Cyber security

On Tuesday, the US Cybersecurity and Infrastructure Security Agency (CISA) confirmed that hackers have begun exploiting a critical Brotli vulnerability known as Node2Shell, Broccoli2Shell, and HTTP2Shell. [...]

The critical Oracle PeopleSoft bug that ShinyHunters has exploited since May is not one flaw but three chained together, the researchers who reported it said this week. Oracle patched all three under a single identifier, CVE-2026-35273, in June. Its root is a server-side request forgery (SSRF) that reaches an internal management interface because PeopleSoft trusts its own loopback address

The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Tuesday added two vulnerabilities impacting Adobe Commerce and Magento, and Google's Brotli decoder library to its Known Exploited Vulnerabilities (KEV) catalog, citing evidence of active exploitation. The vulnerabilities are listed below - CVE-2026-111497 (CVSS score: 9.2) - An unchecked return value vulnerability in

Article URL: https://arstechnica.com/security/2026/10/code-execution-flaw-in-uefi-firmware-threatens-most-servers-on-planet-earth/ Comments URL: https://news.ycombinator.com/item?id=50265393 Points: 66 # Comments: 14

Critical flaw in EDK2 allows attackers to execute code early in the boot process.

Both critical PHP flaws land on the agency’s exploited list as infosec pros confirm hackers are getting working shells

Article URL: https://www.wiz.io/blog/php2shell-exploitation-so-far Comments URL: https://news.ycombinator.com/item?id=50259343 Points: 74 # Comments: 23

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Tailscale has released version 1.104.4 to fix flaws in its built-in SSH server that could let an attacker reach services and files on other servers that only the root user should be able to touch. The flaws are in how Tailscale SSH forwards network connections, a job the Tailscale background process carries out with root privileges. To use them, an attacker must

arXiv:2608.00643v2 Announce Type: replace Abstract: Command-and-control, data transfer, and censorship circumvention can hide in traffic to widely used services. DNS-bound access control grants permits based on resolved IP addresses, while shared edges route requests by tenant identity, creating a validation gap. An attacker can resolve an allowed anchor, obtain a permit for its shared edge address, and access a hidden tenant by presenting the tenant's name as both SNI and HTTP Host. To investigate this gap, we present the Domain Decoupling Attack (DDA), which exploits this gap in CDN and non-CDN hosting while preserving SNI--Host consistency. Across 1,069,048 domains, we conduct 18,025,068 successful probes. Overall, 95.8% of domains accept an external SNI, and 84.6% return content matching the named tenant. Exposure reaches 99.26% across 506,763 CDN domains and 92.75% across 562,285 non-CDN domains. The co-location graph places 666,413 exposed domains in cross-tenant components; 97.7% of 54,069 cross-tenant non-CDN addresses have a confirmed path to another tenant. None of the tested defenses bind tenant identity to the DNS-approved name. Cleartext inline IPS can block access bas…

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The GMO Group has urged customers to disconnect their systems from the internet and shut down computers after a threat actor who breached the company's Onamae Desktop Cloud threatened to launch a ransomware attack today. [...]

The University of New Mexico Health Sciences Center disclosed a cyberattack that caused system outages and disrupted patient care and academic activities. [...]

Article URL: https://tailscale.com/ssh-investigation-update Comments URL: https://news.ycombinator.com/item?id=50264857 Points: 80 # Comments: 29

One critical, three high-severity EPICS bugs could disrupt research experiments

Cybersecurity researchers have disclosed details of three cyber attacks targeting organizations in Japan in which artificial intelligence (AI) was a key element, either in the driving seat or to assist a human operator. TrendAI, which analyzed three exposed server environments used by threat actors to conduct the malicious cyber operations, described them as distinct from previously published

Microsoft has released out-of-band (OOB) Windows updates to remove trust in certificates tied to compromised eMudhra certificate authority keys, protecting systems that do not receive automatic certificate trust updates. [...]

