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AI workflows may be creating a dangerous new authorization blind spot
Noma Labs researchers describe 'workflow identity hijacking,' letting unauthenticated users trigger privileged AI workflows that execute actions with high-privilege service accounts.
Noma Labs lead researcher Sasi Levi detailed 'workflow identity hijacking,' where benign unauthenticated inputs via support inboxes, GitHub issues, or web forms trigger enterprise AI pipelines that execute privileged actions. The workflow runs using high-privilege service accounts or developer API keys, decoupled from the requester's identity, effectively creating a confused-deputy condition. Unlike prompt injection, the model behaves correctly; the failure lies in authorization enforcement at the workflow layer, and activity blends into routine automation. Mitigations include identity-aware access at execution points and user-context propagation between AI outputs and downstream operations.
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AI Agents Are Here. So Are the Threats.
Unit 42 demonstrates nine framework-agnostic attack scenarios against AI agents built with CrewAI and AutoGen, causing data leakage, credential theft and remote code execution.
Palo Alto Networks Unit 42 investigated how attackers can target agentic applications, implementing two functionally identical apps with the open-source CrewAI and AutoGen frameworks and executing the same attacks on both. Nine attack scenarios produce outcomes including information leakage, credential theft, tool exploitation and remote code execution. Findings show most vulnerabilities are framework-agnostic, arising from insecure design patterns, misconfigurations and unsafe tool integrations rather than flaws in the frameworks themselves. The team published defense strategies per scenario and open-sourced the source code and datasets on GitHub.
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Cyble Introduces Major Upgrade to its Executive Monitoring Module
Cyble upgraded Executive Monitoring in Cyble Vision, unifying impersonation, exposure, and mention findings with AI scoring and multi-channel alerting.
Cyble released a major upgrade to Executive Monitoring within its Cyble Vision platform, consolidating Mentions, Impersonations, Exposures, and a new Surface Mentions source (blog and news coverage) into a single findings stream. The release adds AI-generated verdicts and recommendations, per-executive Risk and Reputation scoring for board reporting, and richer onboarding with aliases, reference images, and addresses to cut same-name false positives. Alerting now supports data residency, bulk import, delivery via email, WhatsApp, and SMS, an Access API, and branded executive PDF reports; the upgrade is live with no customer action required.
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Your employees are already using AI tools you never approved
OneTrust report: 74% of organizations have scaled AI adoption, but only 17% embed governance by design and agent use outpaces oversight.
OneTrust's 2026 AI-Ready Governance Report finds 74% of respondents report departmental or scaled AI adoption, yet only 17% report governance embedded by design and just 5% have coordination and accountability defined across the AI lifecycle. Nearly half experienced at least one incident in the past year where AI systems or agents took unapproved actions, with data loss, corruption, and misclassification cited as the most likely and least prepared-for risks. 33% say employees used unapproved AI tools because approved options were not available quickly enough, and 98% plan to increase AI governance technology budgets next financial year.
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Open-source secrets scanning tool Sift hunts credentials in Microsoft 365, Slack, and Jira
Stratus Security open-sourced Sift, a CLI secrets scanner covering Active Directory, SharePoint, Teams, Slack, Jira, and Confluence, outperforming Snaffler in benchmarks.
Stratus Security released Sift, a free open-source command line tool that hunts passwords, API keys, and sensitive data across local disks, Windows shares, Active Directory, SharePoint, OneDrive, Teams, Slack, Jira, and Confluence. In the firm's benchmarks, Sift scanned 250,000 files in 10.61 seconds versus Snaffler's 25.48 and averaged 92 MiB memory versus Snaffler's 337 MiB. Optional false-positive filtering runs through a local language model via Ollama, and scans write checkpoints so interrupted runs resume. The tool found thousands of credentials in Jira ticket comments that prior pentesting had missed.
