logo
Overkill Security  Because Nothing Says 'Security' Like a Dozen Firewalls and a Biometric Scanner
О проекте Просмотр Уровни подписки Фильтры Обновления проекта Контакты Поделиться Метки
Все проекты
О проекте
A blog about all things techy! Not too much hype, just a lot of cool analysis and insight from different sources.

📌Not sure what level is suitable for you? Check this explanation https://sponsr.ru/overkill_security/55291/Paid_Content/

All places to read, listen and watch content:
➡️Text and other media: TG, Boosty, Teletype.in, VK, X.com
➡️Audio: Mave, you find here other podcast services, e.g. Youtube Podcasts, Spotify, Apple or Amazon
➡️Video: Youtube

The main categories of materials — use tags:
📌news
📌digest

QA — directly or via email overkill_qa@outlook.com
Публикации, доступные бесплатно
Уровни подписки
Единоразовый платёж

Your donation fuels our mission to provide cutting-edge cybersecurity research, in-depth tutorials, and expert insights. Support our work today to empower the community with even more valuable content.

*no refund, no paid content

Помочь проекту
Promo 750₽ месяц
Доступны сообщения

For a limited time, we're offering our Level "Regular" subscription at an unbeatable price—50% off!

Dive into the latest trends and updates in the cybersecurity world with our in-depth articles and expert insights

Offer valid until the end of this month.

Оформить подписку
Regular Reader 1 500₽ месяц 16 200₽ год
(-10%)
При подписке на год для вас действует 10% скидка. 10% основная скидка и 0% доп. скидка за ваш уровень на проекте Overkill Security
Доступны сообщения

Ideal for regular readers who are interested in staying informed about the latest trends and updates in the cybersecurity world without.

Оформить подписку
Pro Reader 3 000₽ месяц 30 600₽ год
(-15%)
При подписке на год для вас действует 15% скидка. 15% основная скидка и 0% доп. скидка за ваш уровень на проекте Overkill Security
Доступны сообщения

Designed for IT professionals, cybersecurity experts, and enthusiasts who seek deeper insights and more comprehensive resources. + Q&A

Оформить подписку
Фильтры
Обновления проекта
Поделиться
Метки
overkillsecurity 142 overkillsecuritypdf 52 news 47 keypoints 38 nsa 26 fbi 25 adapt tactics 11 Living Off the Land 11 LOTL 11 unpacking 10 vulnerability 9 cyber security 8 Digest 8 edge routers 8 Essential Eight Maturity Model 8 malware 8 Maturity Model 8 Monthly Digest 8 research 8 ubiquiti 8 IoT 7 lolbin 7 lolbins 7 Cyber Attacks 6 phishing 6 Forensics 5 Ransomware 5 soho 5 authToken 4 BYOD 4 MDM 4 OAuth 4 Energy Consumption 3 IoMT 3 medical 3 ai 2 AnonSudan 2 authentication 2 av 2 battery 2 Buffer Overflow 2 console architecture 2 cve 2 cybersecurity 2 energy 2 Google 2 incident response 2 MITM 2 mqtt 2 Passkeys 2 Retro 2 Velociraptor 2 video 2 Vintage 2 vmware 2 windows 2 1981 1 5g network research 1 8-bit 1 Ad Removal 1 Ad-Free Experience 1 ADCS 1 advisory 1 airwatch 1 AlphV 1 AMSI 1 android 1 Android15 1 announcement 1 antiPhishing 1 AntiPhishStack 1 antivirus 1 Apple 1 Atlassian 1 Attack 1 AttackGen 1 BatBadBut 1 Behavioral Analytics 1 BianLian 1 bias 1 Biocybersecurity 1 Biometric 1 bite 1 bitlocker 1 bitlocker bypass 1 Black Lotus Labs 1 blackberry 1 blizzard 1 botnet 1 Browser Data Theft 1 BucketLoot 1 CellularSecurity 1 checkpoint 1 china 1 chisel 1 cisa 1 CloudSecurity 1 CloudStorage 1 content 1 content category 1 cpu 1 Credential Dumping 1 CVE-2023-22518 1 CVE-2023-35080 1 CVE-2023-38043 1 CVE-2023-38543 1 CVE-2024-0204 1 CVE-2024-21111 1 CVE-2024-21345 1 cve-2024-21447 1 CVE-2024-24919 1 CVE-2024-26218 1 cve-2024-27129 1 cve-2024-27130 1 cve-2024-27131 1 cve-2024-3400 1 cvss 1 cyber operations 1 Cyber Toufan Al-Aqsa 1 cyberops 1 D-Link 1 dark pink apt 1 data leakage 1 dcrat 1 Demoscene 1 DevSecOps 1 Dex 1 disassembler 1 DOS 1 e8mm 1 EDR 1 Embedded systems 1 Employee Training 1 EntraID 1 ESC8 1 Event ID 4663 1 Event ID 4688 1 Event ID 5145 1 Evilginx 1 EvilLsassTwin 1 Facebook 1 FBI IC3 1 FIDO2 1 filewave 1 Firebase 1 Firmware 1 Fortra's GoAnywhere MFT 1 france 1 FraudDetection 1 fuxnet 1 fuzzer 1 game console 1 gamification 1 GeminiNanoAI 1 genzai 1 go 1 GoogleIO2024 1 GooglePlayProtect 1 GoPhish 1 gpu 1 ICS 1 ICSpector 1 IDA 1 IncidentResponse 1 Industrial Control Systems 1 jazzer 1 jetbrains 1 jvm 1 KASLR 1 KillNet 1 LeftOverLocals 1 Leviathan 1 lg smart tv 1 lockbit 1 LSASS 1 m-trends 1 Machine Learning Integration 1 Mallox 1 MalPurifier 1 mandiant 1 MediHunt 1 Meta Pixel 1 ML 1 mobile network analysis 1 mobileiron 1 nes 1 nexus 1 NGO 1 Nim 1 Nimfilt 1 NtQueryInformationThread 1 OFGB 1 oracle 1 paid content 1 panos 1 Passwordless 1 Phishing Resilience 1 PingFederate 1 Platform Lock-in Tool 1 PlayIntegrityAPI 1 PlayStation 1 playstation 2 1 playstation 3 1 plc 1 podcast 1 Privilege Escalation 1 ps2 1 ps3 1 PulseVPN 1 qcsuper 1 qemu 1 qualcomm diag protocol 1 radio frame capture 1 Raytracing 1 Real-time Attack Detection 1 Red Team 1 Registry Modification 1 Risk Mitigation 1 RiskManagement 1 rodrigo copetti 1 rooted android devices 1 Router 1 rust 1 Sagemcom 1 sandworm 1 ScamCallDetection 1 security 1 Security Awareness 1 session hijacking 1 SharpADWS 1 SharpTerminator 1 shellcode 1 SIEM 1 Siemens 1 skimming 1 Smart Devices 1 snes 1 SSO 1 stack overflow 1 TA427 1 TA547 1 TDDP 1 telecom security 1 Telegram 1 telerik 1 TeleTracker 1 TEMP.Periscope 1 Terminator 1 Think Tanks 1 Threat 1 threat intelligence 1 threat intelligence analysis 1 Threat Simulation 1 tool 1 toolkit 1 tp-link 1 UK 1 UserManagerEoP 1 uta0218 1 virtualbox 1 VPN 1 vu 1 wargame 1 Web Authentication 1 WebAuthn 1 webos 1 What2Log 1 Windows 11 1 Windows Kernel 1 Windstream 1 women 1 WSUS 1 wt-2024-0004 1 wt-2024-0005 1 wt-2024-0006 1 xbox 1 xbox 360 1 xbox original 1 xss 1 Yubico 1 Z80A 1 ZX Spectrum 1 Больше тегов
Читать: 1+ мин
logo Overkill Security

The Irony of MobileIron. When Your Security Solution Needs Security


Get ‎ready‏ ‎to ‎press ‎your ‎luck ‎with‏ ‎MobileIron ‎MDM,‏ ‎where‏ ‎security ‎wrinkles ‎are‏ ‎a ‎feature,‏ ‎not ‎a ‎bug:

📌Security ‎Risks:‏ ‎Discover‏ ‎how ‎MobileIron‏ ‎turns ‎"Fort‏ ‎Knox" ‎into ‎"Fort ‎Knocks-over-easily."

📌Technical ‎Exploits:‏ ‎Learn‏ ‎how ‎attackers‏ ‎can ‎smooth‏ ‎out ‎your ‎security ‎defenses ‎faster‏ ‎than‏ ‎you‏ ‎can ‎iron‏ ‎a ‎shirt.

📌Mitigation‏ ‎Strategies: Master ‎the‏ ‎art‏ ‎of ‎digital‏ ‎duct ‎tape ‎and ‎wishful ‎thinking.

📌Impact‏ ‎Assessment: Explore ‎the‏ ‎joys‏ ‎of ‎explaining ‎to‏ ‎your ‎CEO‏ ‎why ‎the ‎company's ‎secrets‏ ‎are‏ ‎now ‎public‏ ‎domain.

By ‎the‏ ‎end, ‎you'll ‎be ‎an ‎expert‏ ‎in‏ ‎MobileIron's ‎unique‏ ‎approach ‎to‏ ‎security ‎– ‎where ‎every ‎vulnerability‏ ‎is‏ ‎just‏ ‎an ‎opportunity‏ ‎for ‎"creative‏ ‎problem-solving." ‎Remember,‏ ‎with‏ ‎MobileIron, ‎your‏ ‎data ‎isn't ‎just ‎mobile, ‎it's‏ ‎on ‎the‏ ‎move...‏ ‎to ‎the ‎dark‏ ‎web!


Читать: 1+ мин
logo Overkill Security

FileWave or FailWave. Navigating the Stormy Seas of MDM Vulnerabilities

Hang ‎ten‏ ‎as ‎we ‎ride ‎the ‎gnarly‏ ‎waves ‎of‏ ‎FileWave‏ ‎MDM ‎insecurities:

📌Security ‎Risks:‏ ‎See ‎how‏ ‎FileWave ‎turns ‎your ‎data‏ ‎ocean‏ ‎into ‎a‏ ‎hacker's ‎paradise.

📌Technical‏ ‎Exploits: ‎Watch ‎in ‎awe ‎as‏ ‎your‏ ‎sensitive ‎information‏ ‎catches ‎the‏ ‎perfect ‎wave... ‎straight ‎into ‎an‏ ‎attacker's‏ ‎hands.

📌Mitigation‏ ‎Strategies: ‎Learn‏ ‎innovative ‎techniques‏ ‎like ‎"hoping‏ ‎for‏ ‎low ‎tide"‏ ‎and ‎"building ‎digital ‎sandcastles."

📌Impact ‎Assessment:‏ ‎Discover ‎the‏ ‎thrill‏ ‎of ‎data ‎breaches‏ ‎that'll ‎make‏ ‎your ‎head ‎spin ‎faster‏ ‎than‏ ‎a ‎surfer's‏ ‎wipeout.

After ‎this‏ ‎radical ‎journey, ‎you'll ‎be ‎ready‏ ‎to‏ ‎rename ‎FileWave‏ ‎to ‎"FileTsunami"‏ ‎and ‎consider ‎reverting ‎to ‎stone‏ ‎tablets‏ ‎for‏ ‎data ‎storage.‏ ‎Remember, ‎with‏ ‎FileWave, ‎your‏ ‎security‏ ‎isn't ‎just‏ ‎going ‎with ‎the ‎flow ‎–‏ ‎it's ‎being‏ ‎swept‏ ‎away ‎entirely!


Читать: 1+ мин
logo Overkill Security

AirWatch Out! Your MDM Solution Might Be Watching Your Data Leak


Prepare ‎for‏ ‎takeoff ‎as ‎we ‎soar ‎through‏ ‎the ‎turbulent‏ ‎skies‏ ‎of ‎AirWatch ‎MDM‏ ‎vulnerabilities:

📌Security ‎Risks:‏ ‎Marvel ‎at ‎AirWatch's ‎innovative‏ ‎"open-door"‏ ‎policy ‎for‏ ‎hackers ‎and‏ ‎data ‎thieves.

📌Technical ‎Exploits: ‎Witness ‎the‏ ‎magic‏ ‎of ‎turning‏ ‎your ‎secure‏ ‎enterprise ‎into ‎a ‎24/7 ‎all-you-can-eat‏ ‎data‏ ‎buffet‏ ‎for ‎cybercriminals.

📌Mitigation‏ ‎Strategies: Learn ‎advanced‏ ‎techniques ‎like‏ ‎"crossing‏ ‎your ‎fingers"‏ ‎and ‎"hoping ‎no ‎one ‎notices."

📌Impact‏ ‎Assessment: ‎Explore‏ ‎the‏ ‎exciting ‎possibilities ‎of‏ ‎complete ‎data‏ ‎exposure ‎and ‎corporate ‎embarrassment!

After‏ ‎this‏ ‎eye-opening ‎journey,‏ ‎you'll ‎be‏ ‎ready ‎to ‎rename ‎AirWatch ‎to‏ ‎"AirLeak"‏ ‎and ‎consider‏ ‎using ‎smoke‏ ‎signals ‎as ‎a ‎more ‎secure‏ ‎alternative.‏ ‎Remember,‏ ‎with ‎AirWatch,‏ ‎your ‎data‏ ‎isn't ‎just‏ ‎in‏ ‎the ‎cloud‏ ‎– ‎it's ‎free ‎as ‎a‏ ‎bird!


Читать: 2+ мин
logo Overkill Security

Blackberry’s Back, and So Are Its Security Flaws

In ‎this‏ ‎thrilling ‎exposé, ‎we’ll ‎dive ‎into‏ ‎the ‎not-so-secure‏ ‎world‏ ‎of ‎Blackberry ‎MDM,‏ ‎where ‎nostalgia‏ ‎meets ‎vulnerability! ‎Join ‎us‏ ‎on‏ ‎an ‎exciting‏ ‎journey ‎through:

📌Security‏ ‎Risks: Discover ‎how ‎Blackberry’s ‎«military-grade» ‎encryption‏ ‎is‏ ‎about ‎as‏ ‎effective ‎as‏ ‎a ‎paper ‎lock ‎on ‎a‏ ‎bank‏ ‎vault.

📌Technical‏ ‎Exploits: ‎Learn‏ ‎how ‎attackers‏ ‎can ‎turn‏ ‎your‏ ‎Blackberry-managed ‎devices‏ ‎into ‎their ‎personal ‎playground ‎faster‏ ‎than ‎you‏ ‎can‏ ‎say ‎«physical ‎keyboard.»

📌Mitigation‏ ‎Strategies: Explore ‎cutting-edge‏ ‎solutions ‎like ‎«turn ‎it‏ ‎off‏ ‎and ‎hope‏ ‎for ‎the‏ ‎best» ‎and ‎«pray ‎to ‎the‏ ‎cybersecurity‏ ‎gods.»

📌Impact ‎Assessment:‏ ‎Find ‎out‏ ‎how ‎your ‎organization ‎can ‎achieve‏ ‎total‏ ‎chaos‏ ‎with ‎just‏ ‎a ‎few‏ ‎simple ‎vulnerabilities!

By‏ ‎the‏ ‎end ‎of‏ ‎this ‎document, ‎you’ll ‎be ‎an‏ ‎expert ‎in‏ ‎Blackberry‏ ‎MDM ‎insecurities ‎and‏ ‎may ‎even‏ ‎consider ‎using ‎carrier ‎pigeons‏ ‎for‏ ‎more ‎secure‏ ‎communications. ‎Remember,‏ ‎in ‎the ‎world ‎of ‎Blackberry‏ ‎MDM,‏ ‎every ‎day‏ ‎is ‎Throwback‏ ‎Thursday ‎to ‎the ‎golden ‎age‏ ‎of‏ ‎mobile‏ ‎insecurity!


Читать: 12+ мин
logo Overkill Security

MalPurifier. Detoxifying Your Android, One Malicious Byte at a Time

Another ‎document‏ ‎to ‎analyze. ‎This ‎time, ‎it’s‏ ‎the ‎riveting‏ ‎«MalPurifier:‏ ‎Enhancing ‎Android ‎Malware‏ ‎Detection ‎with‏ ‎Adversarial ‎Purification ‎against ‎Evasion‏ ‎Attacks.»‏ ‎Because, ‎you‏ ‎know, ‎the‏ ‎world ‎really ‎needed ‎another ‎paper‏ ‎on‏ ‎Android ‎malware‏ ‎detection.

First, ‎we’ll‏ ‎dive ‎into ‎the ‎Introduction ‎and‏ ‎Motivation‏ ‎to‏ ‎understand ‎why‏ ‎yet ‎another‏ ‎solution ‎to‏ ‎the‏ ‎ever-escalating ‎threats‏ ‎of ‎Android ‎malware ‎is ‎necessary.‏ ‎Spoiler ‎alert:‏ ‎it’s‏ ‎because ‎current ‎machine‏ ‎learning-based ‎approaches‏ ‎are ‎as ‎vulnerable ‎as‏ ‎a‏ ‎house ‎of‏ ‎cards ‎in‏ ‎a ‎windstorm.

We’ll ‎then ‎move ‎on‏ ‎to‏ ‎the ‎Experimental‏ ‎Setup ‎and‏ ‎Results. ‎This ‎section ‎will ‎reveal‏ ‎how‏ ‎MalPurifier‏ ‎outperforms ‎other‏ ‎defenses, ‎achieving‏ ‎over ‎90,91%‏ ‎accuracy.‏ ‎Impressive, ‎if‏ ‎you ‎ignore ‎the ‎fact ‎that‏ ‎it’s ‎tested‏ ‎on‏ ‎datasets ‎that ‎may‏ ‎or ‎may‏ ‎not ‎reflect ‎real-world ‎scenarios.

The‏ ‎Defense‏ ‎Mechanisms ‎section‏ ‎will ‎discuss‏ ‎the ‎various ‎strategies ‎employed ‎by‏ ‎MalPurifier,‏ ‎such ‎as‏ ‎adversarial ‎purification‏ ‎and ‎adversarial ‎training. ‎Because ‎nothing‏ ‎says‏ ‎«robust‏ ‎defense» ‎like‏ ‎throwing ‎more‏ ‎adversarial ‎examples‏ ‎at‏ ‎the ‎problem.

Of‏ ‎course, ‎no ‎paper ‎is ‎complete‏ ‎without ‎acknowledging‏ ‎its‏ ‎Limitations ‎and ‎Future‏ ‎Work. ‎Here,‏ ‎the ‎authors ‎will ‎humbly‏ ‎admit‏ ‎that ‎their‏ ‎solution ‎isn’t‏ ‎perfect ‎and ‎suggest ‎areas ‎for‏ ‎future‏ ‎research. ‎Because,‏ ‎naturally, ‎the‏ ‎quest ‎for ‎the ‎perfect ‎malware‏ ‎detection‏ ‎system‏ ‎is ‎never-ending.

This‏ ‎analysis ‎will‏ ‎provide ‎a‏ ‎high-quality‏ ‎summary ‎of‏ ‎the ‎document, ‎highlighting ‎its ‎contributions‏ ‎and ‎implications‏ ‎for‏ ‎security ‎professionals ‎and‏ ‎other ‎specialists‏ ‎in ‎various ‎fields. ‎It‏ ‎will‏ ‎be ‎particularly‏ ‎useful ‎for‏ ‎those ‎who ‎enjoy ‎reading ‎about‏ ‎the‏ ‎latest ‎and‏ ‎greatest ‎in‏ ‎malware ‎detection, ‎even ‎if ‎the‏ ‎practical‏ ‎applications‏ ‎are ‎still‏ ‎up ‎for‏ ‎debate.

----

This ‎document‏ ‎provides‏ ‎a ‎comprehensive‏ ‎analysis ‎of ‎the ‎paper ‎titled‏ ‎«MalPurifier: ‎Enhancing‏ ‎Android‏ ‎Malware ‎Detection ‎with‏ ‎Adversarial ‎Purification‏ ‎against ‎Evasion ‎Attacks.» ‎The‏ ‎analysis‏ ‎delves ‎into‏ ‎various ‎aspects‏ ‎of ‎the ‎paper, ‎including ‎the‏ ‎motivation‏ ‎behind ‎the‏ ‎research, ‎the‏ ‎methodology ‎employed, ‎the ‎experimental ‎setup,‏ ‎and‏ ‎the‏ ‎results ‎obtained.