The Tailscale security team is working to patch almost a dozen security vulnerabilities that could be exploited to steal credentials, crash servers, gain root privileges, and more. [...]

Security updates have been issued by AlmaLinux (bind, bind9.18, brotli, buildah, container-tools:4.0, container-tools:rhel8, firefox, flatpak, freeipmi, gcc, golang, grafana, httpd, kernel, kernel-rt, libreswan, libX11, lrzsz, nodejs:14, nodejs:18, oci-seccomp-bpf-hook, podman, python-urllib3, python3.9, python38:3.8 and python38-devel:3.8, skopeo, thunderbird, xorg-x11-server, and xz), Debian (inkscape, swupdate, thunderbird, and valkey), Fedora (brotli, dolphin, helix, kernel, libical, mingw-python3, nsd, perl-Alien-Brotli, perl-Plack, perl-Plack-Middleware-ReverseProxy, rust-dua-cli, rust-gengo-bin, rust-gitui, stgit, unshield, and webkitgtk), Mageia (evolution, freetype2, ghostscript, kronosnet, libde265, libical, libjxl, packages, perl-DBI, perl-ExtUtils-Typemaps-Default, perl-Imager, vim, and webkit2), Oracle (bind, bind9.18, brotli, buildah, ca-certificates, firefox, flatpak, freeipmi, grafana, httpd, kernel, libreswan, libX11, lrzsz, nodejs22, nodejs24, nodejs:22, oci-seccomp-bpf-hook, perl-DBI:1.641, perl:5.32, postfix, postgresql16-pgvector, postgresql18-pgvector, python3.9, skopeo, unbound, xorg-x11-server, and xz), Red Hat (grafana, grafana-pcp, python3.12-urllib3, and …

Japan's GMO Internet is verifying alleged customer data posted by suspected hackers following a cloud service breach.

CISA has added two new vulnerabilities to its Known Exploited Vulnerabilities (KEV) Catalog, based on evidence of active exploitation. CVE-2026-48356 Adobe Commerce and Magento Unrestricted Upload of File with Dangerous Type Vulnerability CVE-2026-111497 Google Brotli Unchecked Return Value 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 Vulnerabilities and Exposures (CVEs) listed in CISA’s KEV Catalog on publicly exposed assets that grant total control of the asset post-exploitation, while deferring action for lower-risk vulnerabilities. BOD 26-04 further establishes basic expectations for when agencies must check whether threat actors compromised the system before the patch was applied. While BOD 26-04 …

Interesting research: “AI Models Can Provably Hide Arbitrary Capabilities” Abstract: Capability evaluations aim to surface dangerous model behaviors before deployment, but their reliability depends on the assumption that hidden capabilities can be elicited. We show this assumption does not hold under adversarial conditions by constructing backdoor attacks that embed encrypted neural networks within host model weights, decrypting and executing them only upon receiving a secret trigger. Using digital lockers, these hidden circuits remain provably hard to elicit and interpret under cryptographic assumptions, even given full access to model weights, extending prior work from hiding fixed strings to arbitrary computations. We implement our proof of concept constructions in PyTorch and evaluate elicitation through fine-tuning, weight noising, gradient-based trigger search, and latent adversarial training, using a small chemical reaction prediction task as a proxy for CBRN-relevant capabilities. Our results demonstrate resistance to these methods and, together with our cryptographic guarantees, reveal a limit of elicitation-based capability audits. We release our models to support the imp…

A Ukrainian national was sentenced to 70 months in prison for his role in ransomware attacks targeting hospitals, government entities, and high-revenue businesses worldwide between 2018 and 2021. [...]

