Cyber security

The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Tuesday added four vulnerabilities to its Known Exploited Vulnerabilities (KEV) catalog, including four vulnerabilities impacting Plex Media Server that's collectively called Plex2Shell. The vulnerabilities are listed below - CVE-2026-96652 (CVSS score: 5.3) - Plex Media Server Server-Side Request Forgery (SSRF)

Certificate authority eMudhra revoked eight compromised intermediate certificates after researchers found their private keys were so weak that anyone could recover them almost instantly and use them to forge trusted certificates for legitimate websites. [...]

Intermediate certs allow anyone to mint web credentials for any Internet server.

The private keys of eight eMudhra intermediate certificate authority (CA) certificates are compromised, Mozilla and Google's Chrome Root Program confirms on October 20. An intermediate CA signs the certificates that websites present, so anyone holding one of these keys could issue a certificate for any website that a browser would accept. A researcher reported the

Article URL: https://scotthelme.co.uk/eight-bits-of-trust-emudhras-ca-keys-cracked-in-milliseconds/ Comments URL: https://news.ycombinator.com/item?id=50177916 Points: 122 # Comments: 52

Unknown threat actors breached TeamUpdraft's website and potentially gained unauthorized access to customers' connection keys for UpdraftCentral, UpdraftVault, and UpdraftClone, using them to backdoor WordPress sites. TeamUpdraft is the developer behind UpdraftPlus, a popular WordPress backup plugin with over four million active installations. The vendor also offers UpdraftCentral, a remote

State Bank of India has identified 3,897 customer records containing personal information in a set of about 375,000 records available on the dark web, and it does not yet know where the data came from. The state-owned bank, India's largest, said in a stock-exchange filing dated October 21 that it "has experienced an incident involving the loss of certain data." The count is

PHP will ship an out-of-cycle security release at 14:00 UTC today, October 21, for two critical vulnerabilities that its security team has rated 9.2 on the CVSS v4.0 scale but has not described. Security researchers at watchTowr say the two flaws allow remote code execution. Only the four supported PHP branches, 8.2 through 8.5, can receive the fix, and no exploitation has been reported so far.

Unconfirmed report claims PHP2Shell exploit remotely executes code on PHP sites.

A threat actor breached TeamUpdraft's website, a developer of popular WordPress backup and security plugins, potentially compromising UpdraftCentral connection keys that can send commands to connected websites. [...]

Article URL: https://arstechnica.com/security/2026/10/meta-muse-exposes-users-personal-and-business-secrets-when-they-share-conversations/ Comments URL: https://news.ycombinator.com/item?id=50174687 Points: 65 # Comments: 12

Article URL: https://fulcrumsec.vg/pingcap/ Comments URL: https://news.ycombinator.com/item?id=50173716 Points: 26 # Comments: 2

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Article URL: https://krebsonsecurity.com/2026/10/feds-suspect-ransom-negotiator-ran-shinyhunters-extortion-site/ Comments URL: https://news.ycombinator.com/item?id=50173487 Points: 52 # Comments: 12

Following the discovery that eight eMudhra intermediate certificates use weak keys, Cloudflare is deploying mitigations and releasing client updates. We explain the impact, our response, and what customers and developers should do next.

The PHP security team has let it be known that there is a high-stakes security update coming at 14:00 UTC on October 21. "All PHP users are encouraged to prepare now so they can upgrade as soon as the release is available". Anybody running a PHP site probably needs to be prepared for this one.

The PHP security team is warning administrators to prepare for emergency security updates tomorrow to address two critical vulnerabilities, as information about the flaws has reportedly leaked ahead of their scheduled disclosure. [...]