This‏ ‎analysis ‎provides‏ ‎a ‎high-quality‏ ‎summary‏ ‎of ‎the‏ ‎document, ‎offering ‎valuable ‎insights ‎for‏ ‎security ‎professionals,‏ ‎researchers,‏ ‎and ‎practitioners ‎in‏ ‎various ‎fields.‏ ‎By ‎understanding ‎the ‎strengths‏ ‎and‏ ‎limitations ‎of‏ ‎the ‎MalPurifier‏ ‎framework, ‎stakeholders ‎can ‎better ‎appreciate‏ ‎its‏ ‎potential ‎applications‏ ‎and ‎contributions‏ ‎to ‎enhancing ‎Android ‎malware ‎detection‏ ‎systems.‏ ‎The‏ ‎analysis ‎is‏ ‎useful ‎for‏ ‎those ‎involved‏ ‎in‏ ‎cybersecurity, ‎machine‏ ‎learning, ‎and ‎mobile ‎application ‎security,‏ ‎as ‎it‏ ‎highlights‏ ‎innovative ‎approaches ‎to‏ ‎mitigating ‎the‏ ‎risks ‎posed ‎by ‎adversarial‏ ‎evasion‏ ‎attacks.

The ‎paper‏ ‎titled ‎«MalPurifier:‏ ‎Enhancing ‎Android ‎Malware ‎Detection ‎with‏ ‎Adversarial‏ ‎Purification ‎against‏ ‎Evasion ‎Attacks»‏ ‎presents ‎a ‎novel ‎approach ‎to‏ ‎improving‏ ‎the‏ ‎detection ‎of‏ ‎Android ‎malware,‏ ‎particularly ‎in‏ ‎the‏ ‎face ‎of‏ ‎adversarial ‎evasion ‎attacks. ‎The ‎paper‏ ‎highlights ‎that‏ ‎this‏ ‎is ‎the ‎first‏ ‎attempt ‎to‏ ‎use ‎adversarial ‎purification ‎to‏ ‎mitigate‏ ‎evasion ‎attacks‏ ‎in ‎the‏ ‎Android ‎ecosystem, ‎providing ‎a ‎promising‏ ‎solution‏ ‎to ‎enhance‏ ‎the ‎security‏ ‎of ‎Android ‎malware ‎detection ‎systems.

Motivation:

📌 Prevalence‏ ‎of‏ ‎Android‏ ‎Malware: The ‎paper‏ ‎highlights ‎the‏ ‎widespread ‎issue‏ ‎of‏ ‎Android ‎malware,‏ ‎which ‎poses ‎significant ‎security ‎threats‏ ‎to ‎users‏ ‎and‏ ‎devices.

📌 Evasion ‎Techniques: Attackers ‎often‏ ‎use ‎evasion‏ ‎techniques ‎to ‎modify ‎malware,‏ ‎making‏ ‎it ‎difficult‏ ‎for ‎traditional‏ ‎detection ‎systems ‎to ‎identify ‎them.

Challenges:

📌 Adversarial‏ ‎Attacks:‏ ‎it ‎discusses‏ ‎the ‎challenge‏ ‎posed ‎by ‎adversarial ‎attacks, ‎where‏ ‎small‏ ‎perturbations‏ ‎are ‎added‏ ‎to ‎malware‏ ‎samples ‎to‏ ‎evade‏ ‎detection.

📌 Detection ‎System‏ ‎Vulnerabilities: Existing ‎malware ‎detection ‎systems ‎are‏ ‎vulnerable ‎to‏ ‎these‏ ‎adversarial ‎attacks, ‎leading‏ ‎to ‎a‏ ‎need ‎for ‎more ‎robust‏ ‎solutions.

Objective‏ ‎and ‎proposed‏ ‎Solution:

📌 Enhancing ‎Detection‏ ‎Robustness: The ‎primary ‎objective ‎of ‎the‏ ‎research‏ ‎is ‎to‏ ‎enhance ‎the‏ ‎robustness ‎of ‎Android ‎malware ‎detection‏ ‎systems‏ ‎against‏ ‎adversarial ‎evasion‏ ‎attacks.

📌 Adversarial ‎Purification: The‏ ‎proposed ‎solution,‏ ‎MalPurifier,‏ ‎aims ‎to‏ ‎purify ‎adversarial ‎examples, ‎removing ‎the‏ ‎perturbations ‎and‏ ‎restoring‏ ‎the ‎malware ‎to‏ ‎a ‎detectable‏ ‎form.

📌 Techniques ‎Used: The ‎system ‎employs‏ ‎techniques‏ ‎such ‎as‏ ‎autoencoders ‎and‏ ‎generative ‎adversarial ‎networks ‎(GANs) ‎for‏ ‎the‏ ‎purification ‎process.

Techniques‏ ‎Used ‎in‏ ‎Evasion ‎Attacks:

📌 Adversarial ‎Examples: Attackers ‎create ‎adversarial‏ ‎examples‏ ‎by‏ ‎adding ‎small‏ ‎perturbations ‎to‏ ‎malware ‎samples.‏ ‎These‏ ‎perturbations ‎are‏ ‎designed ‎to ‎exploit ‎vulnerabilities ‎in‏ ‎the ‎detection‏ ‎model’s‏ ‎decision ‎boundaries.

📌 Obfuscation: Techniques ‎such‏ ‎as ‎code‏ ‎encryption, ‎packing, ‎and ‎polymorphism‏ ‎are‏ ‎used ‎to‏ ‎alter ‎the‏ ‎appearance ‎of ‎the ‎malware ‎without‏ ‎changing‏ ‎its ‎functionality.

📌 Feature‏ ‎Manipulation: ‎Modifying‏ ‎features ‎used ‎by ‎the ‎detection‏ ‎model,‏ ‎such‏ ‎as ‎adding‏ ‎benign ‎features‏ ‎or ‎obfuscating‏ ‎malicious‏ ‎ones, ‎to‏ ‎evade ‎detection.

Significance:

📌 Improved ‎Security: ‎By ‎enhancing‏ ‎the ‎detection‏ ‎capabilities‏ ‎of ‎malware ‎detection‏ ‎systems, ‎MalPurifier‏ ‎aims ‎to ‎provide ‎better‏ ‎security‏ ‎for ‎Android‏ ‎devices.

📌 Research ‎Contribution:‏ ‎The ‎paper ‎contributes ‎to ‎the‏ ‎field‏ ‎by ‎addressing‏ ‎the ‎gap‏ ‎in ‎robust ‎malware ‎detection ‎solutions‏ ‎that‏ ‎can‏ ‎withstand ‎adversarial‏ ‎attacks.

Benefits

📌 High ‎Accuracy: MalPurifier‏ ‎demonstrates ‎high‏ ‎effectiveness,‏ ‎achieving ‎accuracies‏ ‎over ‎90,91% ‎against ‎37 ‎different‏ ‎evasion ‎attacks.‏ ‎This‏ ‎indicates ‎a ‎robust‏ ‎performance ‎in‏ ‎detecting ‎adversarially ‎perturbed ‎malware‏ ‎samples.

📌 Scalability:‏ ‎The ‎method‏ ‎is ‎easily‏ ‎scalable ‎to ‎different ‎detection ‎models,‏ ‎offering‏ ‎flexibility ‎and‏ ‎robustness ‎in‏ ‎its ‎implementation ‎without ‎requiring ‎significant‏ ‎modifications.

📌 Lightweight‏ ‎and‏ ‎Flexible: ‎The‏ ‎use ‎of‏ ‎a ‎plug-and-play‏ ‎Denoising‏ ‎AutoEncoder ‎(DAE)‏ ‎model ‎allows ‎for ‎a ‎lightweight‏ ‎and ‎flexible‏ ‎approach‏ ‎to ‎purifying ‎adversarial‏ ‎malware. ‎This‏ ‎ensures ‎that ‎the ‎method‏ ‎can‏ ‎be ‎integrated‏ ‎into ‎existing‏ ‎systems ‎with ‎minimal ‎overhead.

📌 Comprehensive ‎Defense:‏ ‎By‏ ‎focusing ‎on‏ ‎adversarial ‎purification,‏ ‎MalPurifier ‎addresses ‎a ‎critical ‎vulnerability‏ ‎in‏ ‎ML-based‏ ‎malware ‎detection‏ ‎systems, ‎enhancing‏ ‎their ‎overall‏ ‎security‏ ‎and ‎robustness‏ ‎against ‎sophisticated ‎evasion ‎techniques.

Limitations

📌 Generalization ‎to‏ ‎Other ‎Platforms: The‏ ‎current‏ ‎implementation ‎and ‎evaluation‏ ‎are ‎focused‏ ‎solely ‎on ‎the ‎Android‏ ‎ecosystem.‏ ‎The ‎effectiveness‏ ‎of ‎MalPurifier‏ ‎on ‎other ‎platforms, ‎such ‎as‏ ‎iOS‏ ‎or ‎Windows,‏ ‎remains ‎untested‏ ‎and ‎uncertain.

📌 Scalability ‎Concerns: While ‎the ‎paper‏ ‎claims‏ ‎scalability,‏ ‎the ‎actual‏ ‎performance ‎and‏ ‎efficiency ‎of‏ ‎MalPurifier‏ ‎in ‎large-scale,‏ ‎real-time ‎detection ‎scenarios ‎have ‎not‏ ‎been ‎thoroughly‏ ‎evaluated.‏ ‎This ‎raises ‎questions‏ ‎about ‎its‏ ‎practical ‎applicability ‎in ‎high-volume‏ ‎environments.

📌 Computational‏ ‎Overhead: ‎The‏ ‎purification ‎process‏ ‎introduces ‎additional ‎computational ‎overhead. ‎Although‏ ‎described‏ ‎as ‎lightweight,‏ ‎the ‎impact‏ ‎on ‎system ‎performance, ‎especially ‎in‏ ‎resource-constrained‏ ‎environments,‏ ‎needs ‎further‏ ‎investigation.

📌 Adversarial ‎Adaptation: Attackers‏ ‎may ‎develop‏ ‎new‏ ‎strategies ‎to‏ ‎adapt ‎to ‎the ‎purification ‎process,‏ ‎potentially ‎circumventing‏ ‎the‏ ‎defenses ‎provided ‎by‏ ‎MalPurifier. ‎Continuous‏ ‎adaptation ‎and ‎improvement ‎of‏ ‎the‏ ‎purification ‎techniques‏ ‎are ‎necessary‏ ‎to ‎stay ‎ahead ‎of ‎evolving‏ ‎threats.

📌 Evaluation‏ ‎Metrics: ‎The‏ ‎evaluation ‎primarily‏ ‎focuses ‎on ‎detection ‎accuracy ‎and‏ ‎robustness‏ ‎against‏ ‎evasion ‎attacks.‏ ‎Other ‎important‏ ‎metrics, ‎such‏ ‎as‏ ‎energy ‎consumption,‏ ‎user ‎experience, ‎and ‎long-term ‎efficacy,‏ ‎are ‎not‏ ‎addressed,‏ ‎limiting ‎the ‎comprehensiveness‏ ‎of ‎the‏ ‎assessment.

📌 Integration ‎with ‎Existing ‎Systems: The‏ ‎paper‏ ‎does ‎not‏ ‎extensively ‎discuss‏ ‎the ‎integration ‎of ‎MalPurifier ‎with‏ ‎existing‏ ‎malware ‎detection‏ ‎systems ‎and‏ ‎the ‎potential ‎impact ‎on ‎their‏ ‎performance.‏ ‎Seamless‏ ‎integration ‎strategies‏ ‎and ‎combined‏ ‎performance ‎evaluations‏ ‎are‏ ‎needed

Impact ‎on‏ ‎Technology

📌 Advancement ‎in ‎Malware ‎Detection: MalPurifier ‎represents‏ ‎a ‎significant‏ ‎technological‏ ‎advancement ‎in ‎the‏ ‎field ‎of‏ ‎malware ‎detection. ‎By ‎leveraging‏ ‎adversarial‏ ‎purification ‎techniques,‏ ‎it ‎enhances‏ ‎the ‎robustness ‎of ‎Android ‎malware‏ ‎detection‏ ‎systems ‎against‏ ‎evasion ‎attacks.‏ ‎This ‎innovation ‎can ‎lead ‎to‏ ‎the‏ ‎development‏ ‎of ‎more‏ ‎secure ‎and‏ ‎reliable ‎malware‏ ‎detection‏ ‎tools.

📌 Adversarial ‎Defense‏ ‎Mechanisms: ‎The ‎paper ‎contributes ‎to‏ ‎the ‎broader‏ ‎field‏ ‎of ‎adversarial ‎machine‏ ‎learning ‎by‏ ‎demonstrating ‎the ‎effectiveness ‎of‏ ‎adversarial‏ ‎purification. ‎This‏ ‎technique ‎can‏ ‎be ‎adapted ‎and ‎applied ‎to‏ ‎other‏ ‎areas ‎of‏ ‎cybersecurity, ‎such‏ ‎as ‎network ‎intrusion ‎detection ‎and‏ ‎endpoint‏ ‎security,‏ ‎thereby ‎improving‏ ‎the ‎overall‏ ‎resilience ‎of‏ ‎these‏ ‎systems ‎against‏ ‎sophisticated ‎attacks.

📌 Machine ‎Learning ‎Applications: The ‎use‏ ‎of ‎Denoising‏ ‎AutoEncoders‏ ‎(DAEs) ‎and ‎Generative‏ ‎Adversarial ‎Networks‏ ‎(GANs) ‎in ‎MalPurifier ‎showcases‏ ‎the‏ ‎potential ‎of‏ ‎advanced ‎machine‏ ‎learning ‎models ‎in ‎cybersecurity ‎applications.‏ ‎This‏ ‎can ‎inspire‏ ‎further ‎research‏ ‎and ‎development ‎in ‎applying ‎these‏ ‎models‏ ‎to‏ ‎other ‎security‏ ‎challenges, ‎such‏ ‎as ‎phishing‏ ‎detection‏ ‎and ‎fraud‏ ‎prevention.

Impact ‎on ‎Industry

📌 Enhanced ‎Security ‎for‏ ‎Mobile ‎Devices: Industries‏ ‎that‏ ‎rely ‎heavily ‎on‏ ‎mobile ‎devices,‏ ‎such ‎as ‎healthcare, ‎finance,‏ ‎and‏ ‎retail, ‎can‏ ‎benefit ‎from‏ ‎the ‎enhanced ‎security ‎provided ‎by‏ ‎MalPurifier.‏ ‎By ‎improving‏ ‎the ‎detection‏ ‎of ‎Android ‎malware, ‎these ‎industries‏ ‎can‏ ‎better‏ ‎protect ‎sensitive‏ ‎data ‎and‏ ‎maintain ‎the‏ ‎integrity‏ ‎of ‎their‏ ‎mobile ‎applications.

📌 Reduction ‎in ‎Cybersecurity ‎Incidents: The‏ ‎implementation ‎of‏ ‎robust‏ ‎malware ‎detection ‎systems‏ ‎like ‎MalPurifier‏ ‎can ‎lead ‎to ‎a‏ ‎reduction‏ ‎in ‎cybersecurity‏ ‎incidents, ‎such‏ ‎as ‎data ‎breaches ‎and ‎ransomware‏ ‎attacks.‏ ‎This ‎can‏ ‎result ‎in‏ ‎significant ‎cost ‎savings ‎for ‎businesses‏ ‎and‏ ‎reduce‏ ‎the ‎potential‏ ‎for ‎reputational‏ ‎damage.

📌 Compliance ‎and‏ ‎Regulatory‏ ‎Benefits: Enhanced ‎malware‏ ‎detection ‎capabilities ‎can ‎help ‎organizations‏ ‎comply ‎with‏ ‎regulatory‏ ‎requirements ‎related ‎to‏ ‎data ‎protection‏ ‎and ‎cybersecurity. ‎For ‎example,‏ ‎industries‏ ‎subject ‎to‏ ‎regulations ‎like‏ ‎GDPR ‎or ‎HIPAA ‎can ‎leverage‏ ‎MalPurifier‏ ‎to ‎ensure‏ ‎they ‎meet‏ ‎stringent ‎security ‎standards.

📌 Innovation ‎in ‎Cybersecurity‏ ‎Products: Cybersecurity‏ ‎companies‏ ‎can ‎incorporate‏ ‎the ‎techniques‏ ‎presented ‎in‏ ‎the‏ ‎paper ‎into‏ ‎their ‎products, ‎leading ‎to ‎the‏ ‎development ‎of‏ ‎next-generation‏ ‎security ‎solutions. ‎This‏ ‎can ‎provide‏ ‎a ‎competitive ‎edge ‎in‏ ‎the‏ ‎market ‎and‏ ‎drive ‎innovation‏ ‎in ‎the ‎cybersecurity ‎industry.

📌 Cross-Industry ‎Applications:‏ ‎While‏ ‎the ‎paper‏ ‎focuses ‎on‏ ‎Android ‎malware ‎detection, ‎the ‎underlying‏ ‎principles‏ ‎of‏ ‎adversarial ‎purification‏ ‎can ‎be‏ ‎applied ‎across‏ ‎various‏ ‎industries. ‎Sectors‏ ‎such ‎as ‎manufacturing, ‎public ‎administration,‏ ‎and ‎transportation,‏ ‎which‏ ‎are ‎also ‎affected‏ ‎by ‎malware,‏ ‎can ‎adapt ‎these ‎techniques‏ ‎to‏ ‎enhance ‎their‏ ‎cybersecurity ‎measures.



Читать: 5+ мин
logo Overkill Security

Oops, We Did It Again. CVE-2024-21111 Strikes


This ‎document‏ ‎dives ‎into ‎the ‎thrilling ‎world‏ ‎of ‎CVE-2024-21111,‏ ‎a‏ ‎delightful ‎vulnerability ‎in‏ ‎Oracle ‎VM‏ ‎VirtualBox ‎that ‎just ‎loves‏ ‎to‏ ‎wreak ‎havoc‏ ‎on ‎Windows‏ ‎hosts. ‎We’ll ‎be ‎dissecting ‎this‏ ‎gem‏ ‎from ‎every‏ ‎possible ‎angle,‏ ‎because ‎who ‎doesn’t ‎love ‎a‏ ‎good‏ ‎security‏ ‎nightmare?

This ‎document‏ ‎provides ‎a‏ ‎top-notch ‎summary‏ ‎of‏ ‎the ‎vulnerability,‏ ‎offering ‎insights ‎for ‎security ‎professionals‏ ‎and ‎other‏ ‎stakeholders‏ ‎who ‎just ‎can’t‏ ‎get ‎enough‏ ‎of ‎dealing ‎with ‎these‏ ‎kinds‏ ‎of ‎issues.‏ ‎The ‎analysis‏ ‎is ‎a ‎must-read ‎for ‎anyone‏ ‎who‏ ‎enjoys ‎understanding‏ ‎the ‎risks‏ ‎associated ‎with ‎CVE-2024-21111 ‎and ‎implementing‏ ‎measures‏ ‎to‏ ‎prevent ‎their‏ ‎systems ‎from‏ ‎becoming ‎the‏ ‎next‏ ‎victim. ‎Enjoy!

----

This‏ ‎document ‎provides ‎a ‎comprehensive ‎analysis‏ ‎of ‎CVE-2024-21111,‏ ‎a‏ ‎critical ‎vulnerability ‎in‏ ‎Oracle ‎VM‏ ‎VirtualBox ‎affecting ‎Windows ‎hosts.‏ ‎The‏ ‎analysis ‎will‏ ‎cover ‎various‏ ‎aspects ‎of ‎the ‎vulnerability, ‎including‏ ‎its‏ ‎technical ‎details,‏ ‎exploitation ‎mechanisms,‏ ‎potential ‎impacts ‎on ‎different ‎industries.

