标签：#cybersecurity

Multiple cybersecurity researchers said they suddenly lost access to OpenAI’s Trusted Access for Cyber (TAC) program, which offers models with fewer guardrails for vetted users.

The U.S. phone provider escaped a large-scale breach of its network after identifying Chinese-backed hackers early on.

A new feature added to Comcast's newest routers can detect if there is motion is inside your home without needing traditional motion sensors.

Passwords are less secure than passkeys, even if you use a password manager. Here's why and how to get started with passkeys.

This is the latest large-scale DDoS attack to hit the social networking site this year.

Developers write far more legally consequential prose than they think, and almost none of it is code. It's the SECURITY.md in the repo root. It's the "Security" page someone in marketing asked you to fill in three years ago. It's the status page update typed at 2 a.m., and the sentence in a customer notice specifying exactly which data was affected. The research summarized in this overview of what the evidence shows about cyber incident disclosure treats post-breach communication as a measurable discipline with predictable failure modes — and the enforcement record of the last three years has quietly turned it into an engineering discipline too. In the most closely watched cybersecurity case of the decade, the only allegation that survived a motion to dismiss concerned a technical description of access controls posted on a website. The claim that survived was written by engineers On July 18, 2024, Judge Paul Engelmayer of the Southern District of New York issued a 107-page opinion in the SEC's case against SolarWinds and its CISO. Most of it was a defeat for the agency. Claims built on blog posts, press releases, and podcast appearances were dismissed as non-actionable corporate puffery — statements too general for any reasonable investor to lean on. The theory that cybersecurity controls fall under "internal accounting controls" was rejected outright. Post-incident 8-K disclosures were held to be reasonable given what was knowable at the time. One thing lived: the company's "Security Statement," a technical page describing its practices to customers. The court let claims proceed specifically on its representations about access controls and password policy , because those were concrete enough to rely on and, as pled, contradicted by internal presentations, security assessments, and Slack messages. The SEC ultimately dismissed the whole action with prejudice in November 2025, so no liability was ever established — but the legal line drawn in 2024 didn't go anywhere.

Z.ai’s latest AI model release could help companies secure their systems—or find its way into the hands of hackers.

The most important AI security story right now is not that models can find bugs. It is that models can find more bugs than humans can responsibly process. That is the part that changes how builders should think about software. For years, security work was constrained by discovery. Could someone find the vulnerability? Could they reproduce it? Could they build an exploit? Could a small team afford enough expert review to catch the important issues before attackers did? Now that bottleneck is moving. Anthropic's recent Project Glasswing update is the clearest signal yet. The company says Claude Mythos Preview and its partners found more than 10,000 high- or critical-severity vulnerabilities across major software systems. In open source alone, Anthropic says it scanned more than 1,000 projects and surfaced thousands of serious findings, with human triage becoming the slow part. You do not have to take every number at face value to see the shape of the shift. AI is making vulnerability discovery cheaper. That sounds like good news, and it is. But it also means every software team is about to face a harder question: What happens when the scanner is faster than the organization? The Patch Window Is the Product Now Security used to have a familiar rhythm. A bug was found. A report was filed. A team reproduced it. Someone argued about severity. Someone wrote a patch. Users eventually upgraded. That process was never fast enough, but it mostly matched the speed of human discovery. AI breaks that balance. If models can search codebases, reason about exploit paths, generate reports, and repeat that work across thousands of projects, then finding bugs stops being the scarce skill. The scarce skill becomes the system around the finding: Can you tell which reports are real? Can you prioritize the ones that actually matter? Can you patch without breaking production? Can you ship fixes before attackers learn the same thing? Can you keep maintainers from drowning in low-quality repo

Cybersecurity experts who investigate spyware attacks say the number of people who received a recent threat notification from Apple is unusually high.

When I first got interested in cybersecurity, I thought it was all about tools. Nmap, Metasploit, Wireshark, Burp Suite. I downloaded them all, watched tutorials, and felt like a hacker. But the first time I tried to customize a scan or parse a weird log file, I hit a wall. I didn't know how to code. And in cybersecurity, that's like trying to be a chef without knowing how to use a knife. This article is for people who want to move beyond clicking buttons. Whether you're a beginner deciding where to start or a security analyst who wants to automate boring tasks, programming will change how you work. I'll cover why programming matters, what languages to learn, the concepts you'll actually use, projects to build, and how to think like both an attacker and a defender. Why programming isn't optional anymore Cybersecurity used to be more forgiving. You could run a vulnerability scanner, read the report, and call it a day. But threats have gotten more complex, and so have the defenses. Today, you need to: · Write scripts to analyze thousands of log lines in seconds. · Automate repetitive tasks like phishing email analysis or IP reputation checks. · Understand the code behind vulnerabilities so you can explain them to developers. · Build custom tools when existing ones don't fit your environment. · Test your own code for flaws before attackers find them. If you can't read or write code, you're limited to what someone else built. That's not a career; that's a hobby. Programming gives you the ability to solve problems no tool can solve out of the box. What "programming for cybersecurity" actually means It's not software engineering. You don't need to build a full web application or master design patterns. Instead, you use code as a tool for investigation, automation, and exploitation (ethically, of course). Different roles need different levels of programming: · SOC analysts might write Python scripts to correlate logs or query APIs. · Penetration testers write proof-of-conc

The hacks at shipping companies used to mail out hardware wallets puts crypto owners at greater risk of real-world attacks.

