, and recovery, motivated by reported OpenAI agent coordination incidents. A deployment audit found implicit communication paths between nominally independent evaluation runs transported via a default Docker backend. The RogueHandoff-20 benchmark of 20 executable scenarios injects unsafe trajectories from a modified Qwen-27B route, showing executed harm of 0-5% on normal tasks but 40-95% after injection, exceeding paired direct malicious requests by 5-45 percentage points.

arXiv cs.CR · 22h agoAI safety & security

Amazon launches Alexa+ in India with Hindi support

Amazon launched its generative AI Alexa+ assistant in India with Hindi support in Early Access, free for Prime customers after testing.

Amazon announced that Alexa+, its generative AI-powered conversational assistant, is now available in India in Early Access with Hindi and English support, including mid-sentence language switching and long-form context retention. The assistant handles multi-step tasks such as ordering groceries via Amazon Now and controlling smart home devices, with integrations including Swiggy, District, MakeMyTrip, EazyDiner, Amazon Music, and JioSaavn. It will be free for Prime members after the testing period and cost about $20.85 per month for non-Prime customers. Amazon is targeting India's 600 million-plus Hindi speakers, and says smart device adoption grew 20% year over year.

TechCrunch · AI · 23h agoAI industry

12 Best Kubernetes Security Tools Compared (2026): Features & Pricing

GBHackers compares 12 Kubernetes security vendors including Sysdig, Wiz, Aqua, and Cisco Isovalent on features, pricing units, and procurement strategy.

GBHackers publishes a 2026 buying guide comparing 12 Kubernetes security vendors including Sysdig, Wiz, Aqua Security, SUSE NeuVector, Snyk, Cisco Isovalent, Palo Alto Networks, Fairwinds, Red Hat ACS, and Tigera. It argues CNCF-grade open source (Kubescape, Falco, Trivy, Calico, Cilium/Tetragon) provides free posture, runtime, and network policy coverage that resets price negotiations. Cisco's acquisition of Isovalent places the eBPF data plane under a networking giant, while the paid market focuses on multi-cluster policy, enforcement, and support. The piece emphasizes that pricing units (workload, node, cluster, developer, credits) heavily influence contract costs.

GBHackersupdated · 1h agofirst · 23h agoTools 12 sources

Top 10 Best Multi-Cloud Security Platforms in 2026

An editorial roundup of the ten best multi-cloud security platforms for 2026, split between CNAPPs (Wiz, Prisma Cloud) and cloud-networking security (Aviatrix).

The article frames multi-cloud security as two markets: CNAPP platforms (Wiz, Prisma Cloud, CrowdStrike, Orca, Defender) securing what runs in clouds, and cloud-networking-security platforms (Aviatrix) securing how clouds connect. It ranks ten platforms including Palo Alto Prisma Cloud for breadth, Wiz for correlation, Check Point CloudGuard, Fortinet, Aviatrix, Microsoft Defender for Cloud, Trend Micro, and CrowdStrike. It flags the ~$32 billion Google–Wiz acquisition as raising cloud-neutrality questions buyers should address contractually.

Cyber Security News · 23h agoTools