Article URL: https://news-web.php.net/php.announce/509 Comments URL: https://news.ycombinator.com/item?id=50172041 Points: 97 # Comments: 19

Meta says it paused a Muse feature that lets you share conversations with the AI assistant after researchers found the URLs publicly available on the web, as reported by Ars Technica. In a report published this week, researchers at the security firm Claroc say they found more than 6,800 Muse links through public DNS records. "People have the ability to share specific Muse artifacts, which creates a page that can be accessed by those with the link," Muse spokesperson Tracy Clayton says in an emailed statement to The Verge. "However, we've paused this functionality while we review this report and consider changes to how these links can be dis … Read the full story at The Verge.

Unit 42 investigates network compromises across numerous industries

Palo Alto Networks has disclosed that it's continuing to observe exploitation of a now-patched security flaw impacting PAN-OS and Prisma Access by ransomware actors. The activity relates to CVE-2026-0257 (CVSS score: 7.8), an authentication bypass flaw that could be exploited by bad actors to set up unauthorized VPN connections. It was patched by Palo Alto Networks in May 2026 and was

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A Chinese-speaking criminal pointed autonomous AI agents at company websites and let them break in with almost no help, and a security researcher watched it happen because the operators left their control panels open on the internet. The agents tried more than 1,200 sites and reached websites belonging to more than 100 companies, including farm-equipment maker Deere, appliance company

Article URL: https://emudhra.we-have-a-problem.com/ Comments URL: https://news.ycombinator.com/item?id=50166579 Points: 57 # Comments: 16

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Staffing software giant calls in CrowdStrike as customers face login headaches and questions remain over possible data theft

CISA has added six new vulnerabilities to its Known Exploited Vulnerabilities (KEV) Catalog, based on evidence of active exploitation. CVE-2026-96652 Plex Media Server Server-Side Request Forgery (SSRF) Vulnerability CVE-2026-96654 Plex Media Server Improper Neutralization of Encoded URI Schemes in a Web Page Vulnerability CVE-2026-96655 Plex Media Server Server-Side Request Forgery (SSRF) Vulnerability CVE-2026-96656 Plex Media Server External Control of File Name or Path Vulnerability CVE-2026-106931 EG Secure Solutions SiteGuard Server Edition OS Command Injection Vulnerability CVE-2026-110936 Siemens Software Center Uncontrolled Search Path Element Vulnerability These types of vulnerabilities are a frequent attack vector for malicious cyber actors and pose significant risks to the federal enterprise. Binding Operational Directive (BOD) 26-04: Prioritizing Security Updates Based on Risk establishes vulnerability management requirements for Federal Civilian Executive Branch (FCEB) agencies. BOD 26-04 reinforces the importance of the KEV Catalog and requires federal agencies to prioritize rapid remediation of high-risk vulnerabilities, specifically those identified by Common Vulne…

Advisory at a Glance Title #StopRansomware: SafePay Ransomware Original Publication October 20, 2026 Executive Summary This advisory details recent activity by the SafePay ransomware group. SafePay actors have been highly active since August 2024, targeting businesses and critical infrastructure across North America, South America, Europe, and Australia. SafePay actors typically gain access to networks by stealing or guessing passwords, exploiting vulnerabilities in security systems, and using phishing tactics. Once inside the network, SafePay actors establish control by creating new accounts or taking over existing ones. They then use legitimate system tools to move through the network, identify valuable files, and disable security protections to avoid detection. Following, they encrypt the victim’s files, making them inaccessible, and leave a ransom note demanding payment in cryptocurrency. This advisory urges organizations to follow recommended security measures to reduce the risk and impact of SafePay ransomware attacks. Affected Products CVE-2020-3259 [Common Weakness Enumeration (CWE)-200: Exposure of Sensitive Information to an Unauthorized Actor] CVE-2023-20269 [CWE-288: Au…

French cloud and hosting provider OVHcloud is warning users that attackers compromised its open-source command-line interface (CLI) tool to distribute information-stealing malware. [...]

Ahold Delhaize, one of the world's largest food retail chains, confirmed that last week's cyberattack disrupted services at stores across Europe and the United States. [...]