This‏ ‎document‏ ‎provides‏ ‎a ‎high-quality‏ ‎summary ‎of‏ ‎the ‎vulnerability,‏ ‎offering‏ ‎valuable ‎insights‏ ‎for ‎security ‎professionals ‎and ‎other‏ ‎stakeholders ‎across‏ ‎various‏ ‎industries. ‎The ‎analysis‏ ‎is ‎beneficial‏ ‎for ‎understanding ‎the ‎risks‏ ‎associated‏ ‎with ‎CVE-2024-21111‏ ‎and ‎implementing‏ ‎effective ‎measures ‎to ‎safeguard ‎systems‏ ‎against‏ ‎potential ‎attacks.

CVE-2024-21111‏ ‎is ‎a‏ ‎significant ‎security ‎vulnerability ‎identified ‎in‏ ‎Oracle‏ ‎VM‏ ‎VirtualBox, ‎specifically‏ ‎affecting ‎Windows‏ ‎hosts. ‎This‏ ‎vulnerability‏ ‎is ‎present‏ ‎in ‎versions ‎of ‎VirtualBox ‎prior‏ ‎to ‎7.0.16.‏ ‎It‏ ‎allows ‎a ‎low‏ ‎privileged ‎attacker‏ ‎with ‎logon ‎access ‎to‏ ‎the‏ ‎infrastructure ‎where‏ ‎Oracle ‎VM‏ ‎VirtualBox ‎is ‎executed ‎to ‎potentially‏ ‎take‏ ‎over ‎the‏ ‎system

An ‎attacker‏ ‎exploiting ‎this ‎vulnerability ‎could ‎achieve‏ ‎unauthorized‏ ‎control‏ ‎over ‎the‏ ‎affected ‎Oracle‏ ‎VM ‎VirtualBox.‏ ‎The‏ ‎specific ‎technical‏ ‎mechanism ‎involves ‎local ‎privilege ‎escalation‏ ‎through ‎symbolic‏ ‎link‏ ‎following, ‎which ‎can‏ ‎lead ‎to‏ ‎arbitrary ‎file ‎deletion ‎and‏ ‎movement.


📌 Vulnerability‏ ‎Type: ‎Local‏ ‎Privilege ‎Escalation‏ ‎(LPE) ‎allows ‎a ‎low ‎privileged‏ ‎attacker‏ ‎who ‎already‏ ‎has ‎access‏ ‎to ‎the ‎system ‎to ‎gain‏ ‎higher‏ ‎privileges.

📌 Attack‏ ‎Vector ‎and‏ ‎Complexity: ‎The‏ ‎CVSS ‎3.1‏ ‎vector‏ ‎(CVSS: ‎3.1/AV:‏ ‎L/AC: ‎L/PR: ‎L/UI: ‎N/S: ‎U/C:‏ ‎H/I: ‎H/A:‏ ‎H)‏ ‎indicates ‎that ‎the‏ ‎attack ‎vector‏ ‎is ‎local ‎(AV: ‎L),‏ ‎meaning‏ ‎the ‎attacker‏ ‎needs ‎local‏ ‎access ‎to ‎the ‎host. ‎The‏ ‎attack‏ ‎complexity ‎is‏ ‎low ‎(AC:‏ ‎L), ‎and ‎no ‎user ‎interaction‏ ‎(UI:‏ ‎N)‏ ‎is ‎required.‏ ‎The ‎privileges‏ ‎required ‎are‏ ‎low‏ ‎(PR: ‎L),‏ ‎suggesting ‎that ‎an ‎attacker ‎with‏ ‎basic ‎user‏ ‎privileges‏ ‎can ‎exploit ‎this‏ ‎vulnerability.

📌 Impact: The ‎impacts‏ ‎on ‎confidentiality, ‎integrity, ‎and‏ ‎availability‏ ‎are ‎all‏ ‎rated ‎high‏ ‎(C: ‎H/I: ‎H/A: ‎H), ‎indicating‏ ‎that‏ ‎an ‎exploit‏ ‎could ‎lead‏ ‎to ‎a ‎complete ‎compromise ‎of‏ ‎the‏ ‎affected‏ ‎system’s ‎confidentiality,‏ ‎integrity, ‎and‏ ‎availability.

📌 Exploitation ‎Method: The‏ ‎vulnerability‏ ‎can ‎be‏ ‎exploited ‎through ‎symbolic ‎link ‎(symlink)‏ ‎attacks. ‎This‏ ‎involves‏ ‎manipulating ‎symbolic ‎links‏ ‎to ‎redirect‏ ‎operations ‎intended ‎for ‎legitimate‏ ‎files‏ ‎or ‎directories‏ ‎to ‎other‏ ‎targets, ‎which ‎the ‎attacker ‎controls.‏ ‎This‏ ‎can ‎lead‏ ‎to ‎arbitrary‏ ‎file ‎deletion ‎or ‎movement, ‎potentially‏ ‎allowing‏ ‎the‏ ‎attacker ‎to‏ ‎execute ‎arbitrary‏ ‎code ‎with‏ ‎elevated‏ ‎privileges.

📌 Specific ‎Mechanism: The‏ ‎vulnerability ‎specifically ‎involves ‎the ‎manipulation‏ ‎of ‎log‏ ‎files‏ ‎by ‎the ‎VirtualBox‏ ‎system ‎service‏ ‎(VboxSDS). ‎The ‎service, ‎which‏ ‎runs‏ ‎with ‎SYSTEM‏ ‎privileges, ‎manages‏ ‎log ‎files ‎in ‎a ‎directory‏ ‎that‏ ‎does ‎not‏ ‎have ‎strict‏ ‎access ‎controls. ‎This ‎allows ‎a‏ ‎low‏ ‎privileged‏ ‎user ‎to‏ ‎manipulate ‎these‏ ‎files, ‎potentially‏ ‎leading‏ ‎to ‎privilege‏ ‎escalation. ‎The ‎service ‎performs ‎file‏ ‎rename/move ‎operations‏ ‎recursively,‏ ‎and ‎if ‎manipulated‏ ‎correctly, ‎this‏ ‎behavior ‎can ‎be ‎abused‏ ‎to‏ ‎perform ‎unauthorized‏ ‎actions.

📌 Mitigation: Users ‎are‏ ‎advised ‎to ‎update ‎their ‎VirtualBox‏ ‎to‏ ‎version ‎7.0.16‏ ‎or ‎later,‏ ‎which ‎contains ‎the ‎necessary ‎patches‏ ‎to‏ ‎mitigate‏ ‎this ‎vulnerability






Читать: 7+ мин
logo Overkill Security

Security Maturity Model. Even Cybersecurity Needs to Grow Up

The ‎Essential‏ ‎Eight ‎Maturity ‎Model, ‎that ‎grand‏ ‎old ‎strategic‏ ‎framework‏ ‎whipped ‎up ‎by‏ ‎the ‎wizards‏ ‎at ‎the ‎Australian ‎Cyber‏ ‎Security‏ ‎Centre ‎to‏ ‎magically ‎enhance‏ ‎cybersecurity ‎defenses ‎within ‎organizations. ‎This‏ ‎analysis‏ ‎promises ‎to‏ ‎dive ‎deep‏ ‎into ‎the ‎thrilling ‎world ‎of‏ ‎the‏ ‎model’s‏ ‎structure, ‎the‏ ‎Herculean ‎challenges‏ ‎of ‎implementation,‏ ‎and‏ ‎the ‎dazzling‏ ‎benefits ‎of ‎climbing ‎the ‎maturity‏ ‎ladder.

We’ll ‎provide‏ ‎a‏ ‎qualitative ‎summary ‎of‏ ‎this ‎legendary‏ ‎Essential ‎Eight ‎Maturity ‎Model,‏ ‎offering‏ ‎«valuable» ‎insights‏ ‎into ‎its‏ ‎application ‎and ‎effectiveness. ‎This ‎analysis‏ ‎is‏ ‎touted ‎as‏ ‎a ‎must-read‏ ‎for ‎security ‎professionals, ‎IT ‎managers,‏ ‎and‏ ‎decision-makers‏ ‎across ‎various‏ ‎industries, ‎who‏ ‎are ‎all‏ ‎presumably‏ ‎waiting ‎with‏ ‎bated ‎breath ‎to ‎discover ‎the‏ ‎secret ‎sauce‏ ‎for‏ ‎fortifying ‎their ‎organizations‏ ‎against ‎those‏ ‎pesky ‎cyber ‎threats.

So, ‎buckle‏ ‎up‏ ‎and ‎prepare‏ ‎for ‎an‏ ‎analysis ‎that ‎promises ‎to ‎be‏ ‎as‏ ‎enlightening ‎as‏ ‎it ‎is‏ ‎essential, ‎guiding ‎you ‎through ‎the‏ ‎mystical‏ ‎realm‏ ‎of ‎cybersecurity‏ ‎maturity ‎with‏ ‎the ‎grace‏ ‎and‏ ‎precision ‎of‏ ‎a ‎cybersecurity ‎guru.


----

This ‎document ‎provides‏ ‎an ‎analysis‏ ‎of‏ ‎the ‎Essential ‎Eight‏ ‎Maturity ‎Model,‏ ‎a ‎strategic ‎framework ‎developed‏ ‎by‏ ‎the ‎Australian‏ ‎Cyber ‎Security‏ ‎Centre ‎to ‎enhance ‎cybersecurity ‎defenses‏ ‎within‏ ‎organizations. ‎The‏ ‎analysis ‎will‏ ‎cover ‎various ‎aspects ‎of ‎the‏ ‎model,‏ ‎including‏ ‎its ‎structure,‏ ‎implementation ‎challenges,‏ ‎and ‎the‏ ‎benefits‏ ‎of ‎achieving‏ ‎different ‎maturity ‎levels.

The ‎analysis ‎offers‏ ‎valuable ‎insights‏ ‎into‏ ‎its ‎application ‎and‏ ‎effectiveness. ‎This‏ ‎analysis ‎is ‎particularly ‎useful‏ ‎for‏ ‎security ‎professionals,‏ ‎IT ‎managers,‏ ‎and ‎decision-makers ‎across ‎various ‎industries,‏ ‎helping‏ ‎them ‎to‏ ‎understand ‎how‏ ‎to ‎better ‎protect ‎their ‎organizations‏ ‎from‏ ‎cyber‏ ‎threats ‎and‏ ‎enhance ‎their‏ ‎cybersecurity ‎measures.


The‏ ‎Essential‏ ‎Eight ‎Maturity‏ ‎Model ‎provides ‎detailed ‎guidance ‎and‏ ‎information ‎for‏ ‎businesses‏ ‎and ‎government ‎entities‏ ‎on ‎implementing‏ ‎and ‎assessing ‎cybersecurity ‎practices.

📌 Purpose‏ ‎and‏ ‎Audience: ‎designed‏ ‎to ‎assist‏ ‎small ‎and ‎medium ‎businesses, ‎large‏ ‎organizations,‏ ‎and ‎government‏ ‎entities ‎in‏ ‎enhancing ‎their ‎cybersecurity ‎posture. ‎It‏ ‎serves‏ ‎as‏ ‎a ‎resource‏ ‎to ‎understand‏ ‎and ‎apply‏ ‎the‏ ‎Essential ‎Eight‏ ‎strategies ‎effectively.

📌 Content ‎Updates: ‎was ‎first‏ ‎published ‎on‏ ‎July‏ ‎16, ‎2021, ‎and‏ ‎has ‎been‏ ‎regularly ‎updated, ‎with ‎the‏ ‎latest‏ ‎update ‎on‏ ‎April ‎23,‏ ‎2024. ‎This ‎ensures ‎that ‎the‏ ‎information‏ ‎remains ‎relevant‏ ‎and ‎reflects‏ ‎the ‎latest ‎cybersecurity ‎practices ‎and‏ ‎threats.

📌 Resource‏ ‎Availability: available‏ ‎as ‎a‏ ‎downloadable, ‎titled‏ ‎«PROTECT ‎—‏ ‎Essential‏ ‎Eight ‎Maturity‏ ‎Model, ‎» ‎making ‎it ‎accessible‏ ‎for ‎offline‏ ‎use‏ ‎and ‎easy ‎distribution‏ ‎within ‎organizations.

📌 Feedback‏ ‎Mechanism: ‎users ‎are ‎encouraged‏ ‎to‏ ‎provide ‎feedback‏ ‎on ‎the‏ ‎usefulness ‎of ‎the ‎information, ‎which‏ ‎indicates‏ ‎an ‎ongoing‏ ‎effort ‎to‏ ‎improve ‎the ‎resource ‎based ‎on‏ ‎user‏ ‎input.

📌 Additional‏ ‎Services: page ‎http://cyber.gov.au also‏ ‎offers ‎links‏ ‎to ‎report‏ ‎cyber‏ ‎security ‎incidents,‏ ‎especially ‎for ‎critical ‎infrastructure, ‎and‏ ‎to ‎sign‏ ‎up‏ ‎for ‎alerts ‎on‏ ‎new ‎threats,‏ ‎highlighting ‎a ‎proactive ‎approach‏ ‎to‏ ‎cybersecurity.


The ‎Essential‏ ‎Eight ‎Maturity‏ ‎Model ‎FAQ ‎provides ‎comprehensive ‎guidance‏ ‎on‏ ‎implementing ‎and‏ ‎understanding ‎the‏ ‎Essential ‎Eight ‎strategies. ‎It ‎emphasizes‏ ‎a‏ ‎proactive,‏ ‎risk-based ‎approach‏ ‎to ‎cybersecurity,‏ ‎reflecting ‎the‏ ‎evolving‏ ‎nature ‎of‏ ‎cyber ‎threats ‎and ‎the ‎importance‏ ‎of ‎maintaining‏ ‎a‏ ‎balanced ‎and ‎comprehensive‏ ‎cybersecurity ‎posture


General‏ ‎Questions

📌 Essential ‎Eight ‎Overview: The ‎Essential‏ ‎Eight‏ ‎consists ‎of‏ ‎eight ‎mitigation‏ ‎strategies ‎recommended ‎for ‎organizations ‎to‏ ‎implement‏ ‎as ‎a‏ ‎baseline ‎to‏ ‎protect ‎against ‎cyber ‎threats. ‎These‏ ‎strategies‏ ‎are‏ ‎application ‎control,‏ ‎patch ‎applications,‏ ‎configure ‎Microsoft‏ ‎Office‏ ‎macro ‎settings,‏ ‎user ‎application ‎hardening, ‎restrict ‎administrative‏ ‎privileges, ‎patch‏ ‎operating‏ ‎systems, ‎multi-factor ‎authentication,‏ ‎and ‎regular‏ ‎backups.

📌 Purpose ‎of ‎Implementing ‎the‏ ‎Essential‏ ‎Eight: ‎Implementing‏ ‎the ‎Essential‏ ‎Eight ‎is ‎seen ‎as ‎a‏ ‎proactive‏ ‎measure ‎that‏ ‎is ‎more‏ ‎cost-effective ‎in ‎terms ‎of ‎time,‏ ‎money,‏ ‎and‏ ‎effort ‎compared‏ ‎to ‎responding‏ ‎to ‎a‏ ‎large-scale‏ ‎cyber ‎security‏ ‎incident.

📌 Essential ‎Eight ‎Maturity ‎Model ‎(E8MM): The‏ ‎E8MM ‎assists‏ ‎organizations‏ ‎in ‎implementing ‎the‏ ‎Essential ‎Eight‏ ‎in ‎a ‎graduated ‎manner‏ ‎based‏ ‎on ‎different‏ ‎levels ‎of‏ ‎tradecraft ‎and ‎targeting.


Updates ‎to ‎the‏ ‎Essential‏ ‎Eight ‎Maturity‏ ‎Model

📌 Reason ‎for‏ ‎Updates: ‎The ‎Australian ‎Signals ‎Directorate‏ ‎(ASD)‏ ‎updates‏ ‎the ‎E8MM‏ ‎to ‎ensure‏ ‎the ‎advice‏ ‎remains‏ ‎contemporary, ‎fit‏ ‎for ‎purpose, ‎and ‎practical. ‎Updates‏ ‎are ‎based‏ ‎on‏ ‎evolving ‎malicious ‎tradecraft,‏ ‎cyber ‎threat‏ ‎intelligence, ‎and ‎feedback ‎from‏ ‎Essential‏ ‎Eight ‎assessment‏ ‎and ‎uplift‏ ‎activities.

📌 Recent ‎Updates: ‎Recent ‎updates ‎include‏ ‎recommendations‏ ‎for ‎using‏ ‎an ‎automated‏ ‎method ‎of ‎asset ‎discovery ‎at‏ ‎least‏ ‎fortnightly‏ ‎and ‎ensuring‏ ‎vulnerability ‎scanners‏ ‎use ‎an‏ ‎up-to-date‏ ‎vulnerability ‎database.


Maturity‏ ‎Model ‎Updates ‎and ‎Implementation

📌 Redefinition ‎of‏ ‎Maturity ‎Levels: The‏ ‎July‏ ‎2021 ‎update ‎redefined‏ ‎the ‎number‏ ‎of ‎maturity ‎levels ‎and‏ ‎moved‏ ‎to ‎a‏ ‎stronger ‎risk-based‏ ‎approach ‎to ‎implementation. ‎It ‎also‏ ‎reintroduced‏ ‎Maturity ‎Level‏ ‎Zero ‎to‏ ‎provide ‎a ‎broader ‎range ‎of‏ ‎maturity‏ ‎level‏ ‎ratings.

📌 Risk-Based ‎Approach: The‏ ‎model ‎now‏ ‎emphasizes ‎a‏ ‎risk-based‏ ‎approach, ‎where‏ ‎circumstances ‎like ‎legacy ‎systems ‎and‏ ‎technical ‎debt‏ ‎are‏ ‎considered. ‎Choosing ‎not‏ ‎to ‎implement‏ ‎entire ‎mitigation ‎strategies ‎where‏ ‎technically‏ ‎feasible ‎is‏ ‎generally ‎considered‏ ‎Maturity ‎Level ‎Zero.

📌 Implementation ‎as ‎a‏ ‎Package:‏ ‎Organizations ‎are‏ ‎advised ‎to‏ ‎achieve ‎a ‎consistent ‎maturity ‎level‏ ‎across‏ ‎all‏ ‎eight ‎mitigation‏ ‎strategies ‎before‏ ‎moving ‎to‏ ‎a‏ ‎higher ‎maturity‏ ‎level. ‎This ‎approach ‎aims ‎to‏ ‎provide ‎a‏ ‎more‏ ‎secure ‎baseline ‎than‏ ‎achieving ‎higher‏ ‎maturity ‎levels ‎in ‎a‏ ‎few‏ ‎strategies ‎to‏ ‎the ‎detriment‏ ‎of ‎others.

Specific ‎Strategy ‎Updates

📌 Application ‎Control‏ ‎Changes: Additional‏ ‎executable ‎content‏ ‎types ‎were‏ ‎introduced ‎for ‎all ‎maturity ‎levels,‏ ‎and‏ ‎Maturity‏ ‎Level ‎One‏ ‎was ‎updated‏ ‎to ‎focus‏ ‎on‏ ‎using ‎file‏ ‎system ‎access ‎permissions ‎to ‎prevent‏ ‎malware ‎execution




Читать: 6+ мин
logo Overkill Security

MediHunt

The ‎paper‏ ‎«MediHunt: ‎A ‎Network ‎Forensics ‎Framework‏ ‎for ‎Medical‏ ‎IoT‏ ‎Devices» ‎is ‎a‏ ‎real ‎page-turner.‏ ‎It ‎starts ‎by ‎addressing‏ ‎the‏ ‎oh-so-urgent ‎need‏ ‎for ‎robust‏ ‎network ‎forensics ‎in ‎Medical ‎Internet‏ ‎of‏ ‎Things ‎(MIoT)‏ ‎environments. ‎You‏ ‎know, ‎those ‎environments ‎where ‎MQTT‏ ‎(Message‏ ‎Queuing‏ ‎Telemetry ‎Transport)‏ ‎networks ‎are‏ ‎the ‎darling‏ ‎of‏ ‎smart ‎hospitals‏ ‎because ‎of ‎their ‎lightweight ‎communication‏ ‎protocol.