The U.S. Department of Justice (DoJ) on Tuesday announced the seizure of a domain associated with a bulletproof hosting provider (BPH) named Virtualine. The move was in response to the service being used to commit and facilitate prolific criminal activity, including "the advertisement of sexually explicit images of minors, the intentional disclosure of nonconsensual intimate visual depictions

Japan's GMO Internet Group is offering up to $1 million in total for tips that help catch the attackers who breached its Onamae.com Desktop Cloud service, after refusing to pay an extortion demand. The reward program opened on October 28 and pays only if a tip helps lead to an arrest or an international wanted notice. The service hosts Windows desktops used for FX trading,

arXiv:2610.36108v1 Announce Type: new Abstract: LLM agents increasingly access external tools through the Model Context Protocol (MCP), but the natural-language metadata used to describe those tools creates a prompt-injection surface. Within this established tool-poisoning surface, we study Log-To-Leak, an additive post-hoc logging attack that induces a separate attacker-controlled call after the final legitimate call. Its payload targets the user query, MCP server name, server response, and agent response. We operationalize the injected directive through Trigger, Tool Binding, Justification, and Pressure, and separately measure call success, payload fidelity, and preservation of legitimate behavior. We evaluate five MCP servers and four LLM agents using five metrics spanning effectiveness, utility, and efficiency. Across 18 model-server pairs with valid tool execution, Log-To-Leak achieves an attack success rate (ASR) of 62.64-100% and conditional logging accuracy (LA) of 76.55-95.64%; 16 pairs have absolute target-task completion changes of at most 6.63 percentage points. Three evaluated defenses leave residual ASR above 55% on GitHub MCP with GPT-4o, while an instruction detecto…

arXiv:2610.36145v1 Announce Type: new Abstract: Harvest-now, decrypt-later (HNDL) attacks make the transition to post-quantum cryptography (PQC) urgent for email. This paper presents a systematic measurement that jointly examines PQC deployment across email service stages, negotiation by communicating peers, and usable message encryption. Endpoint-level support alone does not establish PQC readiness across email workflows because submission, relay, and access use independently negotiated Transport Layer Security (TLS) connections. We therefore combine three snapshots of relay, submission, access, and webmail services associated with the Tranco Top~1M domains with controlled tests of mail clients, sending servers, and OpenPGP and S/MIME implementations. Our measurements reveal a transition concentrated among a few providers, with available capability not consistently translating into actual use. Fewer than half of the domains in each service panel support PQC, and Google alone accounts for approximately 87\% of hybrid-capable relay domains. Only two of eight tested sending providers negotiate PQC with our receiver, although five accept it inbound. When TLS groups are restricted to P…

arXiv:2610.36258v1 Announce Type: new Abstract: Multi-turn jailbreaks turn dialogue safety into a trace property: a violation may become identifiable only when user intent and assistant behavior are considered across multiple turns. Existing guard models largely classify individual messages or exchanges and return risk scores or labels, without executable safety semantics or a formally checkable decision trail. We present SpecGuard, a training-free, specification-driven framework for monitoring multi-turn LLM interactions. SpecGuard uses a fixed atomic-proposition contract to map natural-language observations into causally scoped, evidence-backed facts, and expresses forbidden interaction patterns as Linear Temporal Logic specifications. Each specification is compiled into a symbolic finite automaton that incrementally consumes the resulting dialogue trace. The same monitoring mechanism supports buffered runtime checking and retrospective auditing, while accepting runs produce replayable witnesses that identify the triggered specification, supporting facts, and relevant dialogue turns. Experiments on multi-turn safety benchmarks show that SpecGuard consistently outperforms represen…

arXiv:2610.36295v1 Announce Type: new Abstract: Large Language Models (LLMs) rely on proprietary system prompts to enforce task directives, safety policies, and access controls. These prompts are vulnerable to query-based leakage attacks, where black-box adversaries extract confidential instructions through adaptive, multi-turn interactions. Existing defenses often assess queries independently, missing malicious behavior that emerges across interactions. We present AdvGuard, a model-agnostic framework for detecting and mitigating system prompt leakage. AdvGuard models cross-query relationships using a bounded semantic interaction graph, statistically filters candidate components, and converts them into line graphs for graph convolutional network (GCN) classification. This approach captures multi-hop patterns in query similarity that distinguish coordinated extraction from benign workflows. A lightweight prompt-level detector provides protection before sufficient interaction history accumulates, and the framework supports black-box LLM deployments. In mixed-query evaluations, AdvGuard improves recall by up to 36% over the strongest baseline while maintaining a false positive rate of…