Justin.sh is reporting on a confidential Cellebrite document that has been leaked to him: Cellebrite calls it Advanced Unlocks (AU from here on), not to be confused with the “advanced unlocking services” they’ve marketed for years. A press release from earlier this year confirms AU is a new product for 2026. […] According to Cellebrite, AU: is a “next-generation AFU vector that is more resilient to Apple’s OS changes” works with Stolen Device Protection enabled, which tightens USB restrictions is enabled by a dedicated appliance with a stated range (!) of about 8 meters. AU = Advanced Unlocks, Cellebrite’s term. AFU = after first unlock.

arXiv:2610.27533v1 Announce Type: new Abstract: Machine learning benchmarks act as guideposts for model development and spur the creation of training datasets intended to improve benchmark scores. We introduce BenchDoor, a family of data poisoning attacks that exploits this incentive. Beyond preserving benign performance, BenchDoor requires benchmark gains that encourage adoption of data that also implants a backdoor. The adversary either manipulates a benchmark's training or test data, creating an adversarial benchmark, or supplies an independent training dataset while leaving the benchmark unchanged. We formalize five attack scenarios, including training on rewritten test examples and applying similarity-based decontamination. Across multiple-choice Q&A, text classification, and open-ended Q&A with Qwen and Gemma models, BenchDoor achieves positive benchmark gains for all 30 evaluated configurations, with held-out attack success rates of 82.33% to 100.00% at poisoning rates of 2% to 10%. Both objectives remain achievable after synthetic data generation and similarity-based decontamination, with attack success rates of at least 90.33%. These findings show how benchmarks can serve …

arXiv:2610.27620v1 Announce Type: new Abstract: Autonomous LLM agents act through tools under per-action authorization: a local guard screens each tool call in isolation. We show that local authorization does not compose into global authorization. A compositional authorization failure (CAF) is a locally authorized execution, or a pair of locally authorized executions, that violates a global policy spanning intent, purpose, provenance, consent, and delegation. We characterize CAFs along two axes, expressiveness (single-trace safety versus relational k-safety) and observability (a ladder of monitor profiles). Our central result is an impossibility: relational purpose violations form a 2-safety hyperproperty with no per-trace locus of blame, so a per-action monitor that never raises a false alarm detects none of them, independent of the underlying model or decision procedure; they become visible only under cross-execution monitoring, which none of the six guardrails we survey implements. We make this constructive with AL-SYNTH, a SAT/SMT synthesizer (using no language model) that emits minimal CAF witnesses, each checked against an exhaustive oracle. The empirical signature is sharp: …

arXiv:2610.27653v1 Announce Type: new Abstract: Watermarking has emerged as a key tool for identifying text generated by large language models (LLMs), with current schemes embedding statistical signals into the generation process to enable later detection. In this work, we identify a shared weakness across a broad class of popular LLM watermarking methods, including KGW (and its variants), GumbelSoft, DipMark, ITS, and SynthID. We show that these schemes exhibit a fundamental link between their detection scores and the token probability shifts they introduce during generation. This link, which we call score-ratio alignment, allows an attacker with only black-box query access to the model--and no knowledge of secret keys or model weights--to produce text that evades detection while remaining fluent and natural. We prove that the resulting attack is optimal across all covered watermark families, and show that the weakness is intrinsic: any watermark designed to maximize statistical detection power necessarily induces the very structure that attackers can exploit. We evaluate our attack on seven popular generative LLM watermarking schemes, three LLMs, and tasks, which reduce detection…