MediHunt ‎is‏ ‎an‏ ‎automatic ‎network ‎forensics‏ ‎framework ‎designed‏ ‎for ‎real-time ‎detection ‎of‏ ‎network‏ ‎flow-based ‎traffic‏ ‎attacks ‎in‏ ‎MQTT ‎networks. ‎It ‎leverages ‎machine‏ ‎learning‏ ‎models ‎to‏ ‎enhance ‎detection‏ ‎capabilities ‎and ‎is ‎suitable ‎for‏ ‎deployment‏ ‎on‏ ‎those ‎ever-so-resource-constrained‏ ‎MIoT ‎devices.‏ ‎Because, ‎naturally,‏ ‎that’s‏ ‎what ‎we’ve‏ ‎all ‎been ‎losing ‎sleep ‎over.

These‏ ‎points ‎set‏ ‎the‏ ‎stage ‎for ‎the‏ ‎detailed ‎discussion‏ ‎of ‎the ‎framework, ‎its‏ ‎experimental‏ ‎setup, ‎and‏ ‎evaluation ‎presented‏ ‎in ‎the ‎subsequent ‎sections ‎of‏ ‎the‏ ‎paper. ‎Can’t‏ ‎wait ‎to‏ ‎dive ‎into ‎those ‎thrilling ‎details!

---

The‏ ‎paper‏ ‎addresses‏ ‎the ‎need‏ ‎for ‎robust‏ ‎network ‎forensics‏ ‎in‏ ‎Medical ‎Internet‏ ‎of ‎Things ‎(MIoT) ‎environments, ‎particularly‏ ‎focusing ‎on‏ ‎MQTT‏ ‎(Message ‎Queuing ‎Telemetry‏ ‎Transport) ‎networks.‏ ‎These ‎networks ‎are ‎commonly‏ ‎used‏ ‎in ‎smart‏ ‎hospital ‎environments‏ ‎for ‎their ‎lightweight ‎communication ‎protocol.‏ ‎It‏ ‎highlights ‎the‏ ‎challenges ‎in‏ ‎securing ‎MIoT ‎devices, ‎which ‎are‏ ‎often‏ ‎resource-constrained‏ ‎and ‎have‏ ‎limited ‎computational‏ ‎power. ‎The‏ ‎lack‏ ‎of ‎publicly‏ ‎available ‎flow-based ‎MQTT-specific ‎datasets ‎for‏ ‎training ‎attack‏ ‎detection‏ ‎systems ‎is ‎mentioned‏ ‎as ‎a‏ ‎significant ‎challenge.

The ‎paper ‎presents‏ ‎MediHunt‏ ‎as ‎an‏ ‎automatic ‎network‏ ‎forensics ‎solution ‎designed ‎for ‎real-time‏ ‎detection‏ ‎of ‎network‏ ‎flow-based ‎traffic‏ ‎attacks ‎in ‎MQTT ‎networks. ‎It‏ ‎aims‏ ‎to‏ ‎provide ‎a‏ ‎comprehensive ‎solution‏ ‎for ‎data‏ ‎collection,‏ ‎analysis, ‎attack‏ ‎detection, ‎presentation, ‎and ‎preservation ‎of‏ ‎evidence. ‎It‏ ‎is‏ ‎designed ‎to ‎detect‏ ‎a ‎variety‏ ‎of ‎TCP/IP ‎layers ‎and‏ ‎application‏ ‎layer ‎attacks‏ ‎on ‎MQTT‏ ‎networks. ‎It ‎leverages ‎machine ‎learning‏ ‎models‏ ‎to ‎enhance‏ ‎the ‎detection‏ ‎capabilities ‎and ‎is ‎suitable ‎for‏ ‎deployment‏ ‎on‏ ‎resource ‎constrained‏ ‎MIoT ‎devices.

The‏ ‎primary ‎objective‏ ‎of‏ ‎the ‎MediHunt‏ ‎is ‎to ‎strengthen ‎the ‎forensic‏ ‎analysis ‎capabilities‏ ‎in‏ ‎MIoT ‎environments, ‎ensuring‏ ‎that ‎malicious‏ ‎activities ‎can ‎be ‎traced‏ ‎and‏ ‎mitigated ‎effectively.

Benefits

📌 Real-time‏ ‎Attack ‎Detection:‏ ‎MediHunt ‎is ‎designed ‎to ‎detect‏ ‎network‏ ‎flow-based ‎traffic‏ ‎attacks ‎in‏ ‎real-time, ‎which ‎is ‎crucial ‎for‏ ‎mitigating‏ ‎potential‏ ‎damage ‎and‏ ‎ensuring ‎the‏ ‎security ‎of‏ ‎MIoT‏ ‎environments.

📌 Comprehensive ‎Forensic‏ ‎Capabilities: ‎The ‎framework ‎provides ‎a‏ ‎complete ‎solution‏ ‎for‏ ‎data ‎collection, ‎analysis,‏ ‎attack ‎detection,‏ ‎presentation, ‎and ‎preservation ‎of‏ ‎evidence.‏ ‎This ‎makes‏ ‎it ‎a‏ ‎robust ‎tool ‎for ‎network ‎forensics‏ ‎in‏ ‎MIoT ‎environments.

📌 Machine‏ ‎Learning ‎Integration:‏ ‎By ‎leveraging ‎machine ‎learning ‎models,‏ ‎MediHunt‏ ‎enhances‏ ‎its ‎detection‏ ‎capabilities. ‎The‏ ‎use ‎of‏ ‎a‏ ‎custom ‎dataset‏ ‎that ‎includes ‎flow ‎data ‎for‏ ‎both ‎TCP/IP‏ ‎layer‏ ‎and ‎application ‎layer‏ ‎attacks ‎allows‏ ‎for ‎more ‎accurate ‎and‏ ‎effective‏ ‎detection ‎of‏ ‎a ‎wide‏ ‎range ‎of ‎cyber-attacks.

📌 High ‎Performance: ‎The‏ ‎framework‏ ‎has ‎demonstrated‏ ‎high ‎performance,‏ ‎with ‎F1 ‎scores ‎and ‎detection‏ ‎accuracy‏ ‎exceeding‏ ‎0.99 ‎and‏ ‎indicates ‎that‏ ‎it ‎is‏ ‎highly‏ ‎reliable ‎in‏ ‎detecting ‎attacks ‎on ‎MQTT ‎networks.

📌 Resource‏ ‎Efficiency: ‎Despite‏ ‎its‏ ‎comprehensive ‎capabilities, ‎MediHunt‏ ‎is ‎designed‏ ‎to ‎be ‎resource-efficient, ‎making‏ ‎it‏ ‎suitable ‎for‏ ‎deployment ‎on‏ ‎resource-constrained ‎MIoT ‎devices ‎like ‎Raspberry‏ ‎Pi.

Drawbacks

📌 Dataset‏ ‎Limitations: ‎While‏ ‎MediHunt ‎uses‏ ‎a ‎custom ‎dataset ‎for ‎training‏ ‎its‏ ‎machine‏ ‎learning ‎models,‏ ‎the ‎creation‏ ‎and ‎maintenance‏ ‎of‏ ‎such ‎datasets‏ ‎can ‎be ‎challenging. ‎The ‎dataset‏ ‎needs ‎to‏ ‎be‏ ‎regularly ‎updated ‎to‏ ‎cover ‎new‏ ‎and ‎emerging ‎attack ‎scenarios.

📌 Resource‏ ‎Constraints:‏ ‎Although ‎MediHunt‏ ‎is ‎designed‏ ‎to ‎be ‎resource-efficient, ‎the ‎inherent‏ ‎limitations‏ ‎of ‎MIoT‏ ‎devices, ‎such‏ ‎as ‎limited ‎computational ‎power ‎and‏ ‎memory,‏ ‎can‏ ‎still ‎pose‏ ‎challenges. ‎Ensuring‏ ‎that ‎the‏ ‎framework‏ ‎runs ‎smoothly‏ ‎on ‎these ‎devices ‎without ‎impacting‏ ‎their ‎primary‏ ‎functions‏ ‎can ‎be ‎difficult.

📌 Complexity‏ ‎of ‎Implementation: Implementing‏ ‎and ‎maintaining ‎a ‎machine‏ ‎learning-based‏ ‎network ‎forensics‏ ‎framework ‎can‏ ‎be ‎complex. ‎It ‎requires ‎expertise‏ ‎in‏ ‎cybersecurity ‎and‏ ‎machine ‎learning,‏ ‎which ‎may ‎not ‎be ‎readily‏ ‎available‏ ‎in‏ ‎all ‎healthcare‏ ‎settings.

📌 Dependence ‎on‏ ‎Machine ‎Learning‏ ‎Models:‏ ‎The ‎effectiveness‏ ‎of ‎MediHunt ‎heavily ‎relies ‎on‏ ‎the ‎accuracy‏ ‎and‏ ‎robustness ‎of ‎its‏ ‎machine ‎learning‏ ‎models. ‎These ‎models ‎need‏ ‎to‏ ‎be ‎trained‏ ‎on ‎high-quality‏ ‎data ‎and ‎regularly ‎updated ‎to‏ ‎remain‏ ‎effective ‎against‏ ‎new ‎types‏ ‎of ‎attacks.

📌 Scalability ‎Issues: While ‎the ‎framework‏ ‎is‏ ‎suitable‏ ‎for ‎small-scale‏ ‎deployments ‎on‏ ‎devices ‎like‏ ‎Raspberry‏ ‎Pi, ‎scaling‏ ‎it ‎up ‎to ‎larger, ‎more‏ ‎complex ‎MIoT‏ ‎environments‏ ‎may ‎present ‎additional‏ ‎challenges. ‎Ensuring‏ ‎consistent ‎performance ‎and ‎reliability‏ ‎across‏ ‎a ‎larger‏ ‎network ‎of‏ ‎devices ‎can ‎be ‎difficult


Unpacking ‎in‏ ‎more‏ ‎detail



Читать: 6+ мин
logo Overkill Security

Detection of Energy Consumption Cyber Attacks on Smart Devices

In ‎a‏ ‎world ‎where ‎smart ‎devices ‎are‏ ‎supposed ‎to‏ ‎make‏ ‎our ‎lives ‎easier,‏ ‎«Detection ‎of‏ ‎Energy ‎Consumption ‎Cyber ‎Attacks‏ ‎on‏ ‎Smart ‎Devices»‏ ‎dives ‎into‏ ‎the ‎thrilling ‎saga ‎of ‎how‏ ‎these‏ ‎gadgets ‎can‏ ‎be ‎turned‏ ‎against ‎us. ‎Imagine ‎your ‎smart‏ ‎fridge‏ ‎plotting‏ ‎is ‎going‏ ‎to ‎drain‏ ‎your ‎energy‏ ‎bill‏ ‎while ‎you‏ ‎sleep, ‎or ‎your ‎thermostat ‎conspiring‏ ‎with ‎your‏ ‎toaster‏ ‎to ‎launch ‎a‏ ‎cyberattack. ‎This‏ ‎paper ‎heroically ‎proposes ‎a‏ ‎lightweight‏ ‎detection ‎framework‏ ‎to ‎save‏ ‎us ‎from ‎these ‎nefarious ‎appliances‏ ‎by‏ ‎analyzing ‎their‏ ‎energy ‎consumption‏ ‎patterns. ‎Because, ‎clearly, ‎the ‎best‏ ‎way‏ ‎to‏ ‎outsmart ‎a‏ ‎smart ‎device‏ ‎is ‎to‏ ‎monitor‏ ‎how ‎much‏ ‎juice ‎it’s ‎guzzling. ‎So, ‎next‏ ‎time ‎your‏ ‎smart‏ ‎light ‎bulb ‎flickers,‏ ‎don’t ‎worry—it’s‏ ‎just ‎the ‎algorithm ‎doing‏ ‎its‏ ‎job.

---

The ‎paper‏ ‎emphasizes ‎the‏ ‎rapid ‎integration ‎of ‎IoT ‎technology‏ ‎into‏ ‎smart ‎homes,‏ ‎highlighting ‎the‏ ‎associated ‎security ‎challenges ‎due ‎to‏ ‎resource‏ ‎constraints‏ ‎and ‎unreliable‏ ‎networks.

📌 Energy ‎Efficiency:‏ ‎it ‎emphasizes‏ ‎the‏ ‎significance ‎of‏ ‎energy ‎efficiency ‎in ‎IoT ‎systems,‏ ‎particularly ‎in‏ ‎smart‏ ‎home ‎environments ‎for‏ ‎comfort, ‎convenience,‏ ‎and ‎security.

📌 Vulnerability: ‎it ‎discusses‏ ‎the‏ ‎vulnerability ‎of‏ ‎IoT ‎devices‏ ‎to ‎cyberattacks ‎and ‎physical ‎attacks‏ ‎due‏ ‎to ‎their‏ ‎resource ‎constraints.‏ ‎It ‎underscores ‎the ‎necessity ‎of‏ ‎securing‏ ‎these‏ ‎devices ‎to‏ ‎ensure ‎their‏ ‎effective ‎deployment‏ ‎in‏ ‎real-world ‎scenarios.

📌 Proposed‏ ‎Detection ‎Framework: ‎The ‎authors ‎propose‏ ‎a ‎detection‏ ‎framework‏ ‎based ‎on ‎analyzing‏ ‎the ‎energy‏ ‎consumption ‎of ‎smart ‎devices.‏ ‎This‏ ‎framework ‎aims‏ ‎to ‎classify‏ ‎the ‎attack ‎status ‎of ‎monitored‏ ‎devices‏ ‎by ‎examining‏ ‎their ‎energy‏ ‎consumption ‎patterns.

📌 Two-Stage ‎Approach: ‎The ‎methodology‏ ‎involves‏ ‎a‏ ‎two-stage ‎approach.‏ ‎The ‎first‏ ‎stage ‎uses‏ ‎a‏ ‎short ‎time‏ ‎window ‎for ‎rough ‎attack ‎detection,‏ ‎while ‎the‏ ‎second‏ ‎stage ‎involves ‎more‏ ‎detailed ‎analysis.

📌 Lightweight‏ ‎Algorithm: ‎The ‎paper ‎introduces‏ ‎a‏ ‎lightweight ‎algorithm‏ ‎designed ‎to‏ ‎detect ‎energy ‎consumption ‎attacks ‎on‏ ‎smart‏ ‎home ‎devices.‏ ‎This ‎algorithm‏ ‎is ‎tailored ‎to ‎the ‎limited‏ ‎resources‏ ‎of‏ ‎IoT ‎devices‏ ‎and ‎considers‏ ‎three ‎different‏ ‎protocols:‏ ‎TCP, ‎UDP,‏ ‎and ‎MQTT.

📌 Packet ‎Reception ‎Rate ‎Analysis: The‏ ‎detection ‎technique‏ ‎relies‏ ‎on ‎analyzing ‎the‏ ‎packet ‎reception‏ ‎rate ‎of ‎smart ‎devices‏ ‎to‏ ‎identify ‎abnormal‏ ‎behavior ‎indicative‏ ‎of ‎energy ‎consumption ‎attacks.

Benefits

📌 Lightweight ‎Detection‏ ‎Algorithm: The‏ ‎proposed ‎algorithm‏ ‎is ‎designed‏ ‎to ‎be ‎lightweight, ‎making ‎it‏ ‎suitable‏ ‎for‏ ‎resource ‎constrained‏ ‎IoT ‎devices.‏ ‎This ‎ensures‏ ‎that‏ ‎the ‎detection‏ ‎mechanism ‎does ‎not ‎overly ‎burden‏ ‎the ‎devices‏ ‎it‏ ‎aims ‎to ‎protect.

📌 Protocol‏ ‎Versatility: The ‎algorithm‏ ‎considers ‎multiple ‎communication ‎protocols‏ ‎(TCP,‏ ‎UDP, ‎MQTT),‏ ‎enhancing ‎its‏ ‎applicability ‎across ‎various ‎types ‎of‏ ‎smart‏ ‎devices ‎and‏ ‎network ‎configurations.

📌 Two-Stage‏ ‎Detection ‎Approach: ‎The ‎use ‎of‏ ‎a‏ ‎two-stage‏ ‎detection ‎approach‏ ‎(short ‎and‏ ‎long-time ‎windows)‏ ‎improves‏ ‎the ‎accuracy‏ ‎of ‎detecting ‎energy ‎consumption ‎attacks‏ ‎while ‎minimizing‏ ‎false‏ ‎positives. ‎This ‎method‏ ‎allows ‎for‏ ‎both ‎quick ‎initial ‎detection‏ ‎and‏ ‎detailed ‎analysis.

📌 Real-Time‏ ‎Alerts: ‎The‏ ‎framework ‎promptly ‎alerts ‎administrators ‎upon‏ ‎detecting‏ ‎an ‎attack,‏ ‎enabling ‎quick‏ ‎response ‎and ‎mitigation ‎of ‎potential‏ ‎threats.

📌 Effective‏ ‎Anomaly‏ ‎Detection: ‎By‏ ‎measuring ‎packet‏ ‎reception ‎rates‏ ‎and‏ ‎analyzing ‎energy‏ ‎consumption ‎patterns, ‎the ‎algorithm ‎effectively‏ ‎identifies ‎deviations‏ ‎from‏ ‎normal ‎behavior, ‎which‏ ‎are ‎indicative‏ ‎of ‎cyberattacks.

Drawbacks

📌 Limited ‎Attack ‎Scenarios:‏ ‎The‏ ‎experimental ‎setup‏ ‎has ‎tested‏ ‎only ‎specific ‎types ‎of ‎attacks,‏ ‎which‏ ‎limit ‎the‏ ‎generalizability ‎of‏ ‎the ‎results ‎to ‎other ‎potential‏ ‎attack‏ ‎vectors‏ ‎not ‎covered‏ ‎in ‎the‏ ‎study.

📌 Scalability ‎Concerns:‏ ‎While‏ ‎the ‎algorithm‏ ‎is ‎designed ‎to ‎be ‎lightweight,‏ ‎its ‎scalability‏ ‎in‏ ‎larger, ‎more ‎complex‏ ‎smart ‎home‏ ‎environments ‎with ‎numerous ‎devices‏ ‎and‏ ‎varied ‎network‏ ‎conditions ‎may‏ ‎require ‎further ‎validation.

📌 Dependency ‎on ‎Baseline‏ ‎Data:‏ ‎The ‎effectiveness‏ ‎of ‎the‏ ‎detection ‎mechanism ‎relies ‎on ‎accurate‏ ‎baseline‏ ‎measurements‏ ‎of ‎packet‏ ‎reception ‎rates‏ ‎and ‎energy‏ ‎consumption.‏ ‎Any ‎changes‏ ‎in ‎the ‎normal ‎operating ‎conditions‏ ‎of ‎the‏ ‎devices‏ ‎could ‎affect ‎the‏ ‎baseline, ‎potentially‏ ‎leading ‎to ‎false ‎positives‏ ‎or‏ ‎negatives.

📌 Resource ‎Constraints:‏ ‎Despite ‎being‏ ‎lightweight, ‎the ‎algorithm ‎still ‎requires‏ ‎computational‏ ‎resources, ‎which‏ ‎might ‎be‏ ‎a ‎challenge ‎for ‎extremely ‎resource-limited‏ ‎devices.‏ ‎Continuous‏ ‎monitoring ‎and‏ ‎analysis ‎could‏ ‎also ‎impact‏ ‎the‏ ‎battery ‎life‏ ‎and ‎performance ‎of ‎these ‎devices.


