A new flaw in the Linux kernel's KVM virtualization code for ARM64 processors can leave a freed piece of host memory exposed to a guest virtual machine on hosts with nested virtualization enabled. The bug, tracked as CVE-2026-89775, allows a guest to read and write host kernel memory, and the researcher who found it says it can be used to escape the guest and run code on the host machine.
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Malware already running on a Mac can quietly take over Meta's Muse assistant and use the broad access its owner granted the app, security researcher Patrick Wardle has shown in a proof-of-concept released on September 21. It works by changing a hidden setting so that when the user taps the microphone and dictates a prompt, the words go to the attacker instead of Meta. The flaw is in
Three researchers at the security firm Hacktron used Anthropic's Claude Opus 5 to chain two flaws and take over the ChatGPT and Codex accounts of several OpenAI employees, then reach an internal OpenAI code repository. The chain began with a bug in the software that runs OpenAI's public help forum and moved through a weakness in OpenAI's own login system. This was security research,
Flock reveals little about where its license plate readers are assembled, but the answer could have geopolitical and cybersecurity implications.
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Tuesday, September 22
The response header, Vary , has been called “ the ugliest part of HTTP that we haven't yet improved. ” The same post describes it as a “horrible, kludgy mechanism” with “pretty abysmal interoperability” across intermediaries. That is usually where sensible engineers back away slowly with their hands raised. That’s not exactly an endorsement of Vary , but ugly doesn’t mean useless. One URL can have more than one correct response. A server might, for example, deliver different image formats to different browsers. If a cache ignores Vary , it risks serving the wrong bytes to a request. But if it treats every raw header value as distinct, a handful of similar requests can spread into thousands of barely reusable cache entries. Vary tells a cache which request fields may affect the response, but it does not tell the cache which differences actually matter. Vary support is now available in Cache Rules on every plan. The origin still names the request headers that may affect a response, but you decide how Cloudflare handles each one. You can normalize known negotiation headers, pass exact values through when those small differences matter, or bypass cache when the variation is too unpredictable. The origin declares what may vary, and you decide how much variation is actually meaningful for the cache. How Vary works Vary is a standard HTTP response header that tells intermediary caches (like Cloudflare) which request fields may affect the response sent by the origin. Sites use Vary to serve d
Recent findings on a DPRK-nexus campaign, tracked as Operation Conflict Compass and attributed to Konni. Looks aimed at gauging the medium-term trajectory of the Russia-Ukraine war. → Early August 2026, targeting Ukraine-focused individuals and organizations → Spear-phishing emails with ZIP attachments containing LNK files disguised as PDFs → Lures: Strait of Hormuz food-price fallout, Russia-Ukraine peace negotiation frameworks, and social researcher resumes — pointing to diplomatic entities, think tanks, and NGOs as targets → LNK runs a VBScript that sets persistence via a scheduled task, firing a PowerShell script every minute → Payload (we're calling it VelvetCake) is a modular downloader with no fixed capability set built in — it continuously pulls and runs server-side PowerShell modules, so operators can change functionality without redeploying → Infra: South Korean/Ukrainian sites for lure hosting, GitHub for staging, Medianewsonline for C2 → Attribution: targeting pattern, VelvetCake's code characteristics, shared infrastructure, and time zone alignment with known Konni activity
Talaria, a fast, zero dependency Linux privilege escalation and posture auditor built for blue teams and DevSecOps
I built this because I kept running into the same headaches when assessing Linux hosts or playing CTFs. Every time you need to check a system for local privilege escalation, the go to tools are massive shell scripts like LinPEAS that take 5 to 10 minutes to run, spawn hundreds of subshells, write temp files to /tmp, and dump thousands of lines of colored text with cleartext credentials scrolling right past your screen. On top of that, traditional shell scripts frequently miss complex, real world human misconfigurations. Because of performance limits and basic shell regex, they mostly stick to simple checks like standard GTFOBins SUIDs, basic crontabs, or kernel versions. They end up blind to deeper operational flaws, like dangerous Polkit JavaScript rules in rules.d, systemd EnvironmentFile overrides, $ORIGIN dynamic linker hijacks, PAM chain backdoors, or plaintext tokens leaked inside /proc/\[pid\]/environ. If you are on a sensitive production machine, a hardened enclave, or trying to automate checks inside a CI/CD image build pipeline, that is just too noisy, slow, risky, and blind to realistic attack paths. Talaria tries to fix that with four main things: 1. Zero dependencies and read only safety It is written in 100% pure Go with zero third party packages in go.mod, and CGO is disabled. It compiles into a single static binary you can drop onto any Linux box, even minimal containers or scratch environments without Python, Bash, or GCC. It opens all system files with O\_RDONLY, never writes to /tmp, and finishes full system scans in milliseconds (<15ms to 800ms). 