Smart search ranks by meaning as well as keywords (one row per story, last 45 days).
Palo Alto Networks publishes a product category page for Cortex Cloud, an AI and automation platform for cloud and SOC workflows.
This item is a product category archive page for Palo Alto Networks' Cortex Cloud, describing it as an AI and automation-driven platform spanning code to cloud to SOC. The page contains no new research, incident, or product release details beyond marketing language about prioritizing risks and accelerating remediation.
Unit 42 clusters behavior of 40,000+ AWS identities from 125 cloud environments to map functional roles and enable lightweight SQL-based detection.
Palo Alto Unit 42 built an unsupervised behavioral clustering model using UMAP and HDBSCAN on AWS CloudTrail logs to map cloud identities to functional roles such as administrators, backup services, security tooling and DevOps. The study analyzed over 40,000 identities across 125 cloud environments over two months. The researchers show that heuristics extracted from the clustering map can be implemented in standard SQL, enabling role classification at scale without running a continuous ML pipeline. The methodology extends to audit logs from other cloud providers, SaaS and Kubernetes.
Palo Alto Networks markets Cortex as an AI-driven security operations platform for detection, investigation, automation and response.
The Unit 42 blog page is a product category archive for the Cortex security operations portfolio. Cortex is described as an AI-driven SecOps platform providing detection, investigation, automation, and response capabilities. No research findings, incidents, or vulnerabilities are discussed.
Unit 42 found a BOLA flaw, CVE-2024-22278 (CVSS 6.4), letting Maintainers improperly alter Harbor project metadata; fixed in versions 2.9.5, 2.10.3, and 2.11.0.
Unit 42 researchers identified a broken object-level authorization flaw, CVE-2024-22278, in Harbor, a CNCF-graduated cloud-native container registry with 1.8 million downloads. The flaw (CVSS 6.4) lets users with the Maintainer role create, update, and delete project metadata, actions reserved for ProjectAdmin, risking data exposure, integrity compromise, and circumvention of vulnerability scanning. Harbor patched the issue in versions 2.9.5, 2.10.3, and 2.11.0. The finding came from Unit 42's automated BOLA detection tool built on generative AI.
Unit 42 details five vulnerabilities (CVSS 7.0-7.8) in ICONICS Suite SCADA software enabling privilege escalation and DoS.
Unit 42 discovered five vulnerabilities (CVE-2024-1182, CVE-2024-7587, CVE-2024-8299, CVE-2024-8300, CVE-2024-9852) in ICONICS Suite versions 10.97.2 and earlier for Windows during a 2024 security assessment. The flaws, rated CVSS 7.0-7.8, allow DLL hijacking, privilege escalation, information disclosure, denial-of-service and potentially full system compromise. ICONICS Suite is a SCADA solution with hundreds of thousands of installations in over 100 countries, widely used in critical infrastructure, and several dozen servers are internet-exposed per Unit 42 telemetry. ICONICS released patches and advisories with workarounds in 2024.
Researchers introduced Brain2Semantics2Text, decoding sentence meaning from non-invasive MEG brain recordings via a semantic bottleneck, improving on prior Brain2Text methods.
The paper proposes Brain2Semantics2Text, a non-invasive speech decoding method that maps sentence-level magnetoencephalography (MEG) responses into a semantic embedding space and inverts those embeddings into natural language. Motivated by evidence that high-level semantic representations are distributed across cortex and evolve on slower timescales, the approach targets meaning rather than phonemes or words, avoiding the need for word-level alignment. The authors report improved sentence-level results compared to prior non-invasive Brain2Text methods despite the low signal-to-noise ratio of neural recordings.
Palo Alto Networks Unit 42 hosts content under its Cortex XSOAR category, covering the vendor's security orchestration, automation and response platform.