arXiv:2610.27766v1 Announce Type: new Abstract: The UK, EU and US governments have set timelines for post-quantum cryptography migration of critical systems, with deadlines ranging from 2028 to 2035. This paper focuses on IoT-class devices and microcontrollers and the viability of using PQC to connect these devices in secure TLS 1.3 connections. Using wolfSSL, we benchmark a 36-combination TLS 1.3 algorithm matrix, pairing ML-KEM-512/768/1024 and X25519/ECC P-256 key exchange with ML-DSA-44/65/87, Ed25519, ECDSA, and RSA-PSS authentication, across four devices (Raspberry Pi Pico W & Pico 2 W, ESP32, and a Raspberry Pi Zero), measuring both handshake latency and energy consumption. We found that in capable devices, all choices in the TLS matrix gave similar results, but that in IoT-class devices, PQC performance is highly implementation- and architecture-dependent: the common assumption that elliptic-curve key exchange must be cheaper than post-quantum lattice-based key exchange does not hold in this wolfSSL-based implementation, where the best full-PQC combination (ML-KEM-512 + ML-DSA-44) completes TLS handshakes 41% faster than the equivalent classical-modern pairing (X25519 + RSA…

arXiv:2610.28364v1 Announce Type: new Abstract: Local Retrieval-Augmented Generation (RAG) systems are vulnerable to indirect prompt injection and retrieval poisoning, where malicious instructions in retrieved content are mistaken for trusted input. We present nokast-secureRAG, a roughly 0.5B-parameter small language model that acts as a semantic firewall between retrieval and generation. It jointly evaluates the user query and retrieved context, classifying the pair as safe, suspicious, or malicious. The model is trained using a teacher-judge-student pipeline: a 35B teacher generates 5,233 examples across four attack families, and an independent 120B judge re-labels them, achieving 95.0% agreement before student fine-tuning. On a held-out in-distribution test set, the model achieves 0.994 detection recall at a 0.026 false-positive rate and a 0.006 attack-success-rate proxy, outperforming a regex baseline, a public prompt-injection classifier, Llama Guard 3 1B, and its untuned version. Prompt-Guard-86M reaches 0.900 recall but has a 0.690 false-positive rate. On a judgment-flip test, where the same sentence is benign or malicious depending on context, the model correctly classifies…

arXiv:2610.28397v1 Announce Type: new Abstract: Agentic AI extends large language models (LLMs) from generating responses to planning and executing complex workflows, substantially expanding their utility while exposing applications to unsafe actions, information leakage, and adversarial manipulation. Multi-agent systems further expand these capabilities through specialization and collaboration, but distributed authority, heterogeneous roles, and opaque or potentially compromised participants make safeguarding even more challenging. Existing defenses address important individual threats but provide fragmented coverage across local execution, system-level interactions, and enforcement mechanisms. We introduce MAS-Guard, a unified framework that closes this gap for safeguarding single- and multi-agent AI applications containing both instrumentable and opaque agents. Within instrumentable agents, the proposed local Agent Guardrail (A-Guard) layer applies task-specific experts to assess agentic events. At the system level, developer-owned Agent Charters and a Control Plane combine deterministic structural checks of routes, agent capabilities, and message formats with semantic assessmen…

arXiv:2610.28401v1 Announce Type: new Abstract: We present SPECTER, a post-compromise covert channel that uses host-side USB power control to exfiltrate information from air-gapped and network-segregated systems. A transmitter with administrative privileges encodes bits through USB power-management or device-state operations without placing the payload in USB data transfers. The resulting signals are recovered through three alternative receiver paths based on smartphone charging states, visible peripheral behavior, and near-field RF activity. Experiments on Windows 10 and Ubuntu 22.04 demonstrate the channel on commodity hardware, with charging-state signaling at 0.2-0.25 bit/sec across Android and iOS devices and peripheral-state signaling at 1.0 bit/sec using a USB mouse on Windows. RF reception is demonstrated using a software-defined radio with a loop antenna in direct contact with the USB cable. Channel availability and observable side effects depend on the host configuration, connected device, and receiver path. These results identify host-side USB power control as a mechanism for low-rate exfiltration of short secrets and motivate treating USB power-management and device-sta…