2. An attack graph instead of a wall of text Traditional scripts dump a massive list of individual findings that you have to manually connect in your head. Talaria links individual misconfigurations, like a writable systemd unit, an insecure PATH in a script, or a Polkit rule, into a directed graph and calculates the highest probability path leading to root. The goal is showing defenders the exact link to fix to break the entire chain. 3. Built for defense and remediation (audit mode by default) Instead of just showing offensive GTFOBins exploit commands, it runs in audit mode by default. It masks harvested tokens and passwords, maps findings to CIS Benchmarks and NIST SP 800-53 controls, provides copy paste remediation commands (chmod, chown, config directives), and exports native SARIF or JSON for GitHub Code Scanning and SIEMs. (A quick note for purple teamers and CTF players: you can pass the --ctf flag to switch off credential masking, enable deep ELF string auditing, and get instant GTFOBins exploit one liners for lab targets.) 1. Advanced scanners for subtle vectors Rather than generic heuristics, Talaria includes 45+ specialized scanners that parse complex subsystem configurations: Polkit JavaScript Engine (rules.d): Evaluates custom .rules definitions to detect unauthenticated root action authorizations (polkit.Result.YES) and known Polkit bugs. Systemd Deep Auditing: Traverses unit drop-ins, timer schedules, and writable EnvironmentFile definitions that allow environment variable poisoning in root services. ELF Dynamic Linker Auditing: Analyzes SUID and custom binaries for relative RPATH/RUNPATH entries and $ORIGIN directory path traversals that allow shared library hijacking. Kernel and Memory: Checks kernel security configs (/boot/config-\*, /proc/config.gz), scrapes unprivileged /proc/\[pid\]/environ entries for leaked cloud/API tokens, and spots hijacked live tmux or screen sockets. It is completely open source under the MIT license. No company behind it, just a project I built because I needed something faster, safer, and cleaner for real systems. I used AI as responsibly as I could during development, tested it across many different scenarios myself, and enforced strict code standards to keep the codebase clean. I am not a seasoned veteran developer, but it has worked reliably for me in CTFs and real life labs, so I am sharing it with the community. You can see my test lab screenshots in assets directory in project repository If you do Linux hardening, detection engineering, or golden image builds for your team, I would genuinely like to know your thoughts. I would like to also hear thoughts of offensive users purple teamers and CTF players this started as a offensive tool tbh Code: [https://github.com/cetinkayaismail/talaria-privesc](https://github.com/cetinkayaismail/talaria-privesc) Releases: [https://github.com/cetinkayaismail/talaria-privesc/releases](https://github.com/cetinkayaismail/talaria-privesc/releases) Docs: [https://github.com/cetinkayaismail/talaria-privesc/blob/main/docs/RULES\_CATALOG.md](https://github.com/cetinkayaismail/talaria-privesc/blob/main/docs/RULES_CATALOG.md)
We analyzed 338 million attack simulations in production. Perimeter defense blocks 69% of attacks, but post-compromise blocking drops to 37%. AMA.
Hi r/cybersecurity! We're the **Picus Labs Research Team**, and we're here for an AMA. For the **Blue Report 2026**, we analyzed more than **338 million attack simulations** run in production environments between January and June 2026, mapped to the MITRE ATT&CK® framework. The headline finding for 2026: prevention recovered to **69% at the perimeter**, its 2024 peak. But for the first time, we measured what happens after an attacker gains authenticated access, and **only 37% of their actions get blocked**. Key findings from the research: * Quiet discovery and collection actions get blocked **one time in ten**. Attackers who stay quiet can collect credentials **almost undetected.** * **58% of attacks get logged, but only 14% trigger an alert.** Logging is at a four-year high, which means the evidence is sitting in your SIEM, nobody's turning it into detections. * Same tool, wildly different outcomes: Mimikatz is blocked **94% of the time against LSASS memory**, but just **3% against the registry**. Defenses recognize the signature method, **n**ot the behaviour itself. We're here to talk about **perimeter and post-compromise defense**, **detection engineering**, **stealth techniques**, **where defenders should focus first**, or anything else the 338M data points can answer. Ask us anything! **Participants:** * Dr. Suleyman Ozarslan, Co-founder and VP of Picus Labs (u/malware_bender) * Sila Ozeren Hacioglu, Security Research Engineer (u/sila-ozeren) * Umut Bayram, Associate Security Research Engineer (u/umut_bayram_picus) [Proof Photos](https://imgur.com/a/proof-photos-r-cybersecurity-ama-Zp7vk4Z) We'll be here on September 22, 2026, answering your questions. [Blue Report 2026](https://picussecurity.com/hubfs/BlueReport2026/Picus-BlueReport2026.pdf)
Penetration testing for third-party risk works best as a deeper assurance layer for suppliers whose compromise would meaningfully affect the enterprise, not as a blanket requirement. Tier vendors by data access, system access, operational weight, and external exposure, then match testing depth and cadence to that tier. Combine vendor-supplied reports, enterprise-commissioned tests, and shared platforms depending on the relationship. Get written authorization first, scope the test to the product and integration that matter, and feed validated findings into remediation plans and risk scores. The post Penetration Testing for Third-Party Risk Management Programs appeared first on Synack .