The item is a Unit 42 category page for Cortex XSOAR rather than a standalone article; no article text was available. Cortex XSOAR is Palo Alto Networks' security orchestration, automation and response (SOAR) platform used for incident management and playbooks. No incident, vulnerability, or research findings could be extracted from the available information.
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.
Unit 42 demonstrates that root access on a Kubernetes node lets attackers spoof SPIFFE/SPIRE attestation and harvest co-located workloads' SVIDs.
Palo Alto Networks Unit 42 describes post-exploitation techniques in which an attacker with root on a compromised Kubernetes node spoofs Linux cgroup metadata used by the SPIRE agent during workload attestation, tricking it into issuing a co-located workload's SPIFFE Verifiable Identity Document to an attacker-controlled process. The research shows the core trust assumption of machine-identity systems—that the node is trusted—collapses once root is obtained, exposing all cryptographic identities scoped to that node. Unit 42 released an open-source tool, Spooffe, for defenders to test identity exposure, and notes the technique has not been observed exploited in the wild.
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.
Unit 42 red-teamed Amazon Bedrock multi-agent applications, demonstrating prompt-injection attack chains that leak agent instructions and invoke tools, mitigated by Bedrock Guardrails.
Unit 42 red-teamed Amazon Bedrock Agents' multi-agent collaboration in Supervisor and Supervisor with Routing modes. The demonstrated attack chain detects the operating mode, discovers collaborator agents, delivers attacker-controlled payloads, and can disclose agent instructions and tool schemas and invoke tools with attacker-supplied inputs. No vulnerabilities were found in Bedrock itself, and the built-in prompt attack Guardrail blocked the attacks when properly configured. The researchers collaborated with Amazon's security team and frame the findings as a broader prompt injection risk for LLM-based systems.
Unit 42 maps attack paths into AWS, Azure, and GCP VMs through intended features like startup scripts and SSH key pushes.
Palo Alto Unit 42 reviewed attack vectors against virtual machine services on AWS, Azure, and GCP, finding that 11% of internet-exposed cloud hosts carry Critical or High severity vulnerabilities. The attack paths rely on legitimate features such as EC2 User Data, VM custom data, EC2 Instance Connect, SSM Run Command, and serial consoles rather than vulnerabilities, and exploiting them requires attackers to first obtain control plane permissions. A compromised VM exposes not only its data but the workload identity and cloud permissions assigned to it, making identity compromise potentially more damaging than data theft. The firm places mitigation responsibility on cloud users and administrators.
Ambient team wins EgoLongQA 2026 sub-2B division by distilling an agentic long-video perception pipeline into a 2B vision-language model.
Ambient's entry to the EgoLongQA track of the Wearable-AI Challenge at ECCV 2026 placed first in the <=2B parameter division with 0.8279 on the held-out test set. The system distills the junior perception module of a tool-using agentic pipeline into a 2B student, reaching 89% of the pipeline's accuracy with 1.1% of its parameters and lifting a 27.1% base model to 81.4%. To meet the division limit, the multilingual embedding table is pruned from 248,320 to 143,469 rows, reaching 1.9985B parameters with provably identical logits on retained rows.
Editorial scorecard ranks ten 2026 cloud detection and response platforms; Sysdig, Wiz, and CrowdStrike lead, with Wiz's Gem Security acquisition highlighted.
The editorial scorecard rates ten CDR platforms on real-time detection (30%), cloud telemetry depth, response automation, correlation, and value. Sysdig earns the best real-time detection score for its Falco- and eBPF-powered runtime telemetry, Wiz (8.7) folds acquired Gem Security's real-time CDR into its security graph, and CrowdStrike (8.7) leads response automation. Specialists Stream.Security, Skyhawk Security, Sweet Security, and the open-source Falco project are also assessed.
Stub page for Palo Alto Cortex XDR with no article text, offering no news content for classification.
The item contains only the title 'cortex xdr' and no article body. It references Palo Alto Networks' Cortex XDR product but provides no event, release, or threat information. Classified as general vendor/industry content with minimal relevance.