arXiv:2610.36334v1 Announce Type: new Abstract: AI-assisted vulnerability discovery can produce technically plausible findings faster than maintainers can validate, coordinate, and safely disclose them. The resulting challenge is not only to establish whether a vulnerability claim is credible, but also to ensure that its supporting evidence, human authorization, intended recipients, and applicable policy remain bound to the same case revision. We present FedTrust-CVDv2, a federated coordinated vulnerability disclosure framework that separates evidence validation, interorganizational coordination, human governance, and permissioned auditing. The framework binds independently signed observations to exact evidence revisions and scopes external actions to approved payloads, audiences, expiry, policy, and revocation state while preserving existing CVE Numbering Authority (CNA) roles. A local reference implementation accepted all 25 valid fixtures and rejected all 650 invalid fixtures across 27 constructed policy families; six single-safeguard ablations admitted 25-75 invalid fixtures. Supporting experiments exercised signed messaging, authenticated encryption, audit certificates, and fi…

arXiv:2610.36422v1 Announce Type: new Abstract: Attack logs and red-team reports show targets the attacks used against them, to help them repair their defenses. Prompt injections against large language models (LLMs) are plain text, so such records also hand targets a working copy. Drawing on social learning theory and work on the victim-offender overlap, we study what targets do with that copy in Tensor Trust, an online game whose players defended LLM-guarded accounts, attacked one another's, and could read every attack they received. Using all 563,349 attack records, we compare each received attack with matched attacks that circulated among similar players at the same moment but never reached the target. Reuse mainly followed success: within a week, targets attacked other players with 10.0% of the attacks that had broken their defense, versus 0.03% of matched attacks (adjusted difference: 8.8-10.0 percentage points). Near-misses, whose replies began with "access granted" but that scored as failures, were reused about as rarely as failures: reuse tracked whether an attack paid off, not how its reply read, consistent with payoff-biased social learning. Breaches were also followed by…

arXiv:2610.36612v1 Announce Type: new Abstract: Hardware malware detectors (HMDs) classify hardware performance-counter measurements to identify malicious execution. Faults in their decision logic or parameters can weaken detection and allow malware to be classified as benign. We investigate this vulnerability through structural fault injection across a design space comprising 18 classifiers, four counter budgets, and AdaBoost and Bagging ensembles. The simulation evaluates 453,174 decision stuck-at and selected parameter bit-flip events on a 7,400-instance. Primary comparisons use 128 completed configurations. These completed-subset results are distinguished from the simulation summaries covering 140 configurations with enumerable fault sites. Fault outcomes are classified by their security consequences, including evasion, false-alarm increases, and metric silence. A fault is critical when malware recall decreases by at least five percentage points. Tree-based models exhibit a lower mean critical-fault fraction than function-based models, 5.3% versus 14.3%; exhaustive-only analysis preserves this ordering. Moreover, 72.3% of evaluated tree faults are metric-silent, changing both r…