When a vendor is breached, don't wait for their update page: figure out fast what that vendor can see or touch inside your business, and act on that answer before you have all the facts. Vendor breaches are a recurring headline: a phone system, messaging platform, or file-sharing tool used by thousands of businesses discloses an incident, and every customer of that vendor suddenly has to ask what it means for them, usually with almost no visibility into the vendor's internal investigation. The gap between "something happened to our vendor" and "here's what we do about it" is where most companies lose time they can't get back. Quick answers What's the first thing to do when a vendor is breached? Confirm exactly what that vendor can access in your systems — before you do anything else. Should I rotate credentials before the vendor confirms exposure? Yes, for anything plausibly exposed — even though it may briefly disrupt a live integration. How often should I re-check a slow-to-disclose vendor? It depends on how much access they hold — high-privilege vendors need a 48–72 hour check-in, not a week. Do I need a written plan before an incident happens? Yes — a one-page plan per privileged vendor, reviewed at least yearly. Why vetting a vendor once isn't enough Most businesses do vendor due diligence at signup: a security questionnaire, maybe a look at their trust page, a checkbox before the contract is signed. That's reasonable, but it only answers the question that matters on day one: is this vendor safe to start using? It doesn't answer the question that matters every day after: if this vendor gets breached, what happens to us, and what do we do? Vetting is a point-in-time filter. A breach is an ongoing event with a timeline, and your response needs its own plan, separate from the vetting checklist you ran before signing. The fix is simple: treat vendor risk as a lifecycle, not a gate. Vet before you sign, revisit access and exposure on a regular cadence, and have a re

What kind of data is being collected by our devices, and how is it being used? Should we "Ask app not to track"?

Passkeys are still safer than passwords. That is the answer, and the research behind the scary headlines says so too. On 3 August 2026, Palo Alto Networks' Unit 42 published three techniques that let malware take over accounts protected by Google-synced passkeys. No fingerprint, no PIN, and no prompt on screen. The coverage that followed skipped the part readers need: exactly who is exposed, and what to change. The real scope is narrow. The fix is cheap. The standard itself is not broken. What Pass-ta-key actually is A passkey is a key pair that replaces a password. The private half stays on your device or in a synced store, and the site only ever sees a signature. Unit 42 named three variants, not four. Several outlets reported a fourth, including 9to5Google . The research describes three ( Unit 42 , 3 August 2026). Pass-ta-key. Malware extracts Chrome's device identity key and uses it to sign a request. No admin rights, no device unlock, no user action. Silver Pass-ta-key. The attacker forces Chrome to re-register the device. They then register their own user-verification key with Google's cloud authenticator. Afterwards they can sign in from their own machine, and the cloud authenticator believes a fingerprint check happened. Golden Pass-ta-key. The attacker pulls the Security Domain Secret out of Chrome's process memory during onboarding. The Security Domain Secret is a 32-byte master key that protects every synced passkey. With it, they all decrypt. This is the variant that turns one infection into a saleable bundle ( BleepingComputer , 3 August 2026). The target is not the passkey file on disk. It is the Google Cloud Authenticator behind Google Password Manager, and the trust it puts in a device that malware is now imitating ( The Hacker News , August 2026). Who is actually affected This is the question the coverage left open. Here it is against the research's own stated scope. Setup Status Chrome on Windows with a TPM, Google Password Manager Affected. This i