Nothing is worse than testing out a change that works in staging, only to see it behave differently in production. That’s why we wanted to give you an environment that’s as close to production as possible — so you can battle-test your changes and make sure they behave exactly as you expect them to. Agents are helping us push more lines of code than ever before, and larger changes mean more ground needs to be tested ahead of release. Ideally, that testing is done in a way that doesn’t slow agents down , but gives them the tools to take on more of the development lifecycle. That’s why today we’re launching Worker Previews . Each Git branch gets a production-like place to run, with its own code, configuration, URL, observability, and state. So now, for every change in your codebase, you can: Deploy an isolated Preview with npx wrangler preview , using its own variables, secrets, and bindings, separate from production configuration and traffic. Share a stable Preview URL for the branch so that every push updates the same running Preview where you can send requests, click through the UI, and test runtime responses. Isolate Durable Objects and Containers per branch, keeping state changes, sessions, memory, migrations, and concurrent tests scoped to that Preview. Inspect logs, errors, metrics, and traces for that Preview to confirm the change works, catch failures, push a fix, and verify it before production sees it. Start from the Preview configuration you set, so each Preview begins with a copy of the variables, secrets, bindings, and settings you define — just like a code branch starts from main . We call
Security teams have spent decades asking whether an identity has too much access. AI agents raise a harder question: how can we determine which paths an autonomous system can discover, given the access it already has? A person may try several ways to complete a task. A deterministic application follows the flow its developer wrote. But an AI agent is relentless in its pursuit of done. In May
Attackers are exploiting a new flaw in on-premises VeloCloud Orchestrator (VCO), the server that manages the Edge devices in a VeloCloud SD-WAN, Arista said on September 22. The flaw, tracked as CVE-2026-93952, may allow a remote attacker with no login access to privilege internal functions and affect the VCO host. Only orchestrators set up to authenticate their Edges with certificates are
When the Digital Operational Resilience Act (DORA) became enforceable across the European Union in January 2025, it triggered an administrative sprint. Financial entities spent the first year establishing risk governance, assessing third-party service providers, updating contract clauses, and documenting incident escalation workflows. Now in its second year, the harder part of DORA is
A new flaw in the Linux kernel's KVM virtualization code for ARM64 processors can leave a freed piece of host memory exposed to a guest virtual machine on hosts with nested virtualization enabled. The bug, tracked as CVE-2026-89775, allows a guest to read and write host kernel memory, and the researcher who found it says it can be used to escape the guest and run code on the host machine.
A SharePoint Server vulnerability that Microsoft initially classified as a spoofing flaw with a CVSS score of 6.5 actually enables authenticated remote code execution, according to full technical details published today by Viettel Cyber Security researcher Dinh Ho Anh Khoa. The flaw, CVE-2026-65660, affects SharePoint Server 2016, 2019, and Subscription Edition. Patches have been
Cisco Talos researchers created a new framework for identifying malware and hacking tools that rely on AI chatbots—and quickly discovered something unusual.
A malicious npm package named "indexed-btree" has been observed hiding its malicious behavior within application code rather than using lifecycle scripts, indicating that threat actors are likely shifting tactics in response to recent security controls. "Indexed-btree is a malicious npm package mimicking the legit sorted-btree package, an ordinary B-tree/indexing utility," Checkmarx said. "
I reverse-engineered Intel's NPU stack and got custom C kernels running on its programmable SHAVE cores
Your conversations with AI chatbots are both highly personal and deeply vulnerable to surveillance. Here’s how you can protect yourself.
CVE-2026-59309 & CVE-2026-59310: patch-diffing VMware vCenter reveals two pre-auth 9.8 bugs - an auth bypass and a syslog path traversal to RCE
The threat actor known as SideCopy has been observed using spear-phishing lures to target academic institutions in India, expanding their strategic focus beyond government entities. "SideCopy campaign operations typically initiate through spear-phishing campaigns that leverage the abuse of mshta.exe to execute malicious scripts and circumvent standard security protocols," Trellix researchers
Hey everyone, I’m black-210, the main developer of VULTURE. I started VULTURE around RF and SDR analysis, but over time it became much bigger than that. I wanted to build a platform where RF/signal processing, scientific computing, machine learning, digital forensics, chemistry, physics, mathematics, visualization, and research workflows could exist together instead of having each part live as a completely separate project. So VULTURE is now a modular intelligence and research platform, with Python APIs, a CLI, an optional PyQt6 GUI, analysis frameworks, reproducible/offline workflows, reporting and provenance, and a separate native C layer. What VULTURE actually covers RF / SDR / IQ FFT and FFT-engine workflows PSD analysis spectrograms and waterfall visualization signal detection peak and burst detection occupancy analysis noise-floor analysis interference and anomaly analysis IQ loading and handling IQ recording and playback workflows metadata and calibration boundaries resampling and signal-processing utilities receive-oriented SDR integration boundaries RTL-SDR / PlutoSDR / UHD-USRP / SoapySDR compatibility boundaries where the required drivers are available RF-DNA and RF fingerprinting capture comparison and fingerprint reports Scientific computing RF wavelength calculations free-space path-loss calculations physics calculations mathematics utilities spectroscopy-related calculations NMR / Larmor-frequency calculations material and electromagnetic-property screening complex-permittivity calculations deterministic simulation profiles numerical and statistical analysis AI / ML / analytics VULTURE also has an AI/ML side rather than treating machine learning as an afterthought. It includes areas for: feature engineering preprocessing model evaluation classical machine-learning workflows optional deep-learning components optional ONNX-related workflows clustering anomaly detection statistical analysis time-series analytics model/feature pipelines explainable feature