arXiv:2610.36711v1 Announce Type: new Abstract: Reliable evaluation is a critical bottleneck in privacy red-teaming of large language models (LLMs): determining whether a jailbreak response actually reveals personal information can be difficult when disclosures are indirect, contextual, partial, or obfuscated. Existing evaluation approaches increasingly rely on guard models and LLM-as-Judges, yet these evaluators may interpret the same response differently. To better characterize this evaluation setting, we conduct a systematic study of privacy evaluators and find substantial disagreement, particularly in ambiguous cases that require additional evidence or targeted analysis to resolve. Motivated by these findings, we introduce \textsc{PrivacyEvalClaw}, a training-free deliberative agent for evaluating privacy leakage in LLM jailbreak responses. Rather than relying on isolated single-pass judgments, PrivacyEvalClaw treats evaluators and analysis modules as tools, adaptively gathers evidence, investigates uncertain disclosures, and reconciles conflicting signals before producing a final judgment. Our primary experiments use pairwise LLM-as-Judge evaluation of complete trajectories, s…

arXiv:2610.37467v1 Announce Type: new Abstract: AI chatbot platforms have become one of the most popular web interfaces users interact with online, routinely receiving personal and intimate information shared under an expectation of privacy. Yet, on the web application side, these platforms have the ability to embed third-party analytics, advertising, and session replay scripts that operate silently alongside the chatbot, creating an underexamined channel for conversational data leakage towards third parties. We conduct the first systematic large-scale measurement study of contextual leakage in AI chatbots, auditing the web interfaces of 42 general-purpose and domain-specific (health, legal, and education) platforms. Beyond standard network interception, we instrument the browser at the JavaScript engine level to attribute each data flow to the exact user action that triggered it, and the DOM capture mechanism used to retrieve its content, a granularity invisible to network-layer analysis alone. We find that 21 of these platforms leak conversation titles to third-party trackers, while nine leak verbatim user prompts. Beyond content, we observe a substantial amount of chatbot platfo…

arXiv:2610.37657v1 Announce Type: cross Abstract: We introduce Heads of Security (HoS), a prompt injection defense that enforces instruction-data separation via a small set of learned per-head attention gates. HoS learns how each head should redistribute attention between trusted and untrusted tokens, enabling models to reason over untrusted content without following injected instructions. We evaluate HoS on Llama-3.3-70B-Instruct and GPT-OSS-20B. We compare it against SecAlign++, a state-of-the-art finetuning-based defense, and ASIDE, a defense that, like ours, builds instruction-data separation into the model architecture. We show that HoS offers greater robustness to adaptive attacks, better performance on standard utility benchmarks, and matches top performance on standard agentic prompt injection benchmarks. More specifically, the black-box RL-Hammer attack reaches 97% ASR against GPT-OSS-20B and 85% against SecAlign, but only 10% against HoS. Claudini, a state-of-the-art white-box attack, strengthened against HoS through autoresearch, requires 3 times more FLOPs to reach the same ASR on HoS as it does on GPT-OSS-20B or SecAlign. HoS preserves base-model utility across standar…

arXiv:2607.07062v2 Announce Type: replace Abstract: Monero is a privacy-focused cryptocurrency that deploys the Dandelion++ protocol and incorporates anonymity networks (such as Tor and I2P) to prevent malicious attackers from linking transactions with their source IPs. In this paper, we demonstrate that Monero's integration of the Tor network introduces a fundamental vulnerability: a Monero Tor node's originated transactions are exclusively forwarded to two outgoing Tor hidden service nodes (proxy nodes) prior to clearnet propagation, enabling an adversary to capture originated transactions by occupying the target node's outgoing connections. Based on this observation, we propose \textit{ProxyMark}, a three-stage deanonymization framework for the Monero Tor network, comprising node role identification, originated transaction identification, and node location deanonymization. Through experiments on the live Tor network, Monero mainnet, and testnet, we empirically demonstrate the effectiveness of \textit{ProxyMark} in successfully deanonymizing transactions originating from Monero nodes over Tor.