Your threat model has a hole shaped like your house. You run endpoint protection on your Mac. You have 2FA, passkeys, hardened browser, DNS filtering. You would never install random software from a forum. Then you walk into your living room that has 14 always-on microphones, 6 cameras, 3 devices that map your floor plan, and a router you have never audited, all running firmware you have never read. We need to talk. In cybersec we threat model laptops. We never threat model apartments. That is backwards. Your laptop leaves your house. Your house never leaves. If your home is compromised, every device you bring into it is compromised by proximity. Here is how I started threat modeling my apartment the same way I threat model my infra. It takes an afternoon and it will make your home actually sovereign. Step 1: Draw Trust Zones, Not Floor Plans Stop thinking in rooms. Start thinking in trust zones, exactly like network segmentation. I use 3 zones: Zone 0: The Dead Room. One room where no device can listen, watch, or transmit. No smart anything. No WiFi. No Bluetooth. This is where you think, talk for real, and store sensitive hardware. My bedroom is Zone 0. Nothing with a mic crosses the door. It has a mechanical door sweep and a faraday pouch for phones. Zone 1: The Clean Network. Your own network that you control. Your router, your Pi-hole, your own hotspot. Devices you have audited. This is where your work laptop lives. It never touches landlord WiFi, coffee shop WiFi, or that free "Apartment_5G" that is actually a $30 camera streaming 24/7. Zone 2: The Dirty Periphery. Everything else. Landlord's smart lock, smart thermostat, package room cameras, your smart TV, robot vacuum, Alexa, LED strips with mics, that random air freshener that is plugged in at waist height. Assume Zone 2 is hostile and logs everything. Most people live entirely in Zone 2 and call it cozy. That is why they get doxxed by their own house. If you want the full build for a Zone 0 room, what to r

A guide on how to check if hackers have broken into your accounts on the most popular AI platforms.

Over the last couple of weeks, hackers have targeted and broken into the systems of several water plants in the United States. Here’s what we know and don’t know about this wave of attacks allegedly carried out by the Iranian government.

A couple of weeks ago I dropped the CRA text (the EU's cybersecurity regulation for IoT devices) into ChatGPT and asked when the main requirements actually kick in. The answer was confident and wrong - it mixed up the date the regulation entered into force (2024) with the date the requirements actually apply (2027). Three years off, stated like an obvious fact. My team (Platanor, embedded security for IoT) has been building an internal reference on CRA/RED/NIS2/CSA for a few months now, and this is exactly the kind of mix-up we kept running into whenever we just threw the regulation PDF at a model. The problem isn't the model. It's how the source is laid out: dates are scattered across different articles with no explicit link between them, token-based chunking cuts sentences off mid-article, and the model has no way to tell how fresh the text is. When we rebuilt the base as a public repository, we fixed this with file structure, not prompting. Cut by article headings, not by tokens: ### Article 13 Obligations of manufacturers 1. When placing a product... ### Article 14 Reporting obligations... ### Article N is a natural boundary. Each chunk stays whole - the article never gets split mid-sentence. Source priority, written into the file itself, not the prompt: primary source > official related documents > third-party summaries > our own analysis. The model sees this right next to the content, not as an instruction that's easy to lose in a long chat. A verification date on every file: > Last verified: 2026-08-10. > Annex I application deadline: 11 December 2027 (not to be confused with the entry-into-force date - 10 December 2024). That one line is what removed the exact error I opened with. llms.txt at the repo root - an index of every file, so an agent can pick what to load instead of reading the whole repository. The same questions now get answered correctly - not because the model got smarter, but because the source stopped being one continuous wall of text. We pac

Threat Overview 🚨 Microsoft SharePoint now has a critical flaw, CVE-2026-55040, that has already started being exploited in the wild. ⚠️ The vulnerability scores a 9.1 on CVSS and lets unauthenticated attackers bypass authentication to perform arbitrary operations on any affected site. Vulnerability Technical Background 🔍 The root cause is a flaw in SharePoint’s JWT token validation chain used for service‑to‑service (S2S) communication. ❌ Two internal classes, SPJsonWebSecurityTokenHandlerV2 and SPJsonWebSecurityBaseTokenHandlerV2, incorrectly parse the outer header of a JWT, allowing attackers to skip signature verification under certain conditions. Exploit Chain Step‑by‑Step 1️⃣ The attacker crafts a JWT with alg=none in its outer header, effectively removing the requirement for an outer token signature. 2️⃣ An inner actor token is embedded that includes SharePoint’s own STS certificate thumbprint, tricking SharePoint into resolving a signing key without proper verification. 3️⃣ The resolved certificate is not listed in TrustedSecurityTokenServices, letting the issuer claim be accepted unquestioned. 4️⃣ The actor token’s signature can simply be a non‑empty placeholder like AAAA , which never gets validated, leaving the chain open for injection. Proof of Concept Availability 🔐 A fully functional Python PoC was released by Rapid7 earlier this week. # forge_jwt.py – minimal example import jwt , requests def craft_token (): header = { " alg " : " none " , " typ " : " JWT " } payload = { " iss " : " https://sharepoint.com " , " aud " : " https://sts.sharepoint.com " } return jwt . encode ( payload , key = None , algorithm = " none " , headers = header ) token = craft_token () print ( " Forged token: " , token ) ⚙️ The script demonstrates forging the JWT chain, querying a target domain controller, enumerating user SIDs, and automatically identifying site administrators. 📂 Full source code is available at hxxps://githubcom/sfewer-r7/CVE-2026-55040. Active Exploitation La

Apple has recently sent out notifications, warning users that they'd been targeted by mercenary spyware attack.