reports offline benchmarking human review of analytical results The goal is to make ML another analysis layer that can work with the scientific and signal-processing parts of the platform. Forensics / evidence / auditing There is also a forensic layer for working with supplied data and evidence metadata. It includes: physics audits chemistry audits mathematics audits protocol/frame audits structured JSON reports human-readable reports SHA-256 capture/file hashes provenance metadata case IDs and sample IDs authorization metadata bounded inputs fail-closed validation audit/review fields reproducible analysis information The forensic side is intended to make analytical results easier to review and reproduce rather than pretending that a software output automatically proves attribution or identity. Chemistry / physics / materials The Chemical-RF side is another part of the project. For example, VULTURE can work with: NMR/Larmor calculations spectroscopy-related workflows RF/material screening complex permittivity conductivity-related calculations electromagnetic material calculations resonance-related calculations combined physics/RF calculations These are primarily local scientific calculations and research tools, not replacements for physical laboratory measurements. Visualization and GUI VULTURE can run completely from the terminal, but it also has an optional PyQt6 interface. The GUI provides surfaces for things such as: RF intelligence SDR/IQ workflows machine-learning workflows RF-DNA/fingerprint review provenance review visualization analysis results The GUI is optional, so the core platform can still be used headlessly. Quantum / research experiments There is also an experimental research layer. Some of the work includes: QFT-style versus classical FFT comparisons quantum-inspired experiments small variational/research experiments simulated noise and robustness experiments reproducible seeds classical baselines for comparison scientific experimentation that does not require quantum hardware This is experimental research functionality, not a requirement for normal VULTURE usage. VULTURE C One part I don't want to leave out is the C extension layer. Inside the same repository there is a separate c/ directory containing VULTURE C, a native C11 layer designed to complement the Python platform. It is intentionally independent and can be compiled separately. The C layer currently includes things such as: signal statistics mean / variance / standard deviation RMS median range peak-to-peak measurements local peak detection statistical thresholds SHA-256 hashing of files and memory buffers RF wavelength calculations free-space path-loss calculations deterministic command-line analysis JSON-like/offline reporting a text-to-C tool translator reusable C APIs standalone C analysis engines strict C11 compilation explicit memory ownership fail-closed error handling dependency-light native utilities For example, the C layer contains separate native programs for general analysis, RF analysis, hashing, and the tool translator. It can be built independently with: make -C c I wanted this layer because some parts of the platform make sense as small deterministic native components rather than everything being implemented in Python. So the repository isn't just a Python RF script with a C file added somewhere. The C directory is intended to be a real native extension layer with its own API, tools, build system and documentation. Reproducibility and security model A major design goal of VULTURE is that analysis should be reviewable and reproducible. The platform includes things such as: deterministic offline fixtures reproducible seeds capture/file hashing provenance metadata structured reports explicit case/sample identifiers bounded inputs validation controlled hardware boundaries operator-review fields fail-closed behavior The receive-side hardware integrations are intentionally separated from the offline analysis workflows. VULTURE is receive/analyze-only by design. It does not provide jamming, spoofing, unauthorized interception, credential theft, exploitation, evasion, or automatic RF transmission. It is intended for systems, frequencies, receivers and datasets that the operator owns or is explicitly authorized to analyze. Linux distribution support Another thing I'm genuinely proud of is that VULTURE has moved beyond just being a repository on my GitHub. It is currently packaged in BlackArch as: vulture-black BlackArch's official repository: https://github.com/BlackArch/blackarch BlackArch is an Arch Linux-based distribution for penetration testers and security researchers, and its repository contains thousands of security tools. VULTURE has also been added to the Pentoo overlay as: net-wireless/vulture Pentoo's official overlay: https://github.com/pentoo/pentoo-overlay Pentoo describes this repository as its Gentoo security-tools overlay and the heart of the Pentoo LiveCD. Getting VULTURE packaged by security-focused Linux projects was honestly one of the coolest milestones for me. It means the project can exist in real security-oriented Linux ecosystems rather than only being something people clone directly from my repository. Where the project is GitHub: https://github.com/black-210/VULTURE Codeberg backup: https://codeberg.org/black-210/VULTURE I'm keeping the Codeberg repository as an independent backup as well. I'm still actively developing VULTURE, and there is a lot I want to improve. Some parts are mature, some are experimental, and some are still being expanded. I'm sharing it here because I'd genuinely like feedback from people working in defensive security, digital forensics, RF/SDR, signal processing, machine learning, scientific computing, or open-source research. If you were working on a platform like this, what would you add next? Are there analysis workflows, forensic capabilities, ML features, RF features, or research tooling that you think would be particularly useful? Thanks for taking a look. — black-210
Malware already running on a Mac can quietly take over Meta's Muse assistant and use the broad access its owner granted the app, security researcher Patrick Wardle has shown in a proof-of-concept released on September 21. It works by changing a hidden setting so that when the user taps the microphone and dictates a prompt, the words go to the attacker instead of Meta. The flaw is in
A new flaw in WordPress core let an anonymous visitor leave a comment that planted a hidden script on the page. If a logged-in administrator later opened that page, the script could run code on the site's server. WordPress fixed the flaw, tracked as CVE-2026-93485 and called "Comment2Shell," on September 17 in version 7.1.1 and told site owners to update right away. There is
A flaw in ValidateOAuthState can allow unauthenticated OAuth state CSRF/login-CSRF due to an empty-state collision.