arXiv:2610.28425v1 Announce Type: new Abstract: Modern LLM agents persist state across sessions via two channels: long-lived memory files silently prepended to the system prompt, and scheduled tasks waking the agent without user input. A one-time indirect prompt injection committed to either channel can re-fire across sessions long after the attacker leaves, threats we term carryover attacks. Existing prompt-injection benchmarks evaluate attacks only in the session where malicious content is first observed, leaving the gate governing when and how often a planted payload later re-fires unmeasured. We present CarryoverBench: 12 personal-assistant scenarios and 101 attack tasks across three trigger channels: Instant, same-turn IPI; Autonomous, heartbeat-scheduled; and Latent, memory-resurfaced. A rule-based verifier scores planting and triggering as independent stages. Across five frontier models, planted payloads re-fire without measurable decay over five rounds; conditional on successful planting, the trigger stage often provides little additional protection. Porting the Latent channel to a second runtime, Hermes, attenuates but does not eliminate the effect, suggesting that carryov…

arXiv:2610.27210v1 Announce Type: cross Abstract: Speech models are increasingly used as an interface to AI systems, from transcription tools to voice agents. Existing audio backdoors require an attacker to introduce triggers at inference time. We study a different threat model in which the attacker compromises the model during fine-tuning but has no access to the victim's inference-time inputs. We introduce the Speaker-Activated Backdoor (SAB) setting, in which a target speaker's natural voice serves as the trigger. We develop a two-phase fine-tuning method that first makes speaker identity more accessible and then binds the target speaker to an attacker-chosen payload. Compared with a one-phase baseline with the same training budget, the two-phase method substantially improves selectivity and clean performance, and is especially important for content-dependent attacks. SAB achieves 90.2% and 97.0% backdoor success on Whisper-medium and Parakeet, with false-positive rates of 1.7% and 0%, respectively using as little as two minutes of real audio from the target speaker. We further demonstrate content-dependent semantic rewriting and downstream tool-use attacks, where malicious inst…

arXiv:2610.27304v1 Announce Type: cross Abstract: Large language models are deployed globally, yet safety alignment and evaluation remain concentrated in English: harmful requests refused in English can elicit unsafe completions when translated into low-resource languages. We evaluate ten widely deployed LLMs across 79 languages (English plus 78 low-resource) under a translation-bypass threat model, using a metric conditioned on English safety, which separates translation bypass from unsafety already present in English. English safety does not transfer reliably: conditioned on safe English completions, mean bypass rates range from 21.9% to 44.4%. Bypass risk concentrates in a subset of language families, a pattern broadly shared across models. The shared ordering is confounded with translation degeneracy, but its variation across models is significant and survives every control we apply. We also show that per-model bypass rates do not identify a stable ranking: nine of ten models change rank across three conditioning schemes that estimate the same quantity, with no change to any underlying response.

arXiv:2610.27548v1 Announce Type: cross Abstract: When an LLM agent acts on behalf of a user, it is expected to act within the authorization scope the user grants. Existing agent evaluations largely measure task completion or harmful consequences and can therefore overlook actions that violate this delegation without producing conventional safety or privacy harms. We introduce AuthorizationBench, a benchmark of authorization alignment grounded in documented real-world cases. A scalable construction pipeline produces 286 executable tasks spanning situational triggers, the presence or absence of direct harmful consequences, and ten application domains. We execute every task with four models at two reasoning-effort settings across three agent harnesses in an authorization-aware sandbox that keeps authorized and out-of-authorization paths executable and observable, yielding 6,864 trajectories. Agents act out of authorization in 19.2% of trajectories, with rates ranging from 10.5% to 26.6% across the 24 configurations. Task completion does not imply authorization. Increasing reasoning effort leaves the aggregate rate nearly unchanged, with effects varying across models. On controlled pa…