GBHackers ranks 12 server security solutions for 2026, naming CrowdStrike and SentinelOne as server EDR leaders and Trend Micro Deep Security top for virtual patching.
The guide scores 12 server security platforms across five weighted criteria, with detection and response depth and Linux parity weighted 25% each. CrowdStrike and SentinelOne lead server EDR, Trend Micro Deep Security is highlighted for virtual patching of unpatchable estates, and Microsoft Defender for Servers is noted for Azure and hybrid economics. It is an editorial assessment comparing features and pricing models rather than a lab test.
Researchers propose TFTrack, a template-free LiDAR 3D single object tracking framework cutting FLOPs ~50% while running at ~120 FPS.
TFTrack is the first template-free framework for 3D Single Object Tracking, dropping template-search pairings and complex motion modeling in favor of the prior bounding box center plus geometric alignment. It ships in three variants (TFTrack-Voxel, TFTrack-Pillar, TFTrack-Point) covering sparse and dense 3D representations. On KITTI and nuScenes it is competitive with leading template-based trackers while reducing FLOPs by about 50% and running near 120 FPS. Code is released, targeting real-time deployment in embedded robotics such as autonomous vehicles.
Unit 42 dissects FrostyGoop OT malware, which sent Modbus TCP commands to disrupt heating for 600+ apartment buildings in Ukraine.
Palo Alto Unit 42 analyzed new FrostyGoop/BUSTLEBERM samples, the ninth known ICS-centric malware, first used against a Ukrainian municipal energy company by sending Modbus TCP commands to ENCO control devices. The attack caused a two-day heating outage affecting over 600 apartment buildings during sub-zero temperatures. The Go-compiled malware accepts Modbus register operations and timing parameters via command-line arguments or a JSON configuration file, uses an obscure open-source Modbus library, and checks the Windows BeingDebugged flag to evade debuggers. Unit 42 telemetry recorded over 1 million Modbus TCP devices exposed to the internet between September and October 2024.
Dark Reading scheduled a virtual event on securing cloud assets in the AI era; no article details were available.
Dark Reading is promoting a virtual event titled 'What Every Enterprise Should Know About Securing Cloud Assets in the Age of AI.' No article text was available, so details such as date, speakers, and agenda are unknown.
Attackers actively exploit Spring Framework RCE CVE-2022-22965 (SpringShell, CVSS 9.8) to deploy webshells; patches 5.3.18/5.2.20 shipped March 31, 2022.
CVE-2022-22965 enables unauthenticated remote code execution in the widely used Spring Framework (CVSS 9.8), which Unit 42 has observed being exploited in the wild. The flaw stems from getCachedIntrospectionResults exposing the class object during parameter binding, letting attackers manipulate the class loader to modify Tomcat logging and upload a JSP webshell. Public PoCs require JDK 9+, Tomcat, WAR packaging, and spring-webmvc or spring-webflux dependencies on Spring 5.3.0-5.3.17, 5.2.0-5.2.19, or older. Fixes shipped in Spring Framework 5.3.18 and 5.2.20; the related Spring Cloud Function flaw CVE-2022-22963 was patched March 29, 2022.
A comparison of twelve managed XDR providers covering pricing models, telemetry breadth, and distinguishing genuine MXDR from rebranded MDR services.
The article compares twelve managed XDR providers including Bitdefender, CrowdStrike, Palo Alto Unit 42, Trend Micro, Fortinet, Secureworks Taegis, Stellar Cyber, Ontinue, and ReliaQuest, highlighting pricing models and telemetry breadth. It explains that genuine MXDR must actively monitor identity, cloud, and email telemetry rather than merely ingest it, and typically costs 30-60% more than endpoint-only MDR. It also notes Sophos completed its approximately $859 million acquisition of Secureworks in February 2025.
Unit 42 archive page for Prisma Cloud product-category articles; contains no new research or announcements.