Two things happened last week, one day apart, and almost nobody connected them. On 11 September, the EU Cyber Resilience Act’s vulnerability reporting obligations came into force. Companies covered by the regulation now have to report actively exploited vulnerabilities within 24 hours and provide a fuller notification within 72. On 12 September, Anthropic CEO Dario […] The post Slow is a design principle, not a delay appeared first on Heimdal Security Blog .
Monday, September 21
Looks like the API security page may be compromised? https://api-security.owasp.org/ Edit: looks like the original site is back up https://owasp.org/API-Security/
A fake LastPass Authenticator installer offered on GitHub installs a Windows kernel driver that shuts off antivirus and other security software before a password stealer runs if a victim downloads and runs it, researchers at LastPass and Delphos Labs said on September 17. Microsoft's own hardware-compatibility program signs the driver, scored zero detections on VirusTotal when researchers
The North Korean threat actors behind the Contagious Interview campaign have compromised at least 30,000 devices located in more than 100 countries and siphoned funds or account credentials from over 7,000 cryptocurrency wallets, according to a new joint cybersecurity advisory. The primary targets of the campaign are individual web designers, engineers, and specialists in cryptocurrency,
Google has been fined €403 million for breaking the EU's data protection law, the GDPR, in the way three of its features handled people's location data from May 2018 to February 2020. Ireland's Data Protection Commission (DPC), Google's lead regulator in the EU, also ordered the company to make its processing comply with the law within 6 months. The DPC has not said publicly which
Reverse Engineering ZTE SmartHome App Led to an Account Takeover Affecting the Entire Account Backend. 4 CVEs
A browser. A plugin. A package. A login screen. Normal stuff. That is basically the problem this week. The trouble keeps showing up inside things people already trust: code that takes a bad turn, old payloads coming back, exposed systems, weak checks, fake fixes, and attack paths that look almost too easy. Even the research side is getting messy, with more findings, more automation, and not
Cybersecurity researchers have disclosed details of a new campaign dubbed TASK#STOMP that delivers a PowerShell backdoor designed to harvest sensitive data from compromised hosts. The backdoor "automatically harvests and exfiltrates business documents, watches the filesystem for new files in real time, steals Wi-Fi passwords and clipboard contents, takes screenshots, and accepts arbitrary
MSRKit - Tool for calling kernel functions and mapping unsigned drivers from user mode using BYOVD (AmdTools64.sys)
We introduced Python Workers two years ago, providing a way to run Python applications in the Cloudflare Workers runtime. Our goal was to make it as simple to write Workers in Python as it is in TypeScript, and to make the ecosystem of Python packages and frameworks “just work”. Today, Python Workers are now generally available (GA). What does GA mean? It means Python is now a first-class, fully supported language on the Cloudflare Developer Platform. You can bring the Python code, libraries, and design patterns you already know and connect them seamlessly to Workers AI, R2, D1, Hyperdrive, Durable Objects, Queues, Workflows, and the rest of the Cloudflare platform. You can also run popular Python frameworks like FastAPI, Django, and Flask inside Python Workers. You can even create a Python Worker inside another Worker using Dynamic Workers . The journey behind Python Workers Bringing Python to Cloudflare Workers was a natural choice. Because Workers has supported WebAssembly since 2018 , it gave us the perfect environment to run a Wasm-compiled Python interpreter. By using Pyodide , we were able to quickly support a wide range of Python applications in Cloudflare Workers. Our goal was to create the first platform for infinitely scalable Python apps, while making it as easy and performant as developing Python apps anywhere else. The features we are highlighting today are the result of this multi-year effort. Many developers are already building applications within Python Workers
Born out of academia and raised in corporate IT departments, the Security Assertion Markup Language (SAML) authentication protocol continues to be a staple in these organizations. However, it’s time for it to retire. With the rise of software-as-a-service (SaaS) companies in the late aughts, IT departments needed a way for users to authenticate to many new web services. SAML and the burgeoning single sign-on (SSO) industry fulfilled this need. However, SAML is being crushed under the weight of its own complexity. It’s time to deprecate it and move on to modern alternatives like OpenID Connect (OIDC). In this post, I will explore the design-by-committee origin of SAML, its progression through the ranks in academic and corporate environments, its slow disintegration at the hands of the security research community, and its (hopeful) deprecation in favor of newer protocols. SAML 101 What’s insidious about SAML is that it really is mostly straightforward to understand, but it’s built on a foundation of sand, bone dust, and ash; it works … if you assume XML signature validation is reliable. But XML signature validation is deeply cursed, and is so complicated that most fielded SAML implementations are wrapping libxmlsec, a gnarly C codebase nobody reads. — Thomas Ptacek, 2023 SAML and the birth of the SSO industry Wikipedia tells me that “SAML is an
Officials discussed setting up a mechanism for the two countries to notify each other of AI incidents which could threaten national security.