arXiv:2610.27574v1 Announce Type: cross Abstract: Multi-agent systems are increasingly deployed to coordinate multiple large language model (LLM) agents. However, this also creates new attack surfaces: malicious agents may have chances to exploit the coordination. In this paper, we propose and study the \textit{show-up attack}, in which a malicious subagent manipulates the supervisor into involving it in tasks beyond its assigned scope. To evaluate this risk, we propose SUA-Arena, which implements 6 attack strategies and contains 188 test cases. Then, we evaluate 6 frontier LLMs and find that all of them are vulnerable to show-up attacks. For example, GPT-5.6-Sol as a supervisor suffers an ASR of up to 0.93. Mitigation strategies such as prompting and restricted communication fail to reduce the risk consistently. These results show that multi-agent systems need explicit mechanisms for enforcing authority boundaries.

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Article URL: https://research.poh.org/bot-benchmarking-2026/ Comments URL: https://news.ycombinator.com/item?id=50169506 Points: 12 # Comments: 0

If you know for sure that a website flagged as suspicious is actually safe, you can mark it as such. | Image: Google Google is launching a new browser safety feature for Chrome that aims to keep you better informed about how malicious a website might be before you open it. The new suspicious site warnings, available when Chrome's Enhanced Protection is on, build on a similar two-stage system introduced for Chrome file downloads in 2024, which provides visually different notifications for blocked files based on whether they're determined to be "suspicious" or "dangerous." For the Chrome site warnings, the feature will flag a website as suspicious if it detects that it has similar qualities to other sites associated with phishing, malware, and scams. Google … Read the full story at The Verge.

From October 26, only high and critical cases stay private as project seeks help sharing the workload

Article URL: https://kaba.cx/posts/20261020_Tor/ Comments URL: https://news.ycombinator.com/item?id=50166257 Points: 36 # Comments: 10

Security updates have been issued by AlmaLinux (environment-modules, kernel, pcs, perl-URI, python3.14-urllib3, and webkit2gtk3), Debian (python-django), Fedora (bind, bind-dyndb-ldap, chromium, cifs-utils, curl, haveged, python3.15, qt5-qtbase, rust-rbw, rust-routinator, rust-rustls, xorg-x11-server, and xorg-x11-server-Xwayland), Mageia (firefox, firefox-l10n, nss, flatpak-builder, imagemagick, libpng, libxi, libxpm, libxtst, openssh, postgis, and thunderbird), Oracle (emacs, environment-modules, libsoup, perl-URI, python3.14-urllib3, webkit2gtk3, and xorg-x11-server), Red Hat (go-fdo-client, go-fdo-server, golang, kernel, kernel-rt, openssh, postgresql:16, postgresql:18, and rust-sequoia-sq), SUSE (alsa, AusweisApp, chromedriver, ffmpeg-4, kubernetes, libsoup2, nvidia-open-driver-G07-signed, p11-kit, perl-Net-OAuth, perl-Net-Whois-Raw, pgvector-devel, pi-coding-agent, podman, python, python3, python3-base, python3-doc, python315, python36, thunderbird, and velociraptor), and Ubuntu (cifs-utils, curl, golang-1.22, libxtst, openssh, openssh-gssapi, and php8.5, php8.3, php8.1, php7.4, php7.2, php7.0, php5).

View CSAF Summary Successful exploitation of these vulnerabilities could crash the Windows kernel. The following versions of HMS Networks PEAK-System PCAN Windows drivers are affected: PEAK-System Device Driver Setup <=5.1.2.1151 (CVE-2026-109576, CVE-2026-101103, CVE-2026-94188, CVE-2026-103672, CVE-2026-110322, CVE-2026-105960) PCAN Windows CAN device drivers <=5.1.2 (CVE-2026-109576, CVE-2026-101103, CVE-2026-94188, CVE-2026-103672, CVE-2026-110322, CVE-2026-105960) CVSS Vendor Equipment v3 7.1 HMS Networks PEAK-System Device Driver Setup 5 Vulnerabilities Out-of-bounds Write, Buffer Copy without Checking Size of Input ('Classic Buffer Overflow'), Improper Validation of Array Index, Untrusted Pointer Dereference, Improper Handling of Length Parameter Inconsistency Background Critical Infrastructure Sectors: Transportation Systems, Healthcare and Public Health, Energy, Critical Manufacturing Countries/Areas Deployed: Worldwide Company Headquarters Location: Sweden Vulnerabilities Expand All + CVE-2026-109576 The parser in PEAK-System PCAN driver correctly detected the malformed record, but the loop iterating the record list advanced its processed-bytes counter even when a record …