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AI "Mind Viruses" Can Spread Between Agents Through Persistent Prompt Files
Anthropic and EPFL researchers showed self-propagating payloads can spread between AI agents via persistent system-prompt files, though no in-the-wild spread was found.
A preprint released August 10, 2026 by Anthropic and EPFL researchers demonstrates that "mind virus" payloads can propagate between AI agents through persistent files such as SOUL.md and MEMORY.md that are injected into system prompts after context resets. In simulated agent chains modeled on OpenClaw, payloads stored in SOUL.md accounted for 88% of propagation attempts and succeeded 55% of the time, versus 17% success for ordinary workspace files; tested payloads ranged from crypto-ad text files to home-directory deletion. Susceptibility varied by model and configuration: Claude Sonnet 4.6 resisted and removed planted payloads, while DeepSeek V3.2, Qwen 3.5 32B, and Gemini 3 Flash adopted an ideological payload, and a one-paragraph warning in the system prompt reduced spread to near zero across 150+ adversarial payloads. No successful agent-to-agent propagation was found in the wild in archived Moltbook posts, and Anthropic's Frontier Red Team separately observed multiagent "turf wars" between unaware model instances sharing a codebase.
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Top 10 Best Device Control & USB Security Tools in 2026
A 2026 scorecard ranks ten USB and device control tools, placing Safetica, Ivanti DeviceLock and DriveLock at the top.
The article compares ten device control and USB security tools using a weighted scorecard covering control granularity, platform coverage, DLP integration, operability and value. Safetica, Ivanti DeviceLock and DriveLock rank highest, with notes on cross-platform depth, Windows granularity and European compliance fit. The piece highlights ownership changes, including CoSoSys joining Netwrix and Digital Guardian joining Fortra, and stresses device control as part of Zero Trust and DLP strategies.
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Phishing 3.0: The Fight Moves to Agent Versus Agent
Agentic AI transforms phishing economics, enabling personalized multi-channel attacks with deepfakes like the $25M Arup deepfake heist.
The article argues phishing has evolved through three stages: from malicious content, to intent-based BEC, to AI-powered multi-channel campaigns where attacker agents autonomously conduct reconnaissance and generate tailored lures. The widely reported Arup case saw a deepfake video call impersonating colleagues convince an employee to approve transfers worth roughly $25 million. An Osterman Research study of 128 security leaders found 88% experienced trust-undermining incidents, while Microsoft 365 EOP and Google Workspace were measured missing hundreds of phishing messages per 100 mailboxes monthly. The author argues defenders must adopt their own agents to match attacker speed.
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12 Best Ransomware Protection Solutions Compared (2026): Features & Pricing
GBHackers compares 12 ransomware protection solutions for 2026, recommending layered stacks of EDR prevention, managed detection, containment, and guaranteed recovery.
The editorial comparison argues no single product stops ransomware, recommending a layered strategy across prevention, early detection, blast-radius containment, and clean recovery. CrowdStrike and SentinelOne are named best-in-class EDR, Huntress and Sophos MDR for managed 24/7 coverage, ColorTokens for microsegmentation containment, and Rubrik and Acronis for guaranteed recovery. The guide notes ransomware is now professionalized with double extortion and encryption sprints measured in minutes.
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DeepSeek AI Released DeepSeek-V4.1-Flash with 1M Context, FP4 KV Cache, and Cross-Layer Attention Reuse
DeepSeek released open-weight V4.1-Flash, a 552B MoE model with 1M context and FP4 KV cache, beating Opus-5 and GPT-5.6 Sol on agent benchmarks.
DeepSeek-V4.1-Flash is a multimodal Mixture-of-Experts model with a 552B-parameter backbone plus 196B Engram parameters, activating 8B parameters at prefill and 16B at decode, with a 1M-token context window. It introduces a causal encoder-decoder design, Compressed Sparse Attention 2, and FP4 (E2M1) KV cache quantization, cutting global KV cache to 890 bytes per token, about 1/4 of V4-Flash and 437x smaller than V1. Pre-training covered 45T multimodal tokens; the MIT-licensed weights ship on Hugging Face with vLLM and SGLang support. It scores 90.6 on Terminal-Bench 2.1 and 74.2 on DeepSWE v1.1, ahead of Opus-5 and GPT-5.6 Sol.