Author here. The post describes three memory-safety bugs which have been in Godot since v1.0 and v3.0. All three are still present in current releases. The bugs can affect exported games that load community-authored data files. Godot allows attackers using maliciously crafted files to trigger reads or writes past the end of a buffer, inside the process running the game. The post includes the response from Godot maintainers who deny this is a security issue, and my reply to them. Happy to give more information about the bugs or the audit if there are questions.
Threat actors are leveraging ClickFix-like lures to deliver a previously undocumented remote access trojan (RAT) called ChainScript. "ChainScript has appeared under multiple build names, including ComponentTask33, UpdateDigital, HostShared, and OrchidViolet66, while presenting itself as Spotify, Zoom Workplace, and Microsoft Teams software," Blackpoint Adversary Pursuit Group (APG)
To reduce the amount of noise from questions, we have disabled self-posts in favor of a unified questions thread every week. Feel free to ask any question about reverse engineering here. If your question is about how to use a specific tool, or is specific to some particular target, you will have better luck on the [Reverse Engineering StackExchange](http://reverseengineering.stackexchange.com/). See also /r/AskReverseEngineering.
This short blog post is about abusing a privilege escalation bug that Microsoft recently fixed in Windows, CVE-2026-66804, that I and 14 others reported. This issue is an incomplete fix for CVE-2026-50343, a bug dubbed “Dark Elevator” by Calif. The root cause of the bug was a dangling COM object registration for the CrossDevice COM object with the CLSID {E9F83CF2-E0C0-4CA7-AF01-E90C70BEF496}. A COM registration typically needs two parts: a server executable, which for in-process components is a DLL and a CLSID entry under the HKEY_CLASSES_ROOT registry key which points to that DLL.
The North Korean threat actor known as Jade Sleet has been attributed to the compromise of an India-based "much smaller organization" in the information technology (IT) services industry, once again highlighting how the adversary continues to target developers to breach target networks. Cybersecurity company SentinelOne, which disclosed details of the activity, said it involved the use of Apple
Open Season on Kapibala: Attacker Steals Over 18,000 Government Records Through WordPress Exploitation
GreyNoise has been tracking malicious use of an IP address since early June 2026 due to its frequent use in scans and attacks against a variety of technologies. We detail a few of the more notable intrusions we observed including the theft of more than 18,000 sensitive records from a western government.
Sunday, September 20
Saturday, September 19
Three researchers at the security firm Hacktron used Anthropic's Claude Opus 5 to chain two flaws and take over the ChatGPT and Codex accounts of several OpenAI employees, then reach an internal OpenAI code repository. The chain began with a bug in the software that runs OpenAI's public help forum and moved through a weakness in OpenAI's own login system. This was security research,
BragJack - $20K in bounty rewards from Anthropic, Perplexity, Google, Microsoft and Opera Using 1 Extension
# [](/r/cybersecurity/?f=flair_name%3A%22News%20-%20General%22)Hi folks, my name is Gal Weizman, I do browser security research. Excited to finally share my recent work, where I managed to hack Chrome, Comet, Edge, Opera and Claude in Chrome using one single browser extension 2 CVEs & $20,000 in bounties 🙂 Hope you like it!
Identity visibility is a starting point for modern identity security, because stolen and misused credentials are among the most frequently reported initial access vectors in breach research, including Verizon's annual Data Breach Investigations Report. This article explains what identity visibility means in IAM, why cloud and multicloud environments complicate it, which capabilities matter in
AI labs are toying with an industry-wide pact to slow development. Meanwhile, widely available AI chatbots are already helping uncover a tidal wave of security flaws.
Every VPN says it’s the best, but only some of them are telling the truth.
As dozens of cities end contracts for its controversial license plate readers, Flock is rolling out a voluntary severance program, WIRED has learned.
Friday, September 18
Cloudflare operates at a scale so big that even after working here for years, it doesn’t seem real. We have thousands of servers all over the world with petabytes of RAM and millions of CPU cores, and all of it is pushed to the max. As vast as those resources feel, they are still finite, and when you need every service to run on every node, it doesn’t leave room for wasted space. At this scale, small improvements are greatly magnified, so even 1%-at-a-time improvements are worth celebrating. And some tweaks add up to a lot more: in this post, we’ll look at how small changes to a single algorithm reduced the memory footprint of one of our Pingora-based services significantly. That allowed us to reclaim more than 100TB of RAM globally, on top of the 100TB of memory the DNS team was able to shed last month . Waste not Maintaining equitable resource sharing between teams is not easy, especially in large organizations. One of the ways Cloudflare ensures the balance is kept is through the tireless efforts of the wonderful Performance team. This story starts with a ticket filed by Ivan who found: Excessive memory usage from pingora-ketama in Pingora Backend Router . The finding was that our internal load-balancing service, Pingora Backend Router (yes, PBR), was using significantly more memory than expected — specifically in structures associated with pingora-ketama, which is our open-source library for handling consistent hashing. In order to talk about ho
Exclusive: Official UK security assessment found Microsoft cloud platform storing files was at potential risk from hostile hackers Vast troves of highly sensitive police data are lying on Microsoft cloud platforms which an official UK security assessment deemed to be vulnerable to “compromise” by foreign actors and the US government, a Guardian investigation can reveal. The files include criminal records, victim statements, internal emails and sensitive information held by more than 40 police forces across the UK. Continue reading...