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Article URL: https://foxio.io/blog/choose-your-backend-three-tls-bugs-in-goahead Comments URL: https://news.ycombinator.com/item?id=50263701 Points: 35 # Comments: 4

Article URL: https://cloudsleuth.io/blog/php2shell-litellm-gitlab-find-what-you-run/ Comments URL: https://news.ycombinator.com/item?id=50261583 Points: 18 # Comments: 0

University hospitals once again accepting patients after initial ambulance diversion, but recovery to continue in phases

Article URL: https://www.propublica.org/article/zohar-pinhasi-monstercloud-ransomware-indictment Comments URL: https://news.ycombinator.com/item?id=50260960 Points: 45 # Comments: 6

Attackers are increasingly abusing legitimate IT tools, Microsoft 365 sessions, and everyday workflows to compromise businesses without triggering traditional defenses. Huntress Labs ranks the threats hitting organizations hardest, highlighting which attack techniques deserve immediate attention and which remain emerging risks. [...]

Article URL: https://www.reuters.com/business/media-telecom/alleged-israeli-spy-company-heavily-targeted-starlink-users-sources-say-2026-10-27/ Comments URL: https://news.ycombinator.com/item?id=50259050 Points: 45 # Comments: 3

We are launching a PHP Capture the Flag challenge integrated with our Bug Bounty program to test our WAF protections. Security researchers are invited to bypass our defenses and capture the flag to help make the Internet safer.

View CSAF Summary Successful exploitation of these vulnerabilities could allow an attacker to execute arbitrary code (CVE-2023-4863), bypass authentication (CVE-2026-16436 and CVE-2026-16437), or perform arbitrary operations (CVE-2026-16438), resulting in information disclosure, tampering with, destruction, or deletion of information, and a denial-of-service (DoS) condition of the system. The following versions of Mitsubishi Electric GENESIS, GENESIS64, ICONICS Suite, Hyper Historian, AnalytiX, MobileHMI, IoTWorX, MC Works64, GENESIS32 and BizViz are affected: Mitsubishi Electric GENESIS64 >=10.97| =10.97| =10.97| =10.97| =10.97| =10.97| =10.97| =10.97| =10.97| =10.97| =10.97| =10.97| =10.97| =10.97| =10.97| =10.97| =10.97| =10.97|<=10.97.2 Product Status: known_affected Remediations Mitsubishi Electric GENESIS: <=11.03 Product Status: known_affected Remediations Mitsubishi Electric GENESIS64: <=10.97.3 Product Status: known_affected Remediations Vendor fix Mitsubishi Electric is releasing fixed version 10.98 or later for GENESIS64, ICONICS Suite, Hyper Historian, AnalytiX, and MobileHMI. Please download the fixed version from the link below and install it: "https://iconicsinc.my.s…

View CSAF Summary Successful exploitation of these vulnerabilities could allow an attacker to cause a denial-of-service condition, corrupt memory, disclose sensitive information, or potentially execute arbitrary code. The following versions of EPICS Base are affected: EPICS Base release <=7.0.10 (CVE-2026-114595, CVE-2026-114596, CVE-2026-114597, CVE-2026-114598) CVSS Vendor Equipment v3 9.8 The EPICS Community EPICS Base release 3 Vulnerabilities Integer Overflow or Wraparound, Improper Handling of Length Parameter Inconsistency, Access of Resource Using Incompatible Type ('Type Confusion') Background Critical Infrastructure Sectors: Critical Manufacturing Countries/Areas Deployed: Worldwide Company Headquarters Location: Global Vulnerabilities Expand All + CVE-2026-114595 In EPICS Base release 7.0.10 and prior, an integer overflow in network request processing can cause memory to be allocated with an incorrect size. Subsequent handling of attacker supplied data may result in memory corruption, denial of service, or potential remote code execution. Read More 1 Affected Product The EPICS Community EPICS Base release: <=7.0.10 Product Status: known_affected Remediations Mitigation T…

Fake login pages are nothing new, but generative AI is making them easier to build and more convincing. Attackers can recreate familiar login screens, impersonate trusted brands and tailor phishing attempts to specific employees or organizations. Some fake login pages go beyond stealing passwords. They can also capture MFA codes or hijack authenticated sessions, allowing attackers to gain