Unpacking‏ ‎in ‎more‏ ‎detail


Читать: 3+ мин
logo Overkill Security

AntiPhishStack

In ‎a‏ ‎world ‎where ‎clicking ‎on ‎a‏ ‎link ‎is‏ ‎akin‏ ‎to ‎navigating ‎a‏ ‎minefield, ‎phishing‏ ‎emerges ‎as ‎the ‎supervillain.‏ ‎Enter‏ ‎our ‎heroes:‏ ‎the ‎researchers‏ ‎behind ‎this ‎paper, ‎armed ‎with‏ ‎their‏ ‎shiny ‎new‏ ‎weapon, ‎the‏ ‎AntiPhishStack. ‎It’s ‎not ‎just ‎any‏ ‎model;‏ ‎it’s‏ ‎a ‎two-phase,‏ ‎LSTM-powered, ‎cybercrime-fighting‏ ‎marvel ‎that‏ ‎doesn’t‏ ‎need ‎to‏ ‎know ‎squat ‎about ‎phishing ‎to‏ ‎catch ‎a‏ ‎phisher.

The‏ ‎methodology? ‎They’ve ‎concocted‏ ‎a ‎concoction‏ ‎so ‎potent ‎it ‎could‏ ‎make‏ ‎traditional ‎phishing‏ ‎detection ‎systems‏ ‎weep ‎in ‎their ‎outdatedness. ‎By‏ ‎harnessing‏ ‎the ‎mystical‏ ‎powers ‎of‏ ‎Long ‎Short-Term ‎Memory ‎networks ‎and‏ ‎the‏ ‎alchemy‏ ‎of ‎character-level‏ ‎TF-IDF ‎features,‏ ‎they’ve ‎created‏ ‎a‏ ‎phishing ‎detection‏ ‎elixir ‎that’s ‎supposed ‎to ‎be‏ ‎the ‎envy‏ ‎of‏ ‎cybersecurity ‎nerds ‎everywhere.

-------

The‏ ‎analysis ‎of‏ ‎document, ‎titled ‎«AntiPhishStack: ‎LSTM-based‏ ‎Stacked‏ ‎Generalization ‎Model‏ ‎for ‎Optimized‏ ‎Phishing ‎URL ‎Detection, ‎» ‎will‏ ‎cover‏ ‎various ‎aspects‏ ‎of ‎the‏ ‎document, ‎including ‎its ‎methodology, ‎results,‏ ‎and‏ ‎implications‏ ‎for ‎cybersecurity.‏ ‎Specifically, ‎the‏ ‎document’s ‎approach‏ ‎to‏ ‎using ‎Long‏ ‎Short-Term ‎Memory ‎(LSTM) ‎networks ‎within‏ ‎a ‎stacked‏ ‎generalization‏ ‎framework ‎for ‎detecting‏ ‎phishing ‎URLs‏ ‎will ‎be ‎examined. ‎The‏ ‎effectiveness‏ ‎of ‎the‏ ‎model, ‎its‏ ‎optimization ‎strategies, ‎and ‎its ‎performance‏ ‎compared‏ ‎to ‎existing‏ ‎methods ‎will‏ ‎be ‎scrutinized.

The ‎analysis ‎will ‎also‏ ‎delve‏ ‎into‏ ‎the ‎practical‏ ‎applications ‎of‏ ‎the ‎model,‏ ‎discussing‏ ‎how ‎it‏ ‎can ‎be ‎integrated ‎into ‎existing‏ ‎cybersecurity ‎measures‏ ‎and‏ ‎its ‎potential ‎impact‏ ‎on ‎reducing‏ ‎phishing ‎attacks. ‎The ‎document’s‏ ‎relevance‏ ‎to ‎cybersecurity‏ ‎professionals, ‎IT‏ ‎specialists, ‎and ‎stakeholders ‎in ‎various‏ ‎industries‏ ‎will ‎be‏ ‎highlighted, ‎emphasizing‏ ‎the ‎importance ‎of ‎advanced ‎phishing‏ ‎detection‏ ‎techniques‏ ‎in ‎the‏ ‎current ‎digital‏ ‎landscape. ‎This‏ ‎summary‏ ‎will ‎serve‏ ‎as ‎a ‎valuable ‎resource ‎for‏ ‎cybersecurity ‎experts,‏ ‎IT‏ ‎professionals, ‎and ‎others‏ ‎interested ‎in‏ ‎the ‎latest ‎developments ‎in‏ ‎phishing‏ ‎detection ‎and‏ ‎prevention.


Unpacking ‎in‏ ‎more ‎detail




Читать: 18+ мин
logo Snarky Security

Burnout and Liability: The Perks of Being a Modern CISO

The ‎«2024‏ ‎Voice ‎of ‎the ‎CISO» ‎report by‏ ‎Proofpoint ‎paints‏ ‎a‏ ‎vivid ‎picture ‎of‏ ‎the ‎tumultuous‏ ‎landscape ‎that ‎CISOs ‎have‏ ‎navigated‏ ‎recently ‎After‏ ‎all, ‎dealing‏ ‎with ‎a ‎global ‎pandemic, ‎the‏ ‎chaos‏ ‎of ‎remote‏ ‎work, ‎and‏ ‎record ‎levels ‎of ‎employee ‎turnover‏ ‎was‏ ‎just‏ ‎a ‎walk‏ ‎in ‎the‏ ‎park. ‎Now,‏ ‎with‏ ‎hybrid ‎working‏ ‎becoming ‎the ‎norm ‎and ‎cloud‏ ‎technology ‎expanding‏ ‎the‏ ‎attack ‎surface ‎to‏ ‎unprecedented ‎levels,‏ ‎CISOs ‎can ‎finally ‎relax,‏ ‎right?‏ ‎Wrong.

Cyber ‎threats‏ ‎are ‎more‏ ‎targeted, ‎sophisticated, ‎and ‎frequent ‎than‏ ‎ever.‏ ‎Employees ‎are‏ ‎more ‎mobile,‏ ‎often ‎taking ‎sensitive ‎data ‎with‏ ‎them‏ ‎as‏ ‎they ‎hop‏ ‎from ‎job‏ ‎to ‎job.‏ ‎And‏ ‎let’s ‎not‏ ‎forget ‎the ‎generative ‎AI ‎tools‏ ‎that, ‎while‏ ‎promising,‏ ‎have ‎also ‎made‏ ‎it ‎easier‏ ‎for ‎cybercriminals ‎to ‎launch‏ ‎devastating‏ ‎attacks ‎with‏ ‎just ‎a‏ ‎few ‎dollars.

Sure, ‎CISOs ‎are ‎enjoying‏ ‎closer‏ ‎ties ‎with‏ ‎key ‎stakeholders,‏ ‎board ‎members, ‎and ‎regulators. ‎But‏ ‎this‏ ‎newfound‏ ‎proximity ‎only‏ ‎brings ‎higher‏ ‎stakes, ‎more‏ ‎pressure,‏ ‎and ‎heightened‏ ‎expectations. ‎And ‎with ‎flat ‎or‏ ‎reduced ‎budgets,‏ ‎CISOs‏ ‎are ‎expected ‎to‏ ‎do ‎much‏ ‎more ‎with ‎considerably ‎less.‏ ‎In‏ ‎this ‎environment,‏ ‎shortcuts ‎are‏ ‎sometimes ‎necessary, ‎but ‎they ‎can‏ ‎lead‏ ‎to ‎human‏ ‎error—because, ‎of‏ ‎course, ‎everything ‎always ‎goes ‎perfectly‏ ‎when‏ ‎you’re‏ ‎under-resourced ‎and‏ ‎overworked.

To ‎better‏ ‎understand ‎how‏ ‎CISOs‏ ‎are ‎navigating‏ ‎yet ‎another ‎high-pressure ‎year, ‎Proofpoint‏ ‎surveyed ‎1,600‏ ‎CISOs‏ ‎worldwide. ‎They ‎asked‏ ‎about ‎their‏ ‎roles, ‎outlooks ‎for ‎the‏ ‎next‏ ‎two ‎years,‏ ‎and ‎how‏ ‎they ‎see ‎their ‎responsibilities ‎evolving.‏ ‎The‏ ‎report ‎explores‏ ‎the ‎delicate‏ ‎balance ‎between ‎concern ‎and ‎confidence‏ ‎as‏ ‎various‏ ‎factors ‎combine‏ ‎to ‎ramp‏ ‎up ‎the‏ ‎pressure‏ ‎on ‎CISOs.‏ ‎It ‎delves ‎into ‎the ‎persistent‏ ‎risks ‎posed‏ ‎by‏ ‎human ‎error, ‎the‏ ‎challenges ‎of‏ ‎burnout ‎and ‎personal ‎liability,‏ ‎and‏ ‎the ‎evolving‏ ‎relationship ‎between‏ ‎CISOs ‎and ‎the ‎boardroom.


Unpacking ‎in‏ ‎more‏ ‎detail ‎in‏ ‎PDF ‎(at‏ ‎the ‎end ‎of ‎post) ‎or‏ ‎below‏ ‎(plaintext)


Benefits

📌Comprehensive‏ ‎Data: ‎The‏ ‎report ‎surveys‏ ‎1,600 ‎CISOs‏ ‎from‏ ‎organizations ‎with‏ ‎1,000 ‎or ‎more ‎employees ‎across‏ ‎16 ‎countries,‏ ‎providing‏ ‎a ‎broad ‎and‏ ‎diverse ‎dataset.

📌Current‏ ‎Trends ‎and ‎Challenges: ‎It‏ ‎highlights‏ ‎key ‎issues‏ ‎such ‎as‏ ‎the ‎persistent ‎vulnerability ‎of ‎human‏ ‎error,‏ ‎the ‎impact‏ ‎of ‎generative‏ ‎AI, ‎and ‎the ‎economic ‎pressures‏ ‎on‏ ‎cybersecurity‏ ‎budgets.

📌Strategic ‎Insights:‏ ‎The ‎report‏ ‎offers ‎actionable‏ ‎insights‏ ‎and ‎recommendations,‏ ‎such ‎as ‎the ‎importance ‎of‏ ‎AI-powered ‎technologies,‏ ‎improving‏ ‎employee ‎cybersecurity ‎awareness,‏ ‎and ‎the‏ ‎need ‎for ‎robust ‎incident‏ ‎response‏ ‎plans.

📌Board-CISO ‎Relations:‏ ‎It ‎underscores‏ ‎the ‎improving ‎relationship ‎between ‎CISOs‏ ‎and‏ ‎board ‎members,‏ ‎which ‎is‏ ‎crucial ‎for ‎aligning ‎cybersecurity ‎strategies‏ ‎with‏ ‎business‏ ‎objectives.

Limitations

📌Overemphasis ‎on‏ ‎AI: The ‎report‏ ‎places ‎significant‏ ‎emphasis‏ ‎on ‎AI‏ ‎as ‎both ‎a ‎threat ‎and‏ ‎a ‎solution.‏ ‎While‏ ‎AI’s ‎role ‎in‏ ‎cybersecurity ‎is‏ ‎undeniable, ‎the ‎focus ‎might‏ ‎overshadow‏ ‎other ‎critical‏ ‎areas ‎that‏ ‎also ‎need ‎attention.

📌Potential ‎Bias ‎in‏ ‎Self-Reported‏ ‎Data: ‎The‏ ‎data ‎is‏ ‎self-reported ‎by ‎CISOs, ‎which ‎can‏ ‎introduce‏ ‎bias.‏ ‎CISOs ‎might‏ ‎overstate ‎their‏ ‎preparedness ‎or‏ ‎the‏ ‎effectiveness ‎of‏ ‎their ‎strategies ‎to ‎present ‎a‏ ‎more ‎favorable‏ ‎view‏ ‎of ‎their ‎performance.

📌Focus‏ ‎on ‎Large‏ ‎Organizations: ‎The ‎survey ‎targets‏ ‎organizations‏ ‎with ‎1,000‏ ‎or ‎more‏ ‎employees, ‎which ‎may ‎not ‎accurately‏ ‎reflect‏ ‎the ‎challenges‏ ‎and ‎realities‏ ‎faced ‎by ‎smaller ‎organizations. ‎This‏ ‎focus‏ ‎can‏ ‎limit ‎the‏ ‎applicability ‎of‏ ‎the ‎findings‏ ‎to‏ ‎a ‎broader‏ ‎range ‎of ‎businesses.

📌Economic ‎and ‎Regional‏ ‎Variations: ‎While‏ ‎the‏ ‎report ‎covers ‎multiple‏ ‎countries, ‎the‏ ‎economic ‎and ‎regulatory ‎environments‏ ‎vary‏ ‎significantly ‎across‏ ‎regions. ‎The‏ ‎findings ‎might ‎not ‎be ‎universally‏ ‎applicable,‏ ‎and ‎regional‏ ‎nuances ‎could‏ ‎be ‎underrepresented.

📌Human-Centric ‎Security: ‎Although ‎the‏ ‎report‏ ‎emphasizes‏ ‎human-centric ‎security,‏ ‎it ‎might‏ ‎not ‎fully‏ ‎address‏ ‎the ‎complexities‏ ‎of ‎implementing ‎such ‎strategies ‎effectively.‏ ‎The ‎reliance‏ ‎on‏ ‎user ‎education ‎and‏ ‎awareness ‎can‏ ‎be ‎seen ‎as ‎placing‏ ‎too‏ ‎much ‎responsibility‏ ‎on ‎employees‏ ‎rather ‎than ‎improving ‎systemic ‎defenses


Methodology

Survey‏ ‎Scope‏ ‎

📌The ‎survey‏ ‎was ‎conducted‏ ‎by ‎the ‎research ‎firm ‎Censuswide‏ ‎between‏ ‎January‏ ‎20 ‎—‏ ‎February ‎2,‏ ‎2024.

📌It ‎surveyed‏ ‎1,600‏ ‎Chief ‎Information‏ ‎Security ‎Officers ‎(CISOs) ‎from ‎organizations‏ ‎with ‎1,000‏ ‎or‏ ‎more ‎employees ‎across‏ ‎different ‎industries‏ ‎in ‎16 ‎countries.

📌100 CISOs ‎were‏ ‎interviewed‏ ‎in ‎each‏ ‎of ‎the‏ ‎following ‎markets: ‎U.S., ‎Canada, ‎U.K.,‏ ‎France,‏ ‎Germany, ‎Italy,‏ ‎Spain, ‎Sweden,‏ ‎the ‎Netherlands, ‎UAE, ‎Saudi ‎Arabia,‏ ‎Australia,‏ ‎Japan,‏ ‎Singapore, ‎South‏ ‎Korea, ‎and‏ ‎Brazil.

Industry ‎Representation:

📌IT,‏ ‎technology,‏ ‎and ‎telecoms‏ ‎(42%)

📌Manufacturing ‎and ‎production ‎(14%)

📌Financial ‎services‏ ‎(12%)

📌Retail ‎(8%)

📌Business‏ ‎and‏ ‎professional ‎services ‎(6%)

📌Public‏ ‎sector ‎(5%)

📌Healthcare‏ ‎(3%)

📌Education ‎(3%)

📌Media, ‎leisure, ‎and‏ ‎entertainment‏ ‎(3%)

📌Transport ‎(2%)

📌Energy,‏ ‎oil/gas, ‎and‏ ‎utilities ‎(2%)

Company ‎Size:

📌1,000 — 2,500 employees ‎(48%)

📌2,501 — 5,000 employees ‎(33%)

📌5,001 or‏ ‎more‏ ‎employees ‎(19%)

Research‏ ‎Standards:

📌Censuswide, ‎the‏ ‎research ‎firm ‎conducting ‎the ‎survey,‏ ‎complies‏ ‎with‏ ‎the ‎MRS‏ ‎Code ‎of‏ ‎Conduct ‎and‏ ‎ESOMAR‏ ‎principles, ‎ensuring‏ ‎adherence ‎to ‎industry ‎standards ‎and‏ ‎ethical ‎practices.


Heightened‏ ‎Concerns‏ ‎But ‎Growing ‎Confidence

Increased‏ ‎Risk ‎Perception:

📌Material‏ ‎Cyber ‎Attack ‎Risk: ‎Over‏ ‎two-thirds‏ ‎(70%) ‎of‏ ‎CISOs ‎feel‏ ‎at ‎risk ‎of ‎a ‎material‏ ‎cyber‏ ‎attack ‎in‏ ‎the ‎next‏ ‎12 ‎months, ‎a ‎slight ‎increase‏ ‎from‏ ‎68%‏ ‎last ‎year‏ ‎and ‎significantly‏ ‎higher ‎than‏ ‎48%‏ ‎in ‎2022.

📌High‏ ‎Likelihood: ‎31% of ‎CISOs ‎rate ‎the‏ ‎risk ‎of‏ ‎a‏ ‎significant ‎attack ‎as‏ ‎«very ‎likely,‏ ‎» ‎up ‎from ‎25%‏ ‎in‏ ‎2023.

Geographical ‎Concerns:

📌Most‏ ‎Concerned ‎Regions:‏ ‎CISOs ‎in ‎South ‎Korea ‎(91%),‏ ‎Canada‏ ‎(90%), ‎and‏ ‎the ‎US‏ ‎(87%) ‎are ‎the ‎most ‎concerned‏ ‎about‏ ‎experiencing‏ ‎a ‎material‏ ‎cyber ‎attack.

📌Optimistic‏ ‎Regions: ‎Brazil’s‏ ‎CISOs‏ ‎are ‎the‏ ‎most ‎optimistic, ‎with ‎only ‎45%‏ ‎fearing ‎an‏ ‎attack.

Industry-Specific‏ ‎Concerns:

📌High-Risk ‎Industries: ‎Education‏ ‎(86%), ‎transport‏ ‎(77%), ‎and ‎retail, ‎healthcare,‏ ‎and‏ ‎public ‎sector‏ ‎(all ‎74%)‏ ‎lead ‎in ‎cyber ‎attack ‎concerns.

Awareness‏ ‎vs.‏ ‎Preparedness:

📌Awareness: ‎While‏ ‎70% ‎of‏ ‎CISOs ‎feel ‎at ‎risk, ‎only‏ ‎43%‏ ‎believe‏ ‎their ‎organization‏ ‎is ‎unprepared‏ ‎to ‎cope‏ ‎with‏ ‎a ‎targeted‏ ‎cyber ‎attack ‎in ‎2024, ‎an‏ ‎improvement ‎from‏ ‎61%‏ ‎in ‎2023 ‎and‏ ‎50% ‎in‏ ‎2022.

📌Preparedness ‎Gap: ‎The ‎gap‏ ‎between‏ ‎awareness ‎and‏ ‎preparedness ‎remains‏ ‎a ‎concern, ‎highlighting ‎a ‎disconnect‏ ‎between‏ ‎recognizing ‎risks‏ ‎and ‎being‏ ‎ready ‎to ‎address ‎them.

Top ‎Threats:

📌Ransomware:‏ ‎41% of‏ ‎CISOs‏ ‎see ‎ransomware‏ ‎as ‎the‏ ‎leading ‎threat‏ ‎in‏ ‎the ‎next‏ ‎12 ‎months.

📌Other ‎Threats: ‎Malware ‎(38%),‏ ‎email ‎fraud‏ ‎(36%),‏ ‎cloud ‎account ‎compromise‏ ‎(34%), ‎insider‏ ‎threats ‎(30%), ‎and ‎DDoS‏ ‎attacks‏ ‎(30%) ‎are‏ ‎also ‎significant‏ ‎concerns.

Regional ‎Threat ‎Focus:

📌Ransomware: ‎Top ‎concern‏ ‎in‏ ‎Japan ‎(64%),‏ ‎UK ‎(51%),‏ ‎Sweden ‎(49%), ‎and ‎the ‎Netherlands‏ ‎(49%).

📌Email‏ ‎Fraud:‏ ‎Major ‎concern‏ ‎in ‎Saudi‏ ‎Arabia ‎(50%),‏ ‎Australia‏ ‎(46%), ‎Germany‏ ‎(46%), ‎Canada ‎(42%), ‎the ‎Netherlands‏ ‎(42%), ‎and‏ ‎Japan‏ ‎(42%).