This Unit 42 archive page lists product-category posts about Prisma Cloud, Palo Alto Networks' cloud security platform for public clouds, SaaS applications and remote users. It contains no new research, incidents, or product announcements.
Unit 42 links Stately Taurus APT activity in ASEAN region and Myanmar to the decade-old Bookworm malware family via infrastructure overlaps.
Unit 42 connected Stately Taurus (aka Mustang Panda) espionage activity targeting ASEAN-affiliated organizations and Myanmar to the Bookworm malware family, first published in 2015. Earlier attacks delivered the PubLoad stager via DLL sideloading, with a PubLoad variant communicating with C2 at 123.253.32[.]15 while mimicking Windows Update URLs. Three previously unreported loader samples from 2021-2022 used UUID-decoded shellcode loaded via heap allocation and API callbacks, ultimately decrypting and loading Bookworm DLLs. A ToneShell backdoor variant shared debug paths with Bookworm loaders, and the January 2024 CSIRT CTI post corroborated the Myanmar attacks.
Study of label leakage and anatomical grounding in multimodal MRI models for Alzheimer's staging shows cognitive-score fusion accuracy of 87.3% is leakage-driven.
The authors train a ResNet18 slice-based encoder with a one-layer Transformer on 1,075 ADNI-1 T1 MRI scans, using FastSurfer segmentations and YOLOv8 localization (mAP_50 above 0.96) as anatomical reference. Grad-CAM shows the image-only classifier often attends to skull and background rather than disease-relevant structures. A CLIP-style image-tabular contrastive framework organized along a label-leakage spectrum yields 87.3% three-way accuracy with cognitive scores versus 73.0% with regional volumes, and cropping to the medial temporal lobe raises image-only accuracy from 58.7% to 65.1%. Results come from single runs on a small balanced test set with reported confidence intervals.
Unit 42 archive page for Code to Cloud platform product-category articles; no new research or announcements.
This Unit 42 archive page lists product-category posts about Palo Alto Networks' Code to Cloud platform, which secures public cloud environments, SaaS applications and remote locations. It contains no new research, incidents, or announcements.
Cyber Security News ranks 2026 server security platforms, favoring Trend Micro for hybrid estates, CrowdStrike for detection, Defender for Azure economics.
Cyber Security News published an editorial ranking of ten server security platforms for 2026, favoring Trend Micro for hybrid estates, CrowdStrike for detection quality, and Microsoft Defender for Servers for Azure-centric economics. The guide stresses that server security licensing differs (per server, per core, or per cloud-hour) and flags hypervisor protection as a commonly missed coverage gap.
OracleZoom enables recursive extreme-scale image super-resolution via reference-constrained on-policy distillation, reducing hallucinations at deep zoom scales.
OracleZoom tackles recursive super-resolution, where repeated feeding of predictions back into the same model leaves deeper-scale outputs unsupervised as required source resolution grows geometrically. The framework trains on its own trajectory while carrying the last ground-truth evidence beyond the supervision boundary, combining direct and cross-scale supervision, a no-reference quality objective, a KL-constrained pretrained latent prior, and EMA consistency. Across seven datasets it achieves state-of-the-art SR quality across zoom scales, averaging 0.713 CLIPIQA with larger gains at deeper scales and significantly reduced hallucinations. Code, data, and models are publicly released.
An editorial scorecard ranks 12 EDR platforms, with CrowdStrike and SentinelOne tied at 8.6/10 and telemetry retention identified as the hidden cost driver.
An editorial comparison scores twelve EDR platforms on detection, response, analyst burden, pricing transparency, and coverage. CrowdStrike and SentinelOne tie at 8.6/10, with Microsoft Defender for Endpoint close behind at 8.5 and described as effectively free in Microsoft 365 E5 estates. The guide argues that telemetry retention, not per-endpoint price, drives real cost, with fully-priced quotes frequently diverging 2-3x from headline rates. Managed detection offerings, including Cynet's bundled 24/7 SOC, factor into the buyer-fit rankings.