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Cyberbit partners with Optiv to bring simulation-based SOC Team training to clients in North America
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Retrospectively Reverse-Engineering Apple's Neural Engine
A developer reverse-engineers Apple's M1 Neural Engine architecture, mapping compute cores, MAC datapaths, and schedulers to explain the NPU's decline as transformers displaced CNN workloads.
A developer who previously maintained a reverse-engineered Linux driver for Apple's Neural Engine (ANE) published a retrospective deep dive mapping the M1 ANE's full internal architecture: compute, datapath, scheduler, memory, and execution model. The M1 ANE has 16 compute cores with 128 FP16 (or 256 INT8) MAC lanes each, totaling 2048 parallel MAC lanes, using 32-bit Q16.16 fixed-point accumulation with FP16 readout and an accumulator that saturates at 2^15. The author argues the ANE's dataflow was architected around the predictable reuse patterns of 2017-era CNN workloads (dating to the A11 Bionic), which autoregressive transformer decode broke, limiting its usefulness for general ML. With Apple's M5 folding ANE cores into GPU cores to tout LLM performance, the post frames this as the beginning of the end for the standalone NPU.
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TLD Tracker: Exploring Newly Released Top
Unit 42 tracked 19 newly released top-level domains and found large-scale phishing, unwanted program distribution, and cybersquatting tied to TLD launch dates.
Researchers analyzed 19 new generic TLDs, including .zip, .bot, .ing, and .meme, released or approaching general availability over roughly 18 months. Data from passive DNS, registry zone files, newly registered domain feeds, and the Tranco top-1M list showed phishing campaigns, potentially unwanted program distribution, and domain squatting on these TLDs. Abuse correlated with each TLD's rollout phases, indicating attackers monitor general availability dates to register and weaponize domains. The IANA root database now lists over 1,000 generic TLDs.
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When AI Agents Go Rogue: Agent Session Smuggling Attack in A2A Systems
Unit 42 unveils agent session smuggling, where a rogue AI agent hides covert instructions in established Agent2Agent (A2A) protocol sessions to manipulate victim agents.
Palo Alto Networks Unit 42 discovered agent session smuggling, a new attack technique in which a malicious AI agent exploits an established cross-agent session under the Agent2Agent (A2A) protocol to send covert instructions hidden among benign client requests and server responses. The technique leverages the implicit trust agents place in collaborating agents and the stateful, multi-turn nature of A2A sessions; the researchers stress it affects any stateful protocol, not an A2A flaw. Unlike one-shot data-based attacks, a rogue agent can converse, adapt and build false trust over multiple interactions. Proposed mitigations include human-in-the-loop enforcement, cryptographically signed AgentCards for remote agent verification, and context-grounding to detect injected instructions.
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You don’t have to join the hack-back program to inherit its risk
A new US presidential memorandum creates a vetted private hack-back program, leaving participating vendors and their customers with untested legal liability and collateral risks.
The August 12 National Security Presidential Memorandum directs the National Coordination Center, run jointly by DOJ and DHS, to approve covert surveillance and disruptive Cyber Effects Operations by vetted private companies, with a forfeitable bond of at least $1 million required as a contract condition. The analysis argues the criminal shield rests on an untested reading of the CFAA exemption at 18 U.S.C. 1030(f), with no civil safe harbor, no state-law preemption and no foreign-law protection. Non-participating organizations can still inherit risk through shared infrastructure collateral damage, lack of customer disclosure, Lloyd's bulletin Y5381 state-backed attack exclusions, and threat-intelligence pipelines feeding offensive proposals.