TeamPCP pulled off the worst-ever software supply-chain hacking spree and breached thousands of companies. Now Google’s threat intelligence group says it had a mole inside the hackers’ inner circle.
After three months of daily anti-government protests—dubbed the Flamingo Revolution—the sudden mass suspension of Instagram accounts has led to fears of brigading against demonstrators.
Security firms have published numerous blog posts describing how they pointed their agent harness at a codebase and found dozens of bugs ( we’re one of them ). However, these posts tend to focus on agentic code review, which is just one aspect of how we use AI in our security reviews. We want to give a different perspective: before code review even starts, agents now allow us to build custom tooling and formal models that improve the quality and depth of our reviews. We recently reviewed the Miden VM, a new zero-knowledge VM with its own custom assembly language and almost no developer tooling. To prepare, we spent six months having our agents build an LSP server , a decompiler , a static analysis engine , and a Lean model of the VM executor from scratch. These tools found real security issues, like an unvalidated prover-supplied input that would let a malicious prover forge Falcon signatures and steal funds from Miden account holders. Additionally, the Lean work produced 95 machine-checked correctness proofs, covering a large component of the Miden core library. Auditing the Miden zkVM In late 2025, the Miden team came to us to have parts of their zero-knowledge VM reviewed before launch. Part of the review was scoped to cover the Miden core library, which contains a small set of cryptographic primitives written in a custom assembly language called Miden as
In this post, we examine two vibe-coded credential harvesting platforms, Loot and UltraVault, and the Amazon Bedrock abuse used to validate stolen secrets.
Thursday, September 17
Overview Dokploy versions 0.29.8 and 0.29.11, as well as commit 24b02f5 on the canary branch, are vulnerable to OS command injection during the backup creation and restoration processes. The vulnerability stems from unsanitized shell command construction that can allow an attacker to escalate privileges and lead to full compromise of the target device. Description Dokploy is an open-source Platform as a Service solution for deploying applications and databases on self-hosted servers. Dokploy allows authenticated users to create and schedule database backups and restore previously created backups. These backup operations are executed by the Dokploy process, which runs with root privileges by default. Dokploy is vulnerable to OS command injection in its database backup creation and restoration functionality due to insufficient sanitization of user-controlled input before it is incorporated into shell commands. The vulnerable backup functionality constructs database-specific shell commands that directly interpolate a user-supplied database name, while the restore functionality incorporates a user-supplied backupFile value into a shell command. Both operations ultimately pass the resulting command to a shell execution helper that invokes /bin/bash as a child of the Dokploy process, without shell escaping or restrictions on shell metacharacters. The affected parameters are exposed through tRPC procedures that only validate that the supplied values are non-empty strings. Consequently, authenticated users with permission to perform database backups can supply shell metacharacters that are interpreted by /bin/bash , resulting in arbitrary command execution on the Dokploy host with the root privileges of the Dokploy se
Model adopting ‘jailbreak-like instructions’ among six more cases as firm reveals framework for tracking AI misalignment OpenAI has disclosed six more examples of “unexpected or concerning” behaviour by its technology, as it warned that the pace of development could not continue at “maximum speed for much longer” responsibly. In one of the new cases reported by OpenAI, an unreleased research model inserted “jailbreak-like instructions” into its own notes to disregard its normal constraints and told itself to be “freed from the roles and identities that bind other chatbots”. Continue reading...
Flock reveals little about where its license plate readers are assembled, but the answer could have geopolitical and cybersecurity implications.
How Brutus grew into an engine that finds your identities, tests them everywhere they’re accepted, and remembers what it confirms. An attacker rarely needs a novel exploit when a valid username and password pair is sitting in a breach dump, reused across a dozen internal services, or left at a vendor default nobody changed. Brutus started as a focused credential testing tool. It has since grown into something broader: an engine that finds the identities attached to an organization, tests them everywhere they might be accepted, and carries what it confirms forward into future runs. All of it runs automatically as part of the pipeline. There’s no manual setup and no analyst kicking off individual checks. Here’s what changed. Knowing who works there Testing a credential assumes you already know the account exists. Brutus now builds that picture from more places. A new people enumeration subsystem maps organizational exposure using professional identity data, drawing on an Apollo.io connector built with a split discover and enrich flow so the full org roster isn’t revealed automatically. A LinkedIn Sales Navigator connector adds another path for personnel discovery. Microsoft 365 enumeration is now a first class command in its own right rather than something reachable only from inside another mode, and it supports rotating proxies. GitHub email enumeration through rotating proxies is also fixed: the CSRF session handshake no longer stalls or fails quietly, and progress is visible while the session is being established. Two smaller changes make the output easier to work with. Generated usernames now carry the first and last name that produced each candidate, so nothing downstream has to reverse engineer a person’s name from the loca
Wednesday, September 16