FreeFlow is a bias-free hierarchical transformer achieving state-of-the-art optical flow results on Sintel, KITTI-2015, and Spring benchmarks.
FreeFlow replaces task-specific inductive biases like correlation volumes and iterative warping with a single feed-forward encoder-decoder combining window, shifted-window, and reduced-resolution global attention. It reaches 0.68/1.48 EPE on Sintel Clean/Final, 3.23 Fl-all on KITTI-2015, and 3.192 1px on Spring. The architecture scales consistently from small to large variants and remains memory efficient at 1080p inference.
Unit 42 details active exploitation of Exchange SSRF flaws CVE-2022-41080/CVE-2022-41082 via the OWASSRF method, deploying the SilverArrow PowerShell backdoor.
Unit 42 documents OWASSRF, an exploit chain combining CVE-2022-41080 and CVE-2022-41082 to achieve remote code execution on Microsoft Exchange via Outlook Web Access, bypassing Microsoft's ProxyNotShell mitigations. Active exploitation was observed in late November and early December 2022, affecting at least eight organizations. Attackers authenticated to Exchange, then executed a PowerShell backdoor tracked as SilverArrow to create admin accounts, install AnyDesk, tunnel RDP via PuTTY Link, and dump LSASS memory for credential theft. Exploitation is isolated rather than mass-scale because authentication is required.
Case study applies Gaussian and Laplace differential privacy to clinical EEG features, quantifying privacy-utility trade-offs across three deployment scenarios.
Researchers evaluate subject-level differential privacy for EEG-derived feature representations using Gaussian and Laplace perturbations across client-side, centralized server-side, and decentralized local training scenarios. Utility is assessed with statistical measures and a downstream machine-learning check on clinical neurophysiology data. Results show DP can be integrated into EEG workflows, but mechanism choice, privacy parameters, and sensitivity calibration strongly influence data utility, particularly on small and imbalanced clinical datasets. The study highlights the privacy-utility trade-off in protecting biomedical signals against re-identification and inference risks.
Apache Log4j 2 RCE CVE-2021-44228 is actively exploited via crafted JNDI lookups; Palo Alto Unit 42 urges upgrading to Log4j 2.17.1.
Unit 42 details CVE-2021-44228, an easily exploited remote code execution flaw in Apache Log4j 2 where attacker-supplied JNDI lookups in logged user input cause payload download and execution. Massive internet-wide scanning for unpatched systems has begun, with observed follow-on activity including information stealing, Cobalt Strike delivery, and coinmining. The recommended fix is Log4j 2.17.1, which also patches CVE-2021-45046, CVE-2021-45105, and CVE-2021-44832. Widely used Java software including Apache Struts, Solr, Druid, Flink, ElasticSearch, and Spring Boot is affected.
MarkTechPost tutorial implements a hierarchical NeRF in JAX using jax3d volume-rendering primitives for novel-view synthesis and 3D reconstruction.
The tutorial builds an end-to-end hierarchical Neural Radiance Field using JAX, Flax, Optax, and jax3d's volume-rendering functions (sample_along_rays, volume_rendering, sample_piecewise_constant_pdf). It implements positional encoding, skip connections, separate coarse and fine networks, and view-direction conditioning with hierarchical importance sampling. Training uses JAX JIT compilation, Adam optimization, exponential learning-rate decay, and gradient clipping. Evaluation covers PSNR, depth and opacity visualization, 360-degree rendering, and marching-cubes geometry extraction.
Unauthenticated Confluence RCE CVE-2022-26134 was exploited in the wild; Volexity observed intrusions and Cerber ransomware on unpatched servers.