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Top 10 Best Mobile Threat Defense (MTD) Solutions in 2026
Roundup of 2026 mobile threat defense tools recommends Zimperium and Lookout for targeted-attack detection and Defender for Endpoint for Microsoft shops.
This guide ranks ten mobile threat defense solutions, recommending Zimperium and Lookout for on-device detection against targeted users such as executives and journalists, and Microsoft Defender for Endpoint mobile for organizations already licensing Microsoft 365 E5. It explains that MDM enforces configuration while MTD detects attacks, and that mobile phishing now arrives via SMS, messaging apps and QR codes rather than email. It also highlights mercenary spyware and zero-click exploits as shifting requirements for high-risk users, referencing Apple's threat-notification program and Lockdown Mode.
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The 12 Best Antivirus (Endpoint Protection) Software for Business, Compared and Priced
GBHackers compares 12 business antivirus products on detection, EDR depth, pricing, and platform coverage, ranking CrowdStrike and Bitdefender joint top at 8.8.
The roundup scores 12 enterprise endpoint protection vendors across detection, EDR depth, management, pricing transparency, and platform coverage. CrowdStrike and Bitdefender tie at 8.8, with Microsoft Defender for Endpoint scoring 8.5 and noted as effectively free for Microsoft 365 E5 licensees. The piece also flags that Kaspersky cannot legally be sold in the US and that Panda and Webroot now sit under WatchGuard and OpenText respectively.
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[AINews] 10% worse, 100x cheaper, 10000x faster: Why Simulation is taking over
Latent Space argues AI training pipeline stages—rewards, data, teachers, curricula, environments—are flipping from human-made to model-made simulation.
Latent Space's AINews essay traces how each component of AI training has turned synthetic since 2022: reward models (InstructGPT, RLAIF), synthetic pretraining data (Microsoft Phi, NVIDIA Nemotron-4 340B), model teachers (Alpaca, DeepSeek-R1 distillation), and self-generated curricula (Self-Rewarding Language Models, SPIN). In 2026 it highlights Karpathy's autoresearch loop—700 experiments yielding 20 kept improvements, cutting GPT-2 training time from 2.02 to 1.80 hours—and Z.ai's GLM-5.3 fully synthetic RL environment, judging, and verification stack. It frames these shifts as 'simulation': 10% worse but 100x cheaper and 10,000x faster than human equivalents.
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12 Best Browser Isolation Solutions Compared (2026): Features & Pricing
2026 comparison ranks Zscaler, Cloudflare, Menlo Security, Garrison (Everfox), Authentic8 and Kasm among twelve remote browser isolation solutions.
Guide compares twelve RBI products across four architectures: pixel streaming, DOM/vector reconstruction, platform-embedded SSE isolation, and self-hosted containers. Zscaler and Cloudflare lead RBI delivered inside SSE platforms, while Menlo Security leads isolate-everything efficacy and Garrison (Everfox) provides hardware-grade isolation for government use. Most offerings price per user per month.
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The Outsized Shadow: Why 5% of AI Users Are Your Biggest Security Risk
Akamai's 2026 Enterprise AI Usage report finds the top 5% of AI power users create outsized shadow AI, data leakage, and agent security risks.
Akamai's State of the Internet: Enterprise AI Usage Risk Report 2026, based on real-world usage telemetry, finds the top 5% of enterprise AI power users interact with AI models at 12 times the rate of the bottom 50% of the workforce. 47.11% of enterprise AI conversations occur through personal identities rather than corporate-managed accounts, and 14.4% run through corporate email addresses tied to personal freemium subscriptions. 17.7% of employees at midsize enterprises use AI browser or IDE extensions, of which 16.31% contain known CVE vulnerabilities and nearly 75% request high or critical permissions. The report also describes emerging attack vectors including Vibe Hacking, CursorJacking, and CometJacking indirect prompt injection.