Human ‎Error: ‎The‏ ‎Persistent ‎Vulnerability

Human‏ ‎Error ‎as ‎the ‎Biggest‏ ‎Vulnerability:

📌74% of‏ ‎CISOs ‎consider‏ ‎human ‎error‏ ‎to ‎be ‎their ‎organization’s ‎biggest‏ ‎cyber‏ ‎vulnerability, ‎up‏ ‎from ‎60%‏ ‎in ‎2023 ‎and ‎56% ‎in‏ ‎2022.

📌However,‏ ‎only‏ ‎63% ‎of‏ ‎board ‎members‏ ‎agree ‎that‏ ‎human‏ ‎error ‎is‏ ‎the ‎biggest ‎vulnerability, ‎suggesting ‎CISOs‏ ‎need ‎to‏ ‎better‏ ‎communicate ‎this ‎risk‏ ‎to ‎the‏ ‎board.

Employee ‎Negligence ‎as ‎a‏ ‎Key‏ ‎Concern:

📌80% of ‎CISOs‏ ‎see ‎human‏ ‎risk, ‎including ‎employee ‎negligence, ‎as‏ ‎a‏ ‎key ‎cybersecurity‏ ‎concern ‎over‏ ‎the ‎next ‎two ‎years, ‎up‏ ‎from‏ ‎63%‏ ‎in ‎2023.

📌This‏ ‎sentiment ‎was‏ ‎most ‎strongly‏ ‎felt‏ ‎in ‎France‏ ‎(91%), ‎Canada ‎(90%), ‎Spain ‎(86%),‏ ‎South ‎Korea‏ ‎(85%),‏ ‎and ‎Singapore ‎(84%).

Employee‏ ‎Awareness ‎vs.‏ ‎Capability:

📌86% of ‎CISOs ‎believe ‎their‏ ‎employees‏ ‎understand ‎their‏ ‎role ‎in‏ ‎defending ‎the ‎organization, ‎with ‎45%‏ ‎strongly‏ ‎agreeing.

📌However, ‎CISOs‏ ‎still ‎feel‏ ‎that ‎employees ‎pose ‎an ‎enormous‏ ‎risk,‏ ‎implying‏ ‎that ‎while‏ ‎employees ‎understand‏ ‎their ‎responsibilities,‏ ‎they‏ ‎lack ‎the‏ ‎necessary ‎skills, ‎knowledge, ‎and ‎tools‏ ‎to ‎effectively‏ ‎defend‏ ‎against ‎threats.

Adoption ‎of‏ ‎AI-Powered ‎Capabilities:

📌87% of‏ ‎CISOs ‎are ‎looking ‎to‏ ‎deploy‏ ‎AI-powered ‎capabilities‏ ‎to ‎protect‏ ‎against ‎human ‎error ‎and ‎block‏ ‎advanced‏ ‎human-centric ‎cyber‏ ‎threats.

📌Industries ‎leading‏ ‎the ‎adoption ‎include ‎retail ‎(81%),‏ ‎IT,‏ ‎technology,‏ ‎and ‎telecoms‏ ‎(89%), ‎and‏ ‎education ‎(88%).

Regional‏ ‎and‏ ‎Industry ‎Variations:

📌CISOs‏ ‎in ‎Saudi ‎Arabia ‎(84%), ‎Canada‏ ‎(83%), ‎and‏ ‎France‏ ‎(82%) ‎are ‎most‏ ‎concerned ‎about‏ ‎human ‎error ‎being ‎their‏ ‎organization’s‏ ‎biggest ‎cyber‏ ‎vulnerability.

📌Industries ‎with‏ ‎the ‎highest ‎concern ‎about ‎human‏ ‎error‏ ‎include ‎education‏ ‎(89%), ‎media,‏ ‎leisure, ‎and ‎entertainment ‎(85%), ‎and‏ ‎the‏ ‎public‏ ‎sector ‎(78%).


Data‏ ‎Protection ‎and‏ ‎Insider ‎Threats

Reduction‏ ‎in‏ ‎Data ‎Loss:

📌Fewer‏ ‎than ‎half ‎(46%) ‎of ‎global‏ ‎CISOs ‎reported‏ ‎a‏ ‎material ‎loss ‎of‏ ‎sensitive ‎information‏ ‎in ‎the ‎past ‎12‏ ‎months,‏ ‎down ‎from‏ ‎63% ‎last‏ ‎year.

Geographical ‎Variations:

📌South ‎Korea ‎(77%), ‎Canada‏ ‎(61%),‏ ‎France ‎(58%),‏ ‎and ‎Germany‏ ‎(57%) ‎reported ‎higher ‎rates ‎of‏ ‎sensitive‏ ‎data‏ ‎loss ‎compared‏ ‎to ‎the‏ ‎global ‎average.

Industry-Specific‏ ‎Data‏ ‎Loss:

📌Education ‎(68%),‏ ‎financial ‎services ‎(54%), ‎and ‎media,‏ ‎leisure, ‎and‏ ‎entertainment‏ ‎(54%) ‎sectors ‎were‏ ‎most ‎affected‏ ‎by ‎sensitive ‎data ‎loss.

Causes‏ ‎of‏ ‎Data ‎Loss:

📌Negligent‏ ‎insiders ‎or‏ ‎careless ‎employees ‎were ‎blamed ‎for‏ ‎42%‏ ‎of ‎data‏ ‎loss ‎incidents.

📌Other‏ ‎significant ‎causes ‎included ‎external ‎attacks‏ ‎(40%)‏ ‎and‏ ‎malicious ‎or‏ ‎criminal ‎insiders‏ ‎(36%).

📌Additional ‎factors‏ ‎included‏ ‎system ‎misconfiguration‏ ‎(27%) ‎and ‎lost ‎or ‎stolen‏ ‎devices ‎(28%).

Employee‏ ‎Turnover‏ ‎and ‎Data ‎Loss:

📌73% of‏ ‎CISOs ‎said‏ ‎that ‎employees ‎leaving ‎their‏ ‎organization‏ ‎played ‎a‏ ‎role ‎in‏ ‎data ‎loss ‎events.

📌Although ‎concern ‎around‏ ‎data‏ ‎loss ‎due‏ ‎to ‎job‏ ‎switchers ‎has ‎decreased ‎from ‎82%‏ ‎last‏ ‎year,‏ ‎it ‎remains‏ ‎a ‎significant‏ ‎issue.

Impact ‎of‏ ‎Data‏ ‎Loss:

📌The ‎consequences‏ ‎of ‎data ‎loss ‎included ‎financial‏ ‎loss ‎(43%),‏ ‎post-attack‏ ‎recovery ‎costs ‎(41%),‏ ‎and ‎loss‏ ‎of ‎critical ‎data ‎(40%).

Mitigation‏ ‎Strategies:

📌To‏ ‎combat ‎data‏ ‎loss, ‎CISOs‏ ‎are ‎focusing ‎on ‎educating ‎employees‏ ‎about‏ ‎security ‎best‏ ‎practices ‎(53%)‏ ‎and ‎using ‎cloud ‎security ‎solutions‏ ‎(52%).

📌Other‏ ‎measures‏ ‎include ‎deploying‏ ‎data ‎loss‏ ‎prevention ‎(DLP)‏ ‎technology‏ ‎(51%), ‎endpoint‏ ‎security ‎(49%), ‎email ‎security ‎(48%),‏ ‎and ‎isolation‏ ‎technology‏ ‎(42%).

Future ‎Priorities:

📌87% of ‎CISOs‏ ‎agree ‎that‏ ‎information ‎protection ‎and ‎data‏ ‎governance‏ ‎are ‎top‏ ‎priorities, ‎a‏ ‎significant ‎increase ‎from ‎previous ‎years.

📌The‏ ‎adoption‏ ‎of ‎DLP‏ ‎technology ‎has‏ ‎surged, ‎with ‎51% ‎of ‎CISOs‏ ‎now‏ ‎using‏ ‎it, ‎up‏ ‎from ‎35%‏ ‎last ‎year.

📌81% of‏ ‎CISOs‏ ‎believe ‎their‏ ‎data ‎is ‎adequately ‎protected, ‎up‏ ‎from ‎60%‏ ‎in‏ ‎2023.


The ‎Cyber ‎Realities‏ ‎for ‎a‏ ‎CISO ‎in ‎2024

Generative ‎AI:

📌Security‏ ‎Risks:‏ ‎54% of ‎CISOs‏ ‎believe ‎generative‏ ‎AI ‎poses ‎a ‎security ‎risk‏ ‎to‏ ‎their ‎organization.

📌Double-Edged‏ ‎Sword: While ‎AI‏ ‎can ‎aid ‎cybercriminals ‎by ‎making‏ ‎attacks‏ ‎easier‏ ‎to ‎scale‏ ‎and ‎execute,‏ ‎it ‎also‏ ‎provides‏ ‎defenders ‎with‏ ‎real-time ‎insights ‎into ‎threats, ‎which‏ ‎traditional ‎methods‏ ‎cannot‏ ‎match.

📌Top ‎Concerns: ‎ChatGPT‏ ‎and ‎other‏ ‎generative ‎AI ‎models ‎are‏ ‎seen‏ ‎as ‎significant‏ ‎risks, ‎followed‏ ‎by ‎collaboration ‎tools ‎like ‎Slack‏ ‎and‏ ‎Teams ‎(39%)‏ ‎and ‎Microsoft‏ ‎365 ‎(38%).

Economic ‎Impact:

📌Economic ‎Conditions: ‎59% of‏ ‎CISOs‏ ‎agree‏ ‎that ‎current‏ ‎economic ‎conditions‏ ‎have ‎negatively‏ ‎impacted‏ ‎their ‎organization’s‏ ‎ability ‎to ‎resource ‎cybersecurity ‎budgets.

📌Regional‏ ‎Impact: ‎CISOs‏ ‎in‏ ‎South ‎Korea ‎(79%),‏ ‎Canada ‎(72%),‏ ‎France ‎(68%), ‎and ‎Germany‏ ‎(68%)‏ ‎feel ‎the‏ ‎economic ‎impact‏ ‎most ‎acutely.

📌Budget ‎Constraints: ‎Nearly ‎half‏ ‎(48%)‏ ‎of ‎CISOs‏ ‎have ‎been‏ ‎asked ‎to ‎cut ‎staff, ‎delay‏ ‎backfills,‏ ‎or‏ ‎reduce ‎spending.

Priorities‏ ‎and ‎Strategies:

📌Top‏ ‎Priorities: Improving ‎information‏ ‎protection‏ ‎and ‎enabling‏ ‎business ‎innovation ‎remain ‎top ‎priorities‏ ‎for ‎58%‏ ‎of‏ ‎CISOs.

📌Employee ‎Cybersecurity ‎Awareness:‏ ‎Improving ‎employee‏ ‎cybersecurity ‎awareness ‎has ‎become‏ ‎the‏ ‎second-highest ‎priority,‏ ‎indicating ‎a‏ ‎shift ‎towards ‎human-centric ‎security ‎strategies.

Board‏ ‎Relations:

📌Alignment‏ ‎with ‎Board:‏ ‎84% of ‎CISOs‏ ‎now ‎see ‎eye ‎to ‎eye‏ ‎with‏ ‎their‏ ‎board ‎members‏ ‎on ‎cybersecurity‏ ‎issues, ‎up‏ ‎from‏ ‎62% ‎in‏ ‎2023.

📌Board-Level ‎Expertise: ‎84% of ‎CISOs ‎believe‏ ‎cybersecurity ‎expertise‏ ‎should‏ ‎be ‎required ‎at‏ ‎the ‎board‏ ‎level, ‎reflecting ‎a ‎significant‏ ‎increase‏ ‎from ‎previous‏ ‎years.

Challenges ‎and‏ ‎Pressures:

📌Unrealistic ‎Expectations: ‎66% of ‎CISOs ‎believe‏ ‎there‏ ‎are ‎excessive‏ ‎expectations ‎on‏ ‎their ‎role, ‎a ‎continued ‎increase‏ ‎from‏ ‎previous‏ ‎years.

📌Burnout: ‎More‏ ‎than ‎half‏ ‎(53%) ‎of‏ ‎CISOs‏ ‎have ‎experienced‏ ‎or ‎witnessed ‎burnout ‎in ‎the‏ ‎past ‎12‏ ‎months,‏ ‎although ‎there ‎is‏ ‎a ‎slight‏ ‎improvement ‎with ‎31% ‎reporting‏ ‎no‏ ‎burnout, ‎up‏ ‎from ‎15%‏ ‎last ‎year.

📌Personal ‎Liability: ‎66% of ‎CISOs‏ ‎are‏ ‎concerned ‎about‏ ‎personal, ‎financial,‏ ‎and ‎legal ‎liability, ‎with ‎72%‏ ‎unwilling‏ ‎to‏ ‎join ‎an‏ ‎organization ‎without‏ ‎directors ‎and‏ ‎officers‏ ‎(D& ‎O)‏ ‎insurance ‎or ‎similar ‎coverage.


Strengthening ‎Board-CISO‏ ‎Relations

Improved ‎Alignment:

📌Increased‏ ‎Agreement:‏ ‎84% of ‎CISOs ‎now‏ ‎report ‎seeing‏ ‎eye ‎to ‎eye ‎with‏ ‎their‏ ‎board ‎members‏ ‎on ‎cybersecurity‏ ‎issues, ‎a ‎significant ‎increase ‎from‏ ‎62%‏ ‎in ‎2023‏ ‎and ‎51%‏ ‎in ‎2022.

📌Industry ‎Variations: ‎The ‎highest‏ ‎levels‏ ‎of‏ ‎agreement ‎are‏ ‎seen ‎in‏ ‎healthcare ‎(91%),‏ ‎transport‏ ‎(88%), ‎and‏ ‎energy, ‎oil/gas, ‎and ‎utilities ‎(81%).

Board-Level‏ ‎Expertise:

📌Cybersecurity ‎Expertise:‏ ‎84% of‏ ‎CISOs ‎believe ‎that‏ ‎cybersecurity ‎expertise‏ ‎should ‎be ‎required ‎at‏ ‎the‏ ‎board ‎level,‏ ‎up ‎from‏ ‎62% ‎in ‎2023.

📌Regional ‎Differences: ‎CISOs‏ ‎in‏ ‎Saudi ‎Arabia‏ ‎(95%), ‎Brazil‏ ‎(92%), ‎Germany ‎(90%), ‎and ‎UAE‏ ‎(90%)‏ ‎report‏ ‎the ‎highest‏ ‎levels ‎of‏ ‎agreement ‎with‏ ‎their‏ ‎boards.

Board ‎Concerns:

📌Top‏ ‎Concerns: ‎CISOs ‎believe ‎that ‎their‏ ‎boards ‎are‏ ‎most‏ ‎concerned ‎about ‎disruption‏ ‎to ‎operations‏ ‎(44%), ‎loss ‎in ‎revenue‏ ‎(44%),‏ ‎and ‎reputational‏ ‎damage ‎(43%)‏ ‎in ‎the ‎event ‎of ‎a‏ ‎material‏ ‎cyber ‎attack.

📌Country-Specific‏ ‎Concerns: ‎Concerns‏ ‎vary ‎by ‎country, ‎with ‎some‏ ‎regions‏ ‎prioritizing‏ ‎different ‎aspects‏ ‎of ‎the‏ ‎impact ‎of‏ ‎cyber‏ ‎attacks.

Factors ‎Behind‏ ‎Improved ‎Relations:

📌Post-Pandemic ‎Influence: ‎Many ‎CISOs‏ ‎have ‎maintained‏ ‎their‏ ‎place ‎at ‎the‏ ‎table ‎post-pandemic,‏ ‎influencing ‎wider ‎business ‎strategy.

📌Communication:‏ ‎CISOs‏ ‎have ‎taken‏ ‎steps ‎to‏ ‎speak ‎the ‎language ‎of ‎the‏ ‎boardroom,‏ ‎translating ‎security‏ ‎concerns ‎into‏ ‎potential ‎business ‎impacts.

Enduring ‎Integration:

📌Long-Term ‎Change:‏ ‎The‏ ‎integration‏ ‎of ‎CISOs‏ ‎into ‎the‏ ‎boardroom ‎is‏ ‎seen‏ ‎as ‎an‏ ‎enduring ‎enhancement ‎to ‎business ‎strategy,‏ ‎necessary ‎for‏ ‎success‏ ‎in ‎the ‎modern‏ ‎digital ‎era.


The‏ ‎Story ‎Continues… ‎Unrelenting ‎Pressure‏ ‎on‏ ‎CISOs

Increased ‎Expectations:

📌Unrealistic‏ ‎Demands: ‎66% of‏ ‎CISOs ‎believe ‎there ‎are ‎excessive‏ ‎expectations‏ ‎on ‎their‏ ‎role, ‎a‏ ‎continued ‎increase ‎from ‎61% ‎in‏ ‎2023‏ ‎and‏ ‎49% ‎in‏ ‎2022.

📌Global ‎Variations:‏ ‎The ‎highest‏ ‎levels‏ ‎of ‎perceived‏ ‎excessive ‎expectations ‎are ‎in ‎Saudi‏ ‎Arabia ‎(88%),‏ ‎UAE‏ ‎(87%), ‎and ‎South‏ ‎Korea ‎(75%).

Burnout:

📌High‏ ‎Incidence: ‎More ‎than ‎half‏ ‎(53%)‏ ‎of ‎CISOs‏ ‎have ‎experienced‏ ‎or ‎witnessed ‎burnout ‎in ‎the‏ ‎past‏ ‎12 ‎months.

📌Improvement:‏ ‎There ‎is‏ ‎some ‎progress, ‎with ‎31% ‎of‏ ‎CISOs‏ ‎reporting‏ ‎no ‎burnout,‏ ‎up ‎from‏ ‎15% ‎last‏ ‎year.

📌Regional‏ ‎Differences: ‎CISOs‏ ‎in ‎South ‎Korea ‎(72%), ‎Sweden‏ ‎(63%), ‎and‏ ‎Australia‏ ‎(62%) ‎are ‎most‏ ‎likely ‎to‏ ‎have ‎experienced ‎or ‎witnessed‏ ‎burnout.

Personal‏ ‎Liability ‎Concerns:

📌Legal‏ ‎and ‎Financial‏ ‎Risks: ‎66% of ‎CISOs ‎are ‎concerned‏ ‎about‏ ‎personal, ‎financial,‏ ‎and ‎legal‏ ‎liability, ‎up ‎from ‎62% ‎in‏ ‎2023.

📌Insurance‏ ‎Coverage:‏ ‎72% of ‎CISOs‏ ‎would ‎not‏ ‎join ‎an‏ ‎organization‏ ‎without ‎directors‏ ‎and ‎officers ‎(D& ‎O) ‎insurance‏ ‎or ‎similar‏ ‎coverage‏ ‎against ‎financial ‎liability‏ ‎in ‎the‏ ‎event ‎of ‎a ‎successful‏ ‎cyberattack.

📌Industry‏ ‎Concerns: ‎CISOs‏ ‎in ‎manufacturing‏ ‎and ‎production ‎(75%), ‎financial ‎services‏ ‎(74%),‏ ‎and ‎retail‏ ‎(68%) ‎feel‏ ‎most ‎strongly ‎about ‎the ‎need‏ ‎for‏ ‎such‏ ‎insurance.

Impact ‎of‏ ‎High-Profile ‎Cases:

📌Influence‏ ‎of ‎Legal‏ ‎Cases:‏ ‎High-profile ‎legal‏ ‎cases, ‎such ‎as ‎the ‎SEC‏ ‎charges ‎against‏ ‎a‏ ‎SolarWinds ‎CISO, ‎have‏ ‎heightened ‎concerns‏ ‎about ‎personal ‎liability.

Ongoing ‎Challenges:

📌Resource‏ ‎Constraints:‏ ‎CISOs ‎continue‏ ‎to ‎face‏ ‎challenges ‎with ‎flat ‎or ‎reduced‏ ‎budgets,‏ ‎making ‎it‏ ‎difficult ‎to‏ ‎meet ‎the ‎growing ‎demands ‎and‏ ‎expectations‏ ‎placed‏ ‎on ‎them.


