More results...
US agencies warn Russian group Laundry Bear is exploiting a patched Zimbra flaw to steal email accounts from organizations running unpatched servers. The Cybersecurity and Infrastructure Security Agency (CISA), National Security Agency (NSA), Federal Bureau of Investigation (FBI) and other U.S. government and international partners published a joint advisory to warn that the Russia-linked APT […]
US and allies warn of Russian APT groups targeting routers and network devices to compromise critical infrastructure worldwide. The US and allied governments warn that Russian state-sponsored APT groups are scanning and exploiting poorly secured network devices, especially routers, to access critical infrastructure. Groups linked to FSB Center 16, including Berserk Bear, Energetic Bear, Ghost […]
US and allies warn of Russian APT groups targeting routers and network devices to compromise critical infrastructure worldwide. The US and allied governments warn that Russian state-sponsored APT groups are scanning and exploiting poorly secured network devices, especially routers, to access critical infrastructure. Groups linked to FSB Center 16, including Berserk Bear, Energetic Bear, Ghost […]
Ransomware remains above 1,400 attacks yearly since 2023. Qilin leads in 2026, while the U.S. remains the main target. Ransomnews has independently confirmed 9,291 ransomware attacks worldwide between January 2018 and July 2026, tracking incidents only when verified through victim disclosures, regulatory filings, official statements, or credible press reporting. Leak-site listings alone don’t qualify, operators […]
At least one malware developer is adding text about nuclear and biological weapons to their spyware, in an effort to stop automatic AI analysis.
The _index.js payload begins with a large JavaScript block comment containing fake system instructions and policy-triggering content. Because it is inside a comment, it does not affect JavaScript execution. The runtime skips it. The real malware begins after the comment with a try{eval(…)} wrapper around a large character-code array and a ROT-style substitution function.
This header appears designed for AI-mediated analysis, not for Node, Bun, or Python. It attempts to derail scanners or analyst copilots that feed the beginning of a file to a language model without clearly isolating the content as untrusted data. In weak pipelines, this can cause refusal behavior, prompt confusion, context pollution, or premature classification before the scanner reaches the actual malware…
ENISA NIS360 2026 shows cybersecurity improving across EU critical sectors, but health, water, rail, and space remain in the risk zone. ENISA has published its third annual NIS360 report, assessing the cybersecurity maturity and criticality of all sectors covered by the NIS2 directive. The headline finding is that things are improving across the board. The […]
The 2025 Internet Crime Report was published a few weeks ago, but I only just saw it.
Lots of interesting statistics.
Press release. News articles.
A 5-year study on the Ransomware Economy found that 30,515 exposed databases were hit by ransom attacks, causing massive damage despite victims never paying. Database extortion doesn’t look like the ransomware stories that usually grab headlines. There’s no slick branding, no leak-site countdown, no gang posting memes on Telegram. In most cases, there’s just a […]
Apple 2025 fraud report shows major App Store protections: over 2M apps rejected, 1B fake accounts blocked, and billions in fraud prevented. Apple ‘s annual fraud prevention report for 2025 paints a striking picture of just how much effort goes into keeping the App Store clean. The numbers are significant: more than two million app […]
Good report:
Executive Summary: Let’s say you wanted to make sure that your AI is secure. Can you just maximize the security and privacy benchmark and call it a day? Nope, because benchmarks don’t actually work for measuring AI capabilities (even when they are NOT emergent systemic properties like security). So let’s take a step back: how do you measure security in the first place? Good question. Over the last 30 years, security engineering for software evolved from black box penetration testing, through whitebox code analysis and architectural risk analysis to de facto process-driven standards like the Building Security In Maturity Model (BSIMM). Software had a very deep impact on business operations, and it appears that AI is going to have an even deeper impact. Will a software security-like measurement move work for AI? Probably. In the meantime we can make real progress in AI security by cleaning up our WHAT piles and managing risk by identifying and applying good assurance processes. (Spoiler alert: no matter what we do, we still don’t get a security meter for AI, so we need to be extra vigilant about security.)…