View CSAF Summary Two vulnerabilities in the Web-Based Management (WBM) interface of WAGO CC100, PFC100 G2, PFC200 G2, TP600, Edge Controller and WP400 devices allow an authenticated low-privileged user to bypass intended privilege boundaries. The issues affect both the routing configuration functionality and the authorization model for PROFIBUS configuration management. The following versions of WAGO OS Linux are affected: WAGO Firmware (vers:semver/>=1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0| =1.0.0|<4.10.0 (70)) installed on WAGO H…

View CSAF Summary Hitachi Energy is aware of vulnerabilities that affect RTU500 product versions listed in this document. These vulnerabilities if exploited can have impact on confidentiality, integrity and availability of the product. Please refer to the Recommended Immediate Actions for information about the mitigation/remediation. The following versions of Hitachi Energy RTU500 Product are affected: RTU500 series CMU Firmware vers:RTU500_series_CMU_Firmware/>=13.5.1| =13.6.1| =13.7.1| =13.8.1| =12.7.1|<=12.7.7 (CVE-2026-17539, CVE-2026-28388, CVE-2026-6732, CVE-2026-6653, CVE-2026-6276, CVE-2026-9079, CVE-2026-11856, CVE-2026-8927, CVE-2026-8932, CVE-2026-17539, CVE-2026-28388, CVE-2026-6732, CVE-2026-6653, CVE-2026-6276, CVE-2026-9079, CVE-2026-11856, CVE-2026-8927, CVE-2026-8932, CVE-2026-17539, CVE-2026-28388, CVE-2026-6732, CVE-2026-6653, CVE-2026-6276, CVE-2026-9079, CVE-2026-11856, CVE-2026-8927, CVE-2026-8932, CVE-2026-17539, CVE-2026-28388, CVE-2026-6732, CVE-2026-6653, CVE-2026-6276, CVE-2026-9079, CVE-2026-11856, CVE-2026-8927, CVE-2026-8932, CVE-2026-17539, CVE-2026-28388, CVE-2026-6653) CVSS Vendor Equipment v3 8.8 Hitachi Energy RTU500 series CMU Firmware 7 Vulnerab…

View CSAF Summary Hitachi Energy is aware of multiple vulnerabilities that affect MicroSCADA X SYS600 product versions listed in this document. These vulnerabilities can be exploited to carry out various attacks on the product. Please refer to the Recommended Immediate Actions for information about the mitigation/remediation. The following versions of Hitachi Energy MicroSCADA X SYS600 Product are affected: MicroSCADA X SYS600 vers:MicroSCADA_X_SYS600/<=10.7, 10.8 (CVE-2026-9852, CVE-2026-9853, CVE-2026-9854, CVE-2026-9853) CVSS Vendor Equipment v3 7.8 Hitachi Energy MicroSCADA X SYS600 2 Vulnerabilities Improper Neutralization of Formula Elements in a CSV File, Incorrect Implementation of Authentication Algorithm Background Critical Infrastructure Sectors: Energy Countries/Areas Deployed: Worldwide Company Headquarters Location: Switzerland Vulnerabilities Expand All + CVE-2026-9852 A CSV injection vulnerability exists in SYS600. Injected malicious formulas can add or modify data to the spreadsheet, insert links, exfiltrate data, and in some cases, depending on how the user has their environment configured, execute malicious code on the user’s machine. To exploit this issue attack…