Conclusion

Increased‏ ‎Concern ‎but‏ ‎Improved ‎Preparedness:

📌More‏ ‎CISOs‏ ‎are ‎concerned‏ ‎about ‎a ‎material ‎cyber ‎attack‏ ‎in ‎the‏ ‎near‏ ‎future.

📌Fewer ‎CISOs ‎feel‏ ‎unprepared, ‎indicating‏ ‎greater ‎confidence ‎in ‎their‏ ‎defensive‏ ‎measures.

Closer ‎Relationships‏ ‎with ‎Stakeholders:

📌CISOs‏ ‎report ‎closer ‎relationships ‎with ‎key‏ ‎stakeholders‏ ‎and ‎the‏ ‎boardroom.

📌This ‎change‏ ‎highlights ‎the ‎growing ‎recognition ‎of‏ ‎the‏ ‎CISO‏ ‎role ‎at‏ ‎the ‎highest‏ ‎organizational ‎levels‏ ‎and‏ ‎the ‎importance‏ ‎of ‎cybersecurity.

Ongoing ‎Challenges:

📌Employee ‎Turnover: ‎Continues‏ ‎to ‎be‏ ‎a‏ ‎critical ‎concern, ‎with‏ ‎job ‎leavers‏ ‎posing ‎a ‎sustained ‎risk‏ ‎of‏ ‎data ‎loss‏ ‎across ‎all‏ ‎sectors.

📌Adoption ‎of ‎DLP ‎Technology: ‎Many‏ ‎CISOs‏ ‎have ‎adopted‏ ‎Data ‎Loss‏ ‎Prevention ‎(DLP) ‎technology ‎and ‎invested‏ ‎in‏ ‎employee‏ ‎education ‎to‏ ‎mitigate ‎this‏ ‎risk.

Evolving ‎Threat‏ ‎Landscape:


📌Familiar‏ ‎Threats: ‎Ransomware‏ ‎and ‎Business ‎Email ‎Compromise ‎(BEC)‏ ‎attacks ‎remain‏ ‎significant‏ ‎concerns.

📌Emerging ‎Technologies: ‎AI‏ ‎poses ‎new‏ ‎challenges ‎but ‎also ‎offers‏ ‎potential‏ ‎solutions.

Human-Centric ‎Security:

📌People‏ ‎and ‎their‏ ‎behaviors ‎continue ‎to ‎pose ‎the‏ ‎greatest‏ ‎ongoing ‎risk‏ ‎to ‎organizations.

📌Many‏ ‎CISOs ‎are ‎investing ‎more ‎in‏ ‎human-centric‏ ‎security‏ ‎approaches, ‎leveraging‏ ‎AI ‎to‏ ‎help ‎mitigate‏ ‎human‏ ‎error.

CISO ‎Role‏ ‎Challenges:

📌Personal ‎Liability: ‎Growing ‎concern ‎around‏ ‎personal ‎liability.

📌Excessive‏ ‎Expectations:‏ ‎Increasing ‎numbers ‎of‏ ‎CISOs ‎report‏ ‎excessive ‎expectations, ‎burnout, ‎and‏ ‎challenging‏ ‎budgets.

📌Addressing ‎these‏ ‎issues ‎is‏ ‎crucial ‎to ‎ensure ‎CISOs ‎are‏ ‎equipped‏ ‎for ‎their‏ ‎roles ‎now‏ ‎and ‎in ‎the ‎future.


Unpacking ‎in‏ ‎more‏ ‎detail‏ ‎in ‎PDF



Читать: 3+ мин
logo Snarky Security

Europol Cybercrime Training Competency Framework 2024

What ‎the‏ ‎world ‎really ‎needs ‎is ‎another‏ ‎deep ‎dive‏ ‎into‏ ‎the ‎«Europol ‎Cybercrime‏ ‎Training ‎Competency‏ ‎Framework ‎2024». ‎Here, ‎the‏ ‎brilliant‏ ‎minds ‎at‏ ‎Europol ‎decided‏ ‎to ‎state ‎the ‎obvious: ‎cybercrime‏ ‎is‏ ‎bad, ‎and‏ ‎we ‎need‏ ‎to ‎stop ‎it. ‎They’ve ‎created‏ ‎this‏ ‎framework‏ ‎to ‎outline‏ ‎the ‎skills‏ ‎necessary ‎to‏ ‎combat‏ ‎cybercrime, ‎because‏ ‎apparently, ‎it’s ‎not ‎enough ‎to‏ ‎just ‎be‏ ‎good‏ ‎with ‎a ‎computer‏ ‎anymore. ‎Who‏ ‎knew?

Moving ‎on ‎to ‎the‏ ‎«Approach‏ ‎and ‎Scope.»‏ ‎It’s ‎where‏ ‎they ‎tell ‎us ‎that ‎the‏ ‎framework‏ ‎isn’t ‎exhaustive.‏ ‎So, ‎in‏ ‎other ‎words, ‎they ‎spent ‎all‏ ‎this‏ ‎time‏ ‎putting ‎together‏ ‎a ‎document‏ ‎that ‎doesn’t‏ ‎cover‏ ‎everything. ‎Fantastic.‏ ‎They ‎also ‎mention ‎that ‎it’s‏ ‎not ‎an‏ ‎endorsement‏ ‎of ‎a ‎specific‏ ‎unit ‎structure,‏ ‎which ‎is ‎code ‎for‏ ‎«please‏ ‎don’t ‎blame‏ ‎us ‎if‏ ‎this ‎doesn’t ‎work ‎out.»

The ‎«Roles»‏ ‎section‏ ‎is ‎where‏ ‎things ‎get‏ ‎spicy. ‎They’ve ‎listed ‎various ‎roles‏ ‎like‏ ‎«Heads‏ ‎of ‎cybercrime‏ ‎units» ‎and‏ ‎«Cybercrime ‎analysts,‏ ‎»‏ ‎each ‎with‏ ‎their ‎own ‎set ‎of ‎required‏ ‎skills. ‎Because,‏ ‎as‏ ‎we ‎all ‎know,‏ ‎the ‎key‏ ‎to ‎stopping ‎cybercriminals ‎is‏ ‎making‏ ‎sure ‎everyone‏ ‎has ‎the‏ ‎right ‎title.

And ‎finally, ‎the ‎«Skill‏ ‎Sets»‏ ‎section. ‎This‏ ‎is ‎where‏ ‎they ‎list ‎all ‎the ‎skills‏ ‎you’ll‏ ‎need‏ ‎to ‎fight‏ ‎cybercrime, ‎from‏ ‎digital ‎forensics‏ ‎to‏ ‎cybercrime ‎legislation.‏ ‎It’s ‎a ‎bit ‎like ‎reading‏ ‎a ‎job‏ ‎description‏ ‎that ‎asks ‎for‏ ‎a ‎candidate‏ ‎who ‎speaks ‎12 ‎languages,‏ ‎can‏ ‎code ‎in‏ ‎15 ‎different‏ ‎programming ‎languages, ‎and ‎has ‎climbed‏ ‎Mount‏ ‎Everest—twice.

The ‎document‏ ‎tells ‎us‏ ‎we ‎need ‎to ‎be ‎prepared‏ ‎to‏ ‎tackle‏ ‎cybercrime ‎with‏ ‎a ‎specific‏ ‎set ‎of‏ ‎skills,‏ ‎roles, ‎and‏ ‎a ‎dash ‎of ‎optimism. ‎Because,‏ ‎in ‎the‏ ‎fight‏ ‎against ‎cybercrime, ‎it’s‏ ‎not ‎just‏ ‎about ‎having ‎the ‎right‏ ‎tools;‏ ‎it’s ‎about‏ ‎having ‎a‏ ‎document ‎that ‎says ‎you ‎have‏ ‎the‏ ‎right ‎tools.

Unpacking‏ ‎in ‎more‏ ‎detail

Читать: 4+ мин
logo Snarky Security

Choosing Secure and Verifiable Technologies

1


Another ‎document‏ ‎on ‎cybersecurity ‎practices—because ‎what ‎the‏ ‎world ‎needs‏ ‎is‏ ‎more ‎guidelines, ‎right?‏ ‎«Choosing ‎Secure‏ ‎and ‎Verifiable ‎Technologies» ‎rolls‏ ‎out‏ ‎the ‎red‏ ‎carpet ‎for‏ ‎organizations ‎that ‎are ‎knee-deep ‎in‏ ‎digital‏ ‎products ‎and‏ ‎services ‎but‏ ‎can’t ‎seem ‎to ‎figure ‎out‏ ‎the‏ ‎whole‏ ‎security ‎thing‏ ‎on ‎their‏ ‎own. ‎It’s‏ ‎packed‏ ‎with ‎everything‏ ‎from ‎the ‎joys ‎of ‎navigating‏ ‎manufacturer ‎transparency‏ ‎(because‏ ‎they’re ‎always ‎so‏ ‎forthcoming) ‎to‏ ‎the ‎rollercoaster ‎ride ‎of‏ ‎supply‏ ‎chain ‎risks‏ ‎(spoiler ‎alert:‏ ‎it’s ‎a ‎doozy!).

And ‎who ‎gets‏ ‎to‏ ‎enjoy ‎this‏ ‎page-turner? ‎Not‏ ‎just ‎anyone! ‎We’re ‎talking ‎high-level‏ ‎execs‏ ‎who‏ ‎need ‎to‏ ‎justify ‎their‏ ‎cybersecurity ‎budget,‏ ‎IT‏ ‎managers ‎who‏ ‎live ‎to ‎decode ‎another ‎risk‏ ‎assessment ‎matrix,‏ ‎and‏ ‎procurement ‎specialists ‎who‏ ‎get ‎giddy‏ ‎over ‎compliance ‎checklists. ‎But‏ ‎let’s‏ ‎not ‎forget‏ ‎the ‎manufacturers—they’re‏ ‎in ‎for ‎a ‎treat ‎learning‏ ‎about‏ ‎all ‎the‏ ‎hoops ‎they’ll‏ ‎need ‎to ‎jump ‎through ‎to‏ ‎prove‏ ‎their‏ ‎tech ‎is‏ ‎as ‎secure‏ ‎as ‎a‏ ‎duck‏ ‎in ‎a‏ ‎shark ‎cage.

So ‎buckle ‎up, ‎dear‏ ‎reader. ‎Whether‏ ‎you’re‏ ‎looking ‎to ‎safeguard‏ ‎national ‎security‏ ‎or ‎just ‎keep ‎your‏ ‎company’s‏ ‎data ‎from‏ ‎becoming ‎the‏ ‎next ‎headline, ‎this ‎document ‎promises‏ ‎to‏ ‎guide ‎you‏ ‎through ‎the‏ ‎cybersecurity ‎jungle ‎with ‎the ‎finesse‏ ‎of‏ ‎a‏ ‎machete-wielding ‎guide.‏ ‎Just ‎remember,‏ ‎it’s ‎not‏ ‎a‏ ‎checklist—it’s ‎a‏ ‎way ‎of ‎life.

-----

The ‎document ‎«Choosing‏ ‎Secure ‎and‏ ‎Verifiable‏ ‎Technologies» ‎provides ‎a‏ ‎comprehensive ‎analysis‏ ‎of ‎the ‎essential ‎aspects‏ ‎of‏ ‎selecting ‎secure‏ ‎digital ‎products‏ ‎and ‎services. ‎This ‎analysis ‎covers‏ ‎various‏ ‎critical ‎areas‏ ‎including ‎Secure-by-Design‏ ‎principles, ‎manufacturer ‎transparency, ‎risk ‎management,‏ ‎supply‏ ‎chain‏ ‎risks, ‎and‏ ‎post-purchase ‎considerations‏ ‎such ‎as‏ ‎maintenance‏ ‎and ‎end-of-life‏ ‎policies. ‎Each ‎section ‎offers ‎a‏ ‎detailed ‎examination‏ ‎of‏ ‎the ‎strategies ‎and‏ ‎practices ‎that‏ ‎enhance ‎the ‎security ‎and‏ ‎reliability‏ ‎of ‎technological‏ ‎procurements.

The ‎document‏ ‎is ‎particularly ‎beneficial ‎for ‎cybersecurity‏ ‎professionals,‏ ‎IT ‎managers,‏ ‎and ‎procurement‏ ‎specialists ‎across ‎various ‎industries. ‎It‏ ‎serves‏ ‎as‏ ‎a ‎valuable‏ ‎resource ‎by‏ ‎outlining ‎the‏ ‎necessary‏ ‎steps ‎to‏ ‎ensure ‎that ‎the ‎technologies ‎acquired‏ ‎not ‎only‏ ‎meet‏ ‎the ‎current ‎security‏ ‎standards ‎but‏ ‎also ‎adhere ‎to ‎ongoing‏ ‎security‏ ‎practices ‎to‏ ‎mitigate ‎future‏ ‎vulnerabilities. ‎This ‎analysis ‎aids ‎in‏ ‎making‏ ‎informed ‎decisions‏ ‎that ‎safeguard‏ ‎organizational ‎data ‎and ‎infrastructure ‎from‏ ‎potential‏ ‎cyber‏ ‎threats, ‎thereby‏ ‎enhancing ‎overall‏ ‎business ‎resilience.‏ ‎By‏ ‎integrating ‎these‏ ‎practices, ‎professionals ‎across ‎different ‎sectors‏ ‎can ‎significantly‏ ‎reduce‏ ‎the ‎risks ‎associated‏ ‎with ‎digital‏ ‎technologies ‎and ‎enhance ‎their‏ ‎operational‏ ‎security.

Unpacking ‎in‏ ‎more ‎detail

Читать: 2+ мин
logo Snarky Security

Offensive companies. Part II

Ah, ‎the‏ ‎shadowy ‎world ‎of ‎offensive ‎security‏ ‎private ‎companies,‏ ‎where‏ ‎the ‎line ‎between‏ ‎white ‎hats‏ ‎and ‎black ‎hats ‎is‏ ‎as‏ ‎clear ‎swing‏ ‎state.

These ‎enterprising‏ ‎companies ‎peddle ‎in ‎the ‎digital‏ ‎dark‏ ‎arts, ‎offering‏ ‎everything ‎from‏ ‎software ‎implants ‎to ‎intrusion ‎sets,‏ ‎and‏ ‎from‏ ‎0day ‎exploits‏ ‎to ‎security‏ ‎bypassing ‎techniques.

Most‏ ‎of‏ ‎them ‎have‏ ‎been ‎involved ‎in ‎nation-state ‎offensive‏ ‎cyber ‎operations,‏ ‎which‏ ‎is ‎just ‎a‏ ‎fancy ‎way‏ ‎of ‎saying ‎they ‎help‏ ‎governments‏ ‎spy ‎on‏ ‎each ‎other‏ ‎and ‎have ‎turned ‎paranoia ‎into‏ ‎profit,‏ ‎and ‎all‏ ‎it ‎took‏ ‎was ‎a ‎little ‎creativity ‎and‏ ‎a‏ ‎flexible‏ ‎moral ‎compass

So,‏ ‎if ‎you‏ ‎ever ‎feel‏ ‎like‏ ‎your ‎privacy‏ ‎is ‎being ‎respected ‎a ‎little‏ ‎too ‎much,‏ ‎just‏ ‎remember ‎that ‎there’s‏ ‎a ‎whole‏ ‎industry ‎out ‎there ‎working‏ ‎tirelessly‏ ‎to ‎ensure‏ ‎that ‎your‏ ‎secrets ‎are ‎as ‎private ‎as‏ ‎a‏ ‎tweet ‎on‏ ‎a ‎billboard.‏ ‎And ‎to ‎all ‎the ‎offensive‏ ‎security‏ ‎private‏ ‎companies ‎out‏ ‎there, ‎we‏ ‎salute ‎you.‏ ‎Without‏ ‎your ‎tireless‏ ‎efforts, ‎the ‎internet ‎would ‎be‏ ‎a ‎much‏ ‎less‏ ‎interesting ‎place

Unpacking ‎in‏ ‎more ‎detail

Читать: 4+ мин
logo Snarky Security

Patent. US9071600B2

The ‎patent‏ ‎US9071600B2 ‎is ‎a ‎delightful ‎example‏ ‎of ‎innovation,‏ ‎where‏ ‎it ‎introduces ‎a‏ ‎method ‎to‏ ‎prevent ‎phishing ‎and ‎online‏ ‎fraud‏ ‎by ‎establishing‏ ‎a ‎VPN‏ ‎tunnel ‎between ‎a ‎user ‎computer‏ ‎and‏ ‎a ‎server.‏ ‎This ‎patent,‏ ‎with ‎its ‎revolutionary ‎idea, ‎ensures‏ ‎that‏ ‎the‏ ‎user’s ‎data‏ ‎is ‎as‏ ‎secure ‎as‏ ‎a‏ ‎squirrel’s ‎nut‏ ‎in ‎winter. ‎It’s ‎a ‎marvel‏ ‎how ‎it‏ ‎uses‏ ‎such ‎a ‎complex‏ ‎technology ‎like‏ ‎a ‎VPN, ‎which ‎might‏ ‎just‏ ‎be ‎as‏ ‎old ‎as‏ ‎the ‎internet ‎itself, ‎to ‎create‏ ‎a‏ ‎secure ‎communication‏ ‎channel. ‎This‏ ‎method ‎is ‎not ‎just ‎about‏ ‎securing‏ ‎data‏ ‎but ‎also‏ ‎about ‎authenticating‏ ‎entities ‎and‏ ‎separating‏ ‎internal ‎networks‏ ‎from ‎external ‎threats, ‎which ‎is‏ ‎surely ‎something‏ ‎the‏ ‎world ‎has ‎never‏ ‎seen ‎before.

The‏ ‎patent ‎details ‎various ‎operations‏ ‎such‏ ‎as ‎the‏ ‎use ‎of‏ ‎hyperlinks, ‎webpages, ‎and ‎servers ‎to‏ ‎create‏ ‎a ‎fortress‏ ‎of ‎digital‏ ‎security. ‎It’s ‎almost ‎as ‎if‏ ‎the‏ ‎patent‏ ‎has ‎rediscovered‏ ‎the ‎wheel‏ ‎in ‎terms‏ ‎of‏ ‎online ‎security,‏ ‎providing ‎a ‎shield ‎against ‎the‏ ‎nefarious ‎acts‏ ‎of‏ ‎cyber ‎villains. ‎The‏ ‎classifications ‎under‏ ‎which ‎this ‎patent ‎is‏ ‎filed,‏ ‎such ‎as‏ ‎network ‎security‏ ‎protocols ‎for ‎authentication ‎of ‎entities‏ ‎and‏ ‎virtual ‎private‏ ‎networks, ‎are‏ ‎just ‎icing ‎on ‎the ‎cake,‏ ‎adding‏ ‎layers‏ ‎of ‎security‏ ‎that ‎are‏ ‎as ‎thick‏ ‎as‏ ‎a ‎bunker’s‏ ‎walls.

In ‎essence, ‎US9071600B2 ‎is ‎not‏ ‎just ‎a‏ ‎patent;‏ ‎it’s ‎a ‎beacon‏ ‎of ‎hope‏ ‎in ‎the ‎dark ‎world‏ ‎of‏ ‎cyber ‎threats,‏ ‎standing ‎tall‏ ‎like ‎a ‎lighthouse ‎guiding ‎the‏ ‎lost‏ ‎ships ‎in‏ ‎a ‎stormy‏ ‎sea ‎of ‎data ‎breaches ‎and‏ ‎online‏ ‎frauds.‏ ‎Truly, ‎a‏ ‎masterpiece ‎of‏ ‎modern ‎technology,‏ ‎wrapped‏ ‎in ‎the‏ ‎cloak ‎of ‎VPNs ‎and ‎network‏ ‎security ‎protocols!

-----

This‏ ‎analysis‏ ‎provides ‎a ‎examination‏ ‎of ‎patent‏ ‎US9071600B2, ‎which ‎pertains ‎to‏ ‎phishing‏ ‎and ‎online‏ ‎fraud ‎prevention.‏ ‎The ‎document ‎will ‎be ‎scrutinized‏ ‎to‏ ‎explore ‎various‏ ‎aspects ‎including‏ ‎the ‎technical ‎field, ‎the ‎problem‏ ‎addressed‏ ‎by‏ ‎the ‎invention,‏ ‎the ‎proposed‏ ‎solution, ‎and‏ ‎its‏ ‎principal ‎uses.

