Hi, we ran a tabletop after last year's vendor breach and my team froze because the plan assumed the vendor would answer in minutes, not 14 hours. I feel sick about it, because the whole exercise turned into us staring at the phone and asking each other what the actual next step was (pls tell me someone else has done this).

Hi mates! I’ve set up a homelab (enterprise network simulation) on my laptop (an OMEN 16, i7-14650HX, 32 GB RAM, RTX 4060 8 GB) for long-term IT practice and testing, focusing on networking, sysadmin, and pentesting. More details can be found in this GitHub repo: https://github.com/Ko0ler/HomeLab

I'd greatly appreciate your feedback!

Recent drone strikes have knocked multiple major Yandex data centers offline, and Cloudflare is reporting a massive 99% drop in Yandex-originating bot traffic.

This gives us an unprecedented, real-world control group. While some of this drop is just standard IT automation scripts going offline, this is our best window to measure exactly how much X (Twitter) engagement is artificially inflated by Russian infrastructure.

**We need to pull X data NOW before they spin up backup infrastructure or reroute through VPNs.**

**Key metrics to capture:**
1. Engagement ratios (Like/RT/Reply) on highly politicized topics.
2. Sudden drop-offs in currently trending hashtags.
3. Stalled follower growth for anomalous accounts.
4. Current data snapshots to compare against 30-day historical datasets.

If you have historical firehose data, are actively scraping, or want to pool resources, drop a comment or repo link below.

Let’s capture this snapshot while the window is open.

https://www.tomshardware.com/tech-industry/data-centers/russian-disinformation-bot-traffic-nearly-eliminated-overnight-after-ukraine-drone-strikes-cripple-multiple-of-russias-google-data-centers-ukraine-intensifies-bombing-of-yandex-data-centers-in-response-to-moscows-strikes-on-kyiv-data-centers

Autonomous AI agents running intrusions from recon to root. The operator wrote a goal and read the results. This blog covers real AI attacks happening in the wild.

- 75 transcripts off attacker servers
- Claude Code on DeepSeek, pi, Codex
- command execution on 23 hosts
- SSRF to a root cloud box in 9h 44m
- unauth SQLi to OS commands
- Open WebUI rooted, CVE-2026-0766
- one target held 5 days, 304 steps
- card and wallet data stolen, wiped
- 150,574 AI gateways swept for keys
- in house 0day dev on gateway source

Reposting for visibility. My name is Stephanie Hull, and I am a doctoral student at National University. I am conducting an online survey to examine how organizational readiness influences the effectiveness of AI-driven cybersecurity in U.S. healthcare systems. In order to participate, you must be at least 18 years of age, currently employed in a cybersecurity, information technology, digital security analyst, or other related role, and working within a U.S. healthcare system.

The survey is anonymous and has approximately 45 questions and will take about 10–15 minutes to complete and will ask questions about technical infrastructure, workforce competence, financial resource allocation, AI cybersecurity implementation, and cybersecurity performance outcomes such as threat detection, response time, and system resilience.

Follow this link if you wish to participate in this voluntary research: https://ncu.co1.qualtrics.com/jfe/form/SV_1IatwkB184OOyHA. Please share this link with others!

Thank you for your time,

Stephanie Hull, Doctoral Student, National University

Email: [s.hull7960@student.nu.edu](mailto:s.hull7960@student.nu.edu)

Thoughts on MITRE ATTACK human interaction techniques mapped into a gamified way to train banking/telecom sector employees.

Did this project is worth it as an FYP?

if yes should we focus on training technical staff or non technical staff because platforms like immersive labs focus on IT technical employees.

VigilOSS - https://github.com/VigilOSS/Vigil

I built this tool because I was interested in Bug Bounties, wanted to learn how far AI could go at finding bugs, and was very interested in whether it could remove the mundane parts I remember from preparing for my OSCP.

Over time it went from a pile of prompts to a structured harness for long-running engagements. It's the result of hundreds of hours of running it on real targets, watching where it went wrong, and refining.

An operator agent coordinates specialist agents, and most every tool runs through one shared Kali container. Scope, attack surface, coverage, commands, credentials, evidence and findings live in a backend that survives restarts and compaction, so the agent doesn't redo work or forget why it ruled something out. It works with Claude Code and Codex. One engagement can mix source review and live web testing, and a bug found in code and then confirmed live stays as one finding.