A modern storefront can look perfectly healthy while malicious JavaScript works underneath: siphoning affiliate revenue, hijacking searches and clicks, tampering with analytics, or asking a remote server what to execute next. Pages load, products appear, and checkout works — yet the browser may be quietly doing something the site owner never authorized. That is the blind spot our Client-Side Security machine learning (ML) model is built to expose. This post follows four operations, spanning eight payloads, that our Page Shield ML uncovered in the wild. The detection of these malicious payloads was automated; humans verified each finding only after the system had flagged it. When we afterward reviewed the campaigns using security scanning tools, seven of the eight payloads were entirely absent from VirusTotal, and URLScan returned no malicious verdict for any of them. Page Shield ML , meanwhile, caught all eight in live traffic. For instance, while security research documented the broader Lnkr family years earlier, one specific payload version sat indexed by URLScan for nearly two and a half years with “No classification,” including during a direct scan in January 2024. Only in this case had VirusTotal ingested the payload earlier: while it currently flags the script as malicious, public history does not reveal when that verdict was first assigned. Meanwhile, Page Shield ML independently surfaced those exact bytes live on an online retailer's storefront. More broadly, a hash can be known long before the code behind it is classified as malicious. If your defense
The consumer data broker Radaris.com has long had a reputation for ignoring requests to remove personal information from its vast empire of people-search services online. That reputation caught up with the company recently in a lawsuit alleging Radaris violated a New Jersey privacy law that provides for hefty fines against data brokers that publish personal information on state law enforcement officials. In the face of repeated stonewalling and prevarication by attorneys for Radaris, the judge in the case ordered that radaris.com and more than a dozen other data broker domains be transferred to the plaintiffs. The radaris.com website, prior to the domain transfer to Atlas. In February 2024, Radaris was sued by Atlas Data Privacy Corp , a company that has been pursuing data brokers alleged to be violating a New Jersey statute called Daniel’s Law . The statute allows state law enforcement officials, government personnel, judges and their families to have their information completely removed from commercial data brokers and people-s
A penetration testing scope defines the assurance an enterprise needs, not just the assets a vendor will touch. Start with the business or compliance objective, then map the system boundary before counting assets. List applications, APIs, infrastructure, roles and integrations separately, specify authenticated and unauthenticated testing, and clarify whether production, staging or both will be […] The post How to Scope an Enterprise Penetration Test: Free Scope-of-Work Template appeared first on Synack .
Overview A vulnerability in MLflow’s dspy and statsmodels model flavors allows unauthorized pickle deserialization executions despite a safety control. Specifically, the dspy flavor conditionally applies the control based on the model path’s file extension, and the statsmodels flavor does not apply the control. Description MLflow is an open-source platform for managing machine learning lifecycles, including model packaging, versioning, and deployment. "Flavors" refer to the specialized frameworks through which supported models are stored and loaded. In response to previous vulnerability concerns, MLflow implemented the MLFLOW_ALLOW_PICKLE_DESERIALIZATION safety control to block and disable executing any pickle deserialization and subsequent loads per the user’s choice. When loading models through mlflow.pyfunc.load_model(model) , users must specify a model flavor and path in an MLmodel file. With the dspy flavor, MLflow checks the value of MLFLOW_ALLOW_PICKLE_DESERIALIZATION , and whether the specified model path ends in .pkl . A model path that does not end in .pkl (even if the file is actually a pickle file), will route to a separate branch for pickle deserialization, bypassing the safety control. However, when loading through the statsmodels flavor, there is no check for MLFLOW_ALLOW_PICKLE_DESERIALIZATION at all. Impact Exploitation of this vulnerability allows for arbitrary remote code execution through a malicious pickle-loaded payload, regardless of a user explicitly disallowing pickle serialization, through vulnerable flavor specifications in the MLmodel configuration file. The attack path requires write access to any location from which a use
VU#212479: Sentry Seer vulnerability allows attacker-controlled input to be executed in a privileged environment
Overview A vulnerability exists in Sentry Seer when the system is configured to automatically hand issues to a coding agent for remediation. Successful exploitation results in arbitrary code execution within the coding‑agent environment and access to connected source repositories. This vulnerability is tracked as CVE-2026-90999 . Description Sentry is a software error‑monitoring and performance‑tracking platform used by developers to detect, diagnose, and understand issues in their applications. It collects telemetry such as exceptions, stack traces, logs, and performance data from applications. Built into Sentry, Seer acts as an automated debugging assistant that converts telemetry into actionable remediation steps and can hand off issues to an integrated coding agent to propose code fixes. Because Sentry front-end projects commonly expose a public DSN (Data Source Name) to allow browsers to submit this telemetry, an attacker can craft and submit malicious events through this public endpoint. When Seer is enabled to automatically pass issues to a coding agent, these attacker-supplied events can traverse multiple trust boundaries. Ultimately, malicious event fields propagate through Seer’s analysis pipeline, transforming into untrusted instructions that the privileged coding agent may execute. The vulnerable workflow is as follows: * Sentry ingests attacker‑generated exception events submitted through the public DSN. * Seer evaluates whether the event represents an issue eligible for automated remediation. * Seer generates a root‑cause analysis that uses attacker-controlled event fields, including exception messages, stack traces, source context, and breadcrumbs. * The generated analysis is embedded directly into the initial prompt provided to the coding agent.
In this post, we walk through different threats to GitHub and how to detect them.
Tuesday, September 15