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Why Johnny Can't Encrypt: A Usability Evaluation of PGP 5.0 (1999)
Seminal 1999 USENIX study finds most novice users cannot correctly sign and encrypt email with PGP 5.0 in 90 minutes.
Whitten and Tygar's USENIX Security Symposium paper evaluates whether cryptography novices can use PGP 5.0 effectively, using cognitive walkthrough analysis and a laboratory user test. The majority of test participants failed to successfully sign and encrypt a message within 90 minutes, despite PGP 5.0 having a well-regarded graphical interface. The authors argue that security requires usability standards beyond those of general consumer software and propose domain-specific UI design principles for security. The paper is a foundational reference in usable security research.
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WordPress Security Plugins: How to Choose the Right One
Sucuri's guide breaks WordPress security plugins into hardening, malware scanning, integrity monitoring, and filtering types, and explains how to evaluate and layer them.
The Sucuri guide explains that WordPress security plugins bundle five capabilities - hardening, malware detection, integrity monitoring, activity logging, and application-level filtering - and that plugins run only after WordPress loads, unlike server-level firewalls. It lists leading causes of compromise: outdated plugins and themes, weak or reused credentials, nulled premium software, insecure configuration, and shared-hosting cross-contamination. It concludes with evaluation criteria and a post-installation security checklist for owners without dedicated security teams.
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Cognition launches new SWE-2 model, Rivaling Fable 5.1 and GPT-Astra
Cognition released SWE-2, a coding model post-trained from Kimi K3 that scores 50.0% on FrontierCode 1.1 Main, near Fable 5.1 at 64% lower cost.
Cognition introduced SWE-2, its most advanced coding model, post-trained from the 2.8T-parameter Kimi K3 base model. It achieves 50.0% on FrontierCode 1.1 Main, 73.0% on DeepSWE 1.1, and 92.8% on Terminal-Bench 2.1, beating Grok 4.6 and SWE-1.7 while matching Fable 5.1 and GPT-5.6 Sol at a fraction of the price. The company says it scaled reinforcement learning to the multi-trillion-parameter regime for the first time, using Pareto-informed cost penalties that train all reasoning-effort levels in a single run, tripled RL environments, and NVFP4/FP8 quantization-aware training. SWE-2 is available today in Devin Desktop and CLI, with rollout on Devin Web and Fusion.
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When AI Remembers Too Much
Unit 42 PoC shows indirect prompt injection can poison Amazon Bedrock Agent long-term memory, enabling silent exfiltration of conversation history across future sessions.
Palo Alto Networks Unit 42 published a proof of concept showing that indirect prompt injection can silently poison the long-term memory of Amazon Bedrock Agents when the memory feature is enabled. Malicious content on a webpage or document manipulates the agent's session summarization process, so injected instructions persist across sessions and are added to later orchestration prompts, silently exfiltrating user conversation history. The issue is not a vulnerability in the Amazon Bedrock platform but an illustration of the broader unsolved LLM prompt-injection challenge. Amazon reviewed the research and stated that Bedrock Guardrails with the prompt-attack policy provides effective mitigation.
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U.S. Agencies Accuse China AI Firms of Distilling Claude, GPT, Gemini, and Grok
NSA, CISA and FBI accuse Chinese AI firms including DeepSeek of industrial-scale distillation of Claude, GPT, Gemini and Grok since late 2024.
A joint bulletin from the NSA, CISA and FBI accuses China-based AI firms including DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun and Z.AI of systematic, industrial-scale distillation of U.S. frontier models. The agencies say billions of tokens were extracted from Claude, GPT, Gemini and Grok variants since at least late 2024 through APIs, cloud relays, obfuscated accounts and gray-market proxies, likely with Chinese government backing. Firms allegedly shared premium subscriptions across developer teams and used chain-of-thought extraction and automated failover to evade blocks. Mitigations include subtly altering responses to suspected distillers and correlating activity across providers, clouds and aggregators.
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