I've used it on authorized HackerOne programs for findings that paid out more than $12,000 (Scanning large amounts of source maps, finding potential bugs, and having the web engagement test and verify). It has been most useful on large codebases, where tracking what has and hasn't been reviewed is harder than finding any single bug.

I conceived MSPEP — the Multi-Source Physical Entropy Pool Encryption System — in June 2026 and spent the last 3 months deciding whether to patent it or release it for free. Today it drops as a defensive publication, free to the world. MSPEP turns the sensors already on your device (magnetometer, thermistors, accelerometer, microphone, photodiode, RF front-end, power rail noise, NIC timing) into a continuous, hardware-rooted entropy pool. Key points: - Random subset selection (min 3 sensors) per event - Bounded sampling window, hardware-timestamped - Adaptive entropy weighting per sensor - Cryptographic extractor (HKDF/SHA3) with continuous reseed - Applications: storage encryption, physical timestamping, distributed consensus, AI session security, communication layer AI Session Security (new in v6): - Per-session keys from client physical entropy at initiation - Continuous integrity monitoring via sensor subset - Anomaly responses: terminate, rotate, escalate (MFA), alert with physical timestamp - Port timing serves as BOTH entropy source AND integrity baseline - Cloud architecture: client generates key, server validates physical fingerprint, NO key transmission. Concept specification and prior art disclosure, CC0 licensed.Prior art established June 27, 2026 (v1-v6 documented) 23 claims across 6 families Repo: github.com/vichallock-creator/MSPEP Spec: Zenodo DOI: 10.5281/zenodo.23286461. Happy to discuss the architecture, the Synaptic Method used to derive it, or commercial licensing for supported integration.

Running a simple user access review should not require a project team.

With many legacy IGA platforms, even a basic review needs developers, business analysts and project managers. Custom applications need custom connectors. Every change to a review becomes a change request. And audit evidence is assembled by hand before every audit.

In this short video, we compare legacy IGA with SecurEnds across five everyday tasks:

✔ Launching a user access review
✔ Bringing in custom and homegrown applications
✔ Changing who reviews, how often, and what they see
✔ Including service accounts and AI agents
✔ Producing audit evidence

SecurEnds takes a different approach: configuration, not code. Your security or GRC team configures reviews themselves, connects to more than 3,000 applications, brings people, service accounts and AI agents into the same campaign, and captures audit evidence automatically with every decision.

That is why security and GRC leaders at banks, financial institutions and other regulated organizations choose SecurEnds.

⏱ Chapters
0:00 Legacy IGA vs SecurEnds
0:07 Launching a user access review
0:20 Custom and homegrown applications
0:31 Changing review rules
0:43 Service accounts and AI agents
0:54 Audit evidence
1:04 Why customers choose SecurEnds

🔗 Learn more: https://www.securends.com
📩 Request a demo: [sales@securends.com](mailto:sales@securends.com)

About SecurEnds
SecurEnds is an identity governance company that helps regulated organizations automate user access reviews, gain visibility into every identity, and stay audit-ready. SecurEnds holds SOC 1 Type II, SOC 2 Type II, TX-RAMP and COV-RAMP certifications.

Hi all, I built Fortress: add one line to a Node/Express app (app.use(fortress.shield())) and it blocks the common automated attacks (SQL and script injection, scanners hunting for /.env, attack tools, password guessing) and shows you what it stopped.

It starts in learning mode, so it records what it would block and blocks nothing. That way it can't lock out a real user by surprise, and you switch blocking on when the list shows only attacks. It fails open and has no runtime dependencies.

You can try it without signing up: getfortress.co.uk

- Attack a pretend shop with Shield off, then on: https://getfortress.co.uk/demo/

- Free check of your own site's security headers, certificate and exposed files: https://getfortress.co.uk/scan/

Honest bits: it's early,, and it only supports Node/Express for now. I'm looking for a few people to run it on a real app and tell me what breaks, especially false positives. I'll help set it up for free.

What would make you trust a security tool from a brand-new project?