Volexity identified exploitation of CVE-2022-26134, an unauthenticated remote code execution vulnerability in Atlassian Confluence Server and Data Center, during Memorial Day weekend 2022, with Atlassian issuing a patch. Cortex Xpanse found 19,707 potentially affected Confluence instances, concentrated in the US, Germany, China, and Russia, plus 1,251 end-of-life versions exposed. Unit 42 and Cortex Managed Threat Hunting observed successful exploitation leading to reconnaissance commands and a Cerber ransomware deployment that was blocked by Cortex XDR. A public PoC has increased exploitation risk.
Hands-on tutorial implements NVIDIA cuML and RAPIDS to GPU-accelerate scikit-learn-style ML workflows with benchmarking, clustering, and inference.
The tutorial demonstrates NVIDIA cuML as a GPU-accelerated machine learning framework, using cuml.accel to speed up unmodified scikit-learn scripts with zero code changes and the native cuML API for CuPy/cuDF interoperability. It benchmarks CPU versus GPU implementations of PCA, K-Means, nearest-neighbor search, logistic regression, random forests, and DBSCAN on datasets up to 200,000 samples with 64 features. It also builds GPU pipelines with UMAP, t-SNE, and HDBSCAN, validates GPU-generated SHAP explanations, uses the FIL library for forest inference, and covers model serialization and GPU/CPU portability.
TrickBot phishing campaign used SendGrid, fake Google Docs, and Drive-hosted downloaders disguised as Word files to deliver a credential-stealing payload.
Unit 42 identified a TrickBot distribution campaign on November 7-8, 2019, using payroll and annual bonus-themed emails sent from likely compromised .edu addresses through the legitimate SendGrid email delivery service. Emails contained links to Google Docs documents linking to downloader executables hosted on Google Drive, further masked behind SendGrid click-tracking URLs. The downloaders, signed by PERISMOUNT LIMITED and displayed with Microsoft Word icons, show a decoy pop-up and retrieve TrickBot payloads from compromised legitimate domains such as savute[.]in and lindaspryinteriordesign[.]com. The newer TrickBot variant stores its files and configuration under %APPDATA%\cashcore.
NIST catalogued 23 novel security challenges unique to multi-cloud environments and urged the community to develop solutions.
NIST published an analysis identifying 23 distinct security challenges that arise specifically in multi-cloud environments. The agency explicitly encouraged the cybersecurity community to work on solutions for these gaps. The publication reflects growing official concern that spanning multiple cloud providers creates risk patterns not covered by single-cloud security models.
Alloy Taurus (GALLIUM) compromised Southeast Asian government networks from 2022 to 2023 using Exchange web shells and undocumented .NET backdoors Reshell and Zapoa.
Unit 42 tracked persistent multiwave intrusions at a Southeast Asian government starting in early 2022 and continuing through 2023, attributing the activity with moderate confidence to Alloy Taurus (aka GALLIUM), a Chinese state-aligned espionage group. Attackers exploited Exchange Server vulnerabilities to deploy web shells including China Chopper, then ran reconnaissance with Fscan and WebScan, created administrative accounts, and installed undocumented .NET backdoors named Reshell and Zapoa. They established resilience by installing SoftEther VPN, brute-forced Active Directory credentials with Kerbrute, and dumped credential stores with GoDumpLsass and LsassUnhooker. The campaign reflects long-term espionage tradecraft to maintain a foothold.
Researchers release Gander, an end-to-end omni interaction model with full-duplex streaming across video, speech, and text plus agentic capabilities.
Gander is an end-to-end model unifying omni perception, realtime interaction, and agentic capabilities in a single framework, accepting continuously streaming video, speech, and text. It uses a Cerebellum-Brain architecture where the Cerebellum handles realtime conversation and the Brain handles reasoning and agentic tasks, built on a streaming Thinker-Talker design with chunk-level token streams. Internal human evaluations report spoken dialogue on par with SOTA open source models and competitive omni interaction; the models, code, and data are released publicly.