The‏ ‎detailed ‎analysis ‎of ‎patent ‎US9071600B2‏ ‎reveals ‎its‏ ‎potential‏ ‎to ‎significantly ‎impact‏ ‎the ‎field‏ ‎of ‎cybersecurity ‎and ‎various‏ ‎industries‏ ‎reliant ‎on‏ ‎secure ‎online‏ ‎operations. ‎The ‎document ‎offers ‎a‏ ‎quality‏ ‎extract ‎of‏ ‎the ‎patent,‏ ‎underscoring ‎its ‎utility ‎for ‎security‏ ‎professionals‏ ‎and‏ ‎specialists ‎seeking‏ ‎to ‎enhance‏ ‎online ‎safety‏ ‎and‏ ‎prevent ‎fraudulent‏ ‎activities. ‎For ‎cybersecurity ‎experts, ‎understanding‏ ‎the ‎mechanisms‏ ‎of‏ ‎such ‎a ‎system‏ ‎can ‎aid‏ ‎in ‎developing ‎more ‎robust‏ ‎security‏ ‎protocols ‎to‏ ‎combat ‎evolving‏ ‎online ‎threats. ‎For ‎professionals ‎in‏ ‎IT‏ ‎and ‎DevOps,‏ ‎the ‎patent’s‏ ‎focus ‎on ‎VPNs ‎and ‎secure‏ ‎communication‏ ‎channels‏ ‎is ‎particularly‏ ‎pertinent.


Unpacking ‎with‏ ‎more ‎detail


Читать: 4+ мин
logo Snarky Security

Patent US11611582B2

The ‎patent‏ ‎US11611582B2 ‎has ‎bestowed ‎upon ‎us‏ ‎a ‎computer-implemented‏ ‎method‏ ‎that ‎uses ‎a‏ ‎pre-defined ‎statistical‏ ‎model ‎to ‎detect ‎phishing‏ ‎threats.‏ ‎Because, ‎you‏ ‎know, ‎phishing‏ ‎is ‎such ‎a ‎novel ‎concept‏ ‎that‏ ‎we’ve ‎never‏ ‎thought ‎to‏ ‎guard ‎against ‎it ‎before.

This ‎method,‏ ‎a‏ ‎dazzling‏ ‎spectacle ‎of‏ ‎machine ‎learning‏ ‎wizardry, ‎dynamically‏ ‎analyzes‏ ‎network ‎requests‏ ‎in ‎real-time. ‎It’s ‎not ‎just‏ ‎any ‎analysis,‏ ‎though—it’s‏ ‎proactive! ‎That ‎means‏ ‎it ‎actually‏ ‎tries ‎to ‎stop ‎phishing‏ ‎attacks‏ ‎before ‎they‏ ‎happen, ‎unlike‏ ‎those ‎other ‎lazy ‎methods ‎that‏ ‎just‏ ‎sit ‎around‏ ‎waiting ‎for‏ ‎disaster ‎to ‎strike.

When ‎a ‎network‏ ‎request‏ ‎graciously‏ ‎makes ‎its‏ ‎way ‎to‏ ‎our ‎system,‏ ‎it‏ ‎must ‎first‏ ‎reveal ‎its ‎secrets—things ‎like ‎the‏ ‎fully ‎qualified‏ ‎domain‏ ‎name, ‎the ‎domain’s‏ ‎age ‎(because‏ ‎older ‎domains ‎clearly ‎have‏ ‎more‏ ‎wisdom), ‎the‏ ‎domain ‎registrar,‏ ‎IP ‎address, ‎and ‎even ‎its‏ ‎geographic‏ ‎location. ‎Because‏ ‎obviously, ‎geographic‏ ‎location ‎is ‎crucial. ‎Everyone ‎knows‏ ‎that‏ ‎phishing‏ ‎attacks ‎from‏ ‎scenic ‎locations‏ ‎are ‎less‏ ‎suspicious.

These‏ ‎juicy ‎details‏ ‎are ‎then ‎fed ‎to ‎the‏ ‎ever-hungry, ‎pre-trained‏ ‎statistical‏ ‎model, ‎which, ‎in‏ ‎its ‎infinite‏ ‎wisdom, ‎calculates ‎a ‎probability‏ ‎score.‏ ‎This ‎score,‏ ‎a ‎beacon‏ ‎of ‎numerical ‎judgment, ‎tells ‎us‏ ‎the‏ ‎likelihood ‎that‏ ‎this ‎humble‏ ‎network ‎request ‎is ‎actually ‎a‏ ‎wolf‏ ‎in‏ ‎sheep’s ‎clothing,‏ ‎a.k.a. ‎a‏ ‎phishing ‎threat.

And‏ ‎should‏ ‎this ‎score‏ ‎dare ‎exceed ‎the ‎sanctity ‎of‏ ‎our ‎pre-defined‏ ‎threshold—an‏ ‎arbitrary ‎line ‎in‏ ‎the ‎cyber‏ ‎sand—an ‎alert ‎is ‎generated.‏ ‎Because‏ ‎nothing ‎says‏ ‎«I’m ‎on‏ ‎top ‎of ‎things» ‎like ‎a‏ ‎good‏ ‎old-fashioned ‎alert.

This‏ ‎statistical ‎model‏ ‎isn’t ‎some ‎static ‎relic; ‎it’s‏ ‎a‏ ‎living,‏ ‎learning ‎creature.‏ ‎It’s ‎trained‏ ‎on ‎datasets‏ ‎teeming‏ ‎with ‎known‏ ‎phishing ‎and ‎non-phishing ‎examples ‎and‏ ‎is ‎periodically‏ ‎updated‏ ‎with ‎fresh ‎data‏ ‎to ‎keep‏ ‎up ‎with ‎the ‎ever-evolving‏ ‎fashion‏ ‎trends ‎of‏ ‎phishing ‎attacks.

Truly,‏ ‎we ‎are ‎blessed ‎to ‎have‏ ‎such‏ ‎an ‎innovative‏ ‎tool ‎at‏ ‎our ‎disposal, ‎tirelessly ‎defending ‎our‏ ‎digital‏ ‎realms‏ ‎from ‎the‏ ‎ceaseless ‎onslaught‏ ‎of ‎phishing‏ ‎attempts.‏ ‎What ‎would‏ ‎we ‎do ‎without ‎it? ‎Probably‏ ‎just ‎use‏ ‎common‏ ‎sense, ‎but ‎where’s‏ ‎the ‎fun‏ ‎in ‎that?

-----

This ‎document ‎will‏ ‎provide‏ ‎a ‎analysis‏ ‎of ‎patent‏ ‎US11611582B2, ‎which ‎describes ‎a ‎computer-implemented‏ ‎method‏ ‎for ‎detecting‏ ‎phishing ‎threats.‏ ‎The ‎analysis ‎will ‎cover ‎various‏ ‎aspects‏ ‎of‏ ‎the ‎patent,‏ ‎including ‎its‏ ‎technical ‎details,‏ ‎potential‏ ‎applications, ‎and‏ ‎implications ‎for ‎cybersecurity ‎professionals ‎and‏ ‎other ‎industry‏ ‎sectors.

Furthermore,‏ ‎it ‎has ‎a‏ ‎relevance ‎to‏ ‎the ‎evolving ‎landscape ‎of‏ ‎DevSecOps‏ ‎underscores ‎its‏ ‎potential ‎to‏ ‎contribute ‎to ‎more ‎secure ‎and‏ ‎efficient‏ ‎software ‎development‏ ‎lifecycles ‎as‏ ‎it ‎offers ‎a ‎methodical ‎approach‏ ‎to‏ ‎phishing‏ ‎detection ‎that‏ ‎can ‎be‏ ‎adopted ‎by‏ ‎various‏ ‎tools ‎and‏ ‎services ‎to ‎safeguard ‎users ‎and‏ ‎organizations ‎from‏ ‎malicious‏ ‎online ‎activities. ‎Cybersecurity‏ ‎professionals ‎should‏ ‎consider ‎integrating ‎such ‎methods‏ ‎into‏ ‎their ‎defensive‏ ‎strategies ‎to‏ ‎stay ‎ahead ‎of ‎emerging ‎threats.


Unpacking‏ ‎with‏ ‎more ‎detail


Читать: 3+ мин
logo Snarky Security

Patent US11496512B2

Let’s ‎dive‏ ‎into ‎the ‎thrilling ‎world ‎of‏ ‎patent ‎of‏ ‎Lookout,‏ ‎Inc., ‎a ‎masterpiece‏ ‎ingeniously ‎titled‏ ‎«Detecting ‎Real ‎time ‎Phishing‏ ‎from‏ ‎a ‎Phished‏ ‎Client ‎or‏ ‎at ‎a ‎Security ‎Server.» ‎Because,‏ ‎you‏ ‎know, ‎the‏ ‎world ‎was‏ ‎desperately ‎waiting ‎for ‎another ‎patent‏ ‎to‏ ‎save‏ ‎us ‎from‏ ‎the ‎clutches‏ ‎of ‎phishing‏ ‎attacks.

In‏ ‎a ‎world‏ ‎teeming ‎with ‎cyber ‎security ‎solutions,‏ ‎our ‎valiant‏ ‎inventors‏ ‎have ‎emerged ‎with‏ ‎a ‎groundbreaking‏ ‎method: ‎inserting ‎an ‎encoded‏ ‎tracking‏ ‎value ‎(ETV)‏ ‎into ‎webpages.‏ ‎This ‎revolutionary ‎technique ‎promises ‎to‏ ‎shield‏ ‎us ‎from‏ ‎the ‎ever-so-slight‏ ‎inconvenience ‎of ‎phishing ‎attacks ‎by‏ ‎tracking‏ ‎our‏ ‎every ‎move‏ ‎online. ‎How‏ ‎comforting!

----

This ‎document‏ ‎provides‏ ‎an ‎in-depth‏ ‎analysis ‎of ‎US11496512B2, ‎a ‎patent‏ ‎that ‎outlines‏ ‎innovative‏ ‎techniques ‎for ‎detecting‏ ‎phishing ‎websites.‏ ‎The ‎analysis ‎covers ‎various‏ ‎aspects‏ ‎of ‎the‏ ‎patent, ‎including‏ ‎its ‎technical ‎foundation, ‎implementation ‎strategies,‏ ‎and‏ ‎potential ‎impact‏ ‎on ‎cybersecurity‏ ‎practices. ‎By ‎dissecting ‎the ‎methodology,‏ ‎this‏ ‎document‏ ‎aims ‎to‏ ‎offer ‎a‏ ‎comprehensive ‎understanding‏ ‎of‏ ‎its ‎contributions‏ ‎to ‎enhancing ‎online ‎security.

This ‎analysis‏ ‎provides ‎a‏ ‎qualitative‏ ‎unpacking ‎of ‎US11496512B2,‏ ‎offering ‎insights‏ ‎into ‎its ‎innovative ‎approach‏ ‎to‏ ‎phishing ‎detection.‏ ‎The ‎document‏ ‎not ‎only ‎elucidates ‎the ‎technical‏ ‎underpinnings‏ ‎of ‎the‏ ‎patent ‎but‏ ‎also ‎explores ‎its ‎practical ‎applications,‏ ‎security‏ ‎benefits,‏ ‎and ‎potential‏ ‎challenges. ‎This‏ ‎examination ‎is‏ ‎important‏ ‎for ‎cybersecurity‏ ‎professionals, ‎IT ‎specialists, ‎and ‎stakeholders‏ ‎in ‎various‏ ‎industries‏ ‎seeking ‎to ‎understand‏ ‎and ‎implement‏ ‎advanced ‎phishing ‎detection ‎techniques.


Unpacking‏ ‎in‏ ‎more ‎detail


Читать: 3+ мин
logo Snarky Security

Patent US11483343B2

Ah, ‎behold‏ ‎the ‎marvel ‎that ‎is ‎US11483343B2,‏ ‎a ‎patent‏ ‎that‏ ‎boldly ‎claims ‎to‏ ‎revolutionize ‎the‏ ‎fight ‎against ‎the ‎digital‏ ‎age’s‏ ‎oldest ‎trick:‏ ‎phishing. ‎Because,‏ ‎of ‎course, ‎what ‎we’ve ‎all‏ ‎been‏ ‎missing ‎is‏ ‎yet ‎another‏ ‎«advanced» ‎system ‎promising ‎to ‎save‏ ‎us‏ ‎from‏ ‎the ‎nefarious‏ ‎links ‎lurking‏ ‎in ‎our‏ ‎inboxes.‏ ‎This ‎patent,‏ ‎with ‎its ‎grandiose ‎title ‎«Phishing‏ ‎Detection ‎System‏ ‎and‏ ‎Method ‎of ‎Use,‏ ‎» ‎introduces‏ ‎a ‎supposedly ‎novel ‎architecture‏ ‎designed‏ ‎to ‎sniff‏ ‎out ‎phishing‏ ‎attempts ‎by ‎scanning ‎messages ‎for‏ ‎suspicious‏ ‎URLs. ‎Groundbreaking,‏ ‎isn’t ‎it?

And‏ ‎so, ‎we ‎arrive ‎at ‎the‏ ‎pièce‏ ‎de‏ ‎résistance: ‎a‏ ‎multi-stage ‎phishing‏ ‎detection ‎system‏ ‎that‏ ‎not ‎only‏ ‎scans ‎messages ‎but ‎also ‎resolves‏ ‎URLs, ‎extracts‏ ‎webpage‏ ‎features, ‎and ‎employs‏ ‎machine ‎learning‏ ‎to ‎distinguish ‎friend ‎from‏ ‎foe.‏ ‎A ‎solution‏ ‎so ‎advanced,‏ ‎it ‎almost ‎makes ‎one ‎wonder‏ ‎how‏ ‎we ‎ever‏ ‎managed ‎to‏ ‎survive ‎the ‎internet ‎without ‎it.‏ ‎While‏ ‎it‏ ‎boldly ‎strides‏ ‎into ‎the‏ ‎battlefield ‎of‏ ‎cybersecurity,‏ ‎one ‎can’t‏ ‎help ‎but ‎ponder ‎the ‎performance‏ ‎and ‎accuracy‏ ‎challenges‏ ‎that ‎lie ‎ahead‏ ‎in ‎the‏ ‎ever-evolving ‎phishing ‎landscape.

-----

This ‎document‏ ‎provides‏ ‎a ‎comprehensive‏ ‎analysis ‎of‏ ‎the ‎patent ‎US11483343B2, ‎which ‎pertains‏ ‎to‏ ‎a ‎phishing‏ ‎detection ‎system‏ ‎and ‎method ‎of ‎use. ‎The‏ ‎analysis‏ ‎will‏ ‎delve ‎into‏ ‎various ‎aspects‏ ‎of ‎the‏ ‎patent,‏ ‎including ‎its‏ ‎technological ‎underpinnings, ‎the ‎novelty ‎of‏ ‎the ‎invention,‏ ‎its‏ ‎potential ‎applications. ‎A‏ ‎high-quality ‎summary‏ ‎of ‎the ‎document ‎is‏ ‎presented,‏ ‎highlighting ‎the‏ ‎key ‎elements‏ ‎that ‎contribute ‎to ‎its ‎significance‏ ‎in‏ ‎the ‎field‏ ‎of ‎cybersecurity.

The‏ ‎analysis ‎is ‎beneficial ‎for ‎security‏ ‎professionals,‏ ‎IT‏ ‎experts, ‎and‏ ‎stakeholders ‎in‏ ‎various ‎industries,‏ ‎providing‏ ‎them ‎with‏ ‎a ‎distilled ‎essence ‎of ‎the‏ ‎patent ‎and‏ ‎its‏ ‎utility ‎in ‎enhancing‏ ‎cybersecurity ‎measures.‏ ‎It ‎serves ‎as ‎a‏ ‎valuable‏ ‎resource ‎for‏ ‎understanding ‎the‏ ‎patented ‎technology’s ‎contribution ‎to ‎the‏ ‎ongoing‏ ‎efforts ‎to‏ ‎combat ‎phishing‏ ‎and ‎other ‎cyber ‎threats.


Unpacking ‎with‏ ‎more‏ ‎detail



Читать: 4+ мин
logo Snarky Security

Patent CN111913833A

Another ‎blockchain‏ ‎solution ‎to ‎solve ‎all ‎our‏ ‎healthcare ‎woes.‏ ‎Because,‏ ‎you ‎know, ‎what‏ ‎the ‎healthcare‏ ‎industry ‎has ‎been ‎desperately‏ ‎missing‏ ‎is ‎more‏ ‎buzzwords ‎like‏ ‎«dual-blockchain ‎architecture» ‎and ‎«attribute-based ‎encryption.»‏ ‎Who‏ ‎wouldn’t ‎sleep‏ ‎better ‎knowing‏ ‎their ‎sensitive ‎medical ‎data ‎is‏ ‎bouncing‏ ‎around‏ ‎on ‎not‏ ‎one, ‎but‏ ‎two ‎blockchains?‏ ‎It’s‏ ‎like ‎double‏ ‎the ‎security ‎blanket, ‎or ‎double‏ ‎the ‎headache,‏ ‎depending‏ ‎on ‎how ‎you‏ ‎look ‎at‏ ‎it. ‎Let’s ‎not ‎forget‏ ‎the‏ ‎pièce ‎de‏ ‎résistance: ‎AI‏ ‎integration. ‎Because ‎nothing ‎says ‎«trustworthy‏ ‎and‏ ‎secure» ‎like‏ ‎throwing ‎artificial‏ ‎intelligence ‎into ‎the ‎mix.

And ‎then‏ ‎there’s‏ ‎the‏ ‎real-time ‎monitoring‏ ‎feature, ‎because‏ ‎constant ‎surveillance‏ ‎is‏ ‎exactly ‎what‏ ‎we ‎all ‎need ‎for ‎peace‏ ‎of ‎mind.‏ ‎Nothing‏ ‎screams ‎«privacy» ‎like‏ ‎having ‎every‏ ‎heartbeat ‎and ‎blood ‎pressure‏ ‎reading‏ ‎recorded ‎on‏ ‎an ‎immutable‏ ‎ledger.

But ‎wait, ‎there’s ‎more! ‎The‏ ‎system‏ ‎promises ‎«decentralization,‏ ‎» ‎the‏ ‎magical ‎word ‎that ‎apparently ‎solves‏ ‎unauthorized‏ ‎data‏ ‎tampering. ‎Because‏ ‎as ‎we‏ ‎all ‎know,‏ ‎decentralization‏ ‎has ‎made‏ ‎cryptocurrencies ‎such ‎as ‎Bitcoin ‎completely‏ ‎immune ‎to‏ ‎fraud‏ ‎and ‎theft. ‎Oh,‏ ‎wait…

In ‎all‏ ‎seriousness, ‎the ‎patent ‎CN111913833A‏ ‎does‏ ‎aim ‎to‏ ‎tackle ‎genuine‏ ‎issues ‎in ‎the ‎healthcare ‎sector,‏ ‎such‏ ‎as ‎data‏ ‎breaches ‎and‏ ‎the ‎lack ‎of ‎standardized ‎protocols‏ ‎for‏ ‎secure‏ ‎data ‎exchange.‏ ‎However, ‎one‏ ‎can’t ‎help‏ ‎but‏ ‎approach ‎it‏ ‎with ‎a ‎healthy ‎dose ‎of‏ ‎skepticism. ‎After‏ ‎all,‏ ‎if ‎history ‎has‏ ‎taught ‎us‏ ‎anything, ‎it’s ‎that ‎technology‏ ‎is‏ ‎only ‎as‏ ‎good ‎as‏ ‎its ‎implementation ‎and ‎the ‎humans‏ ‎behind‏ ‎it. ‎So,‏ ‎here’s ‎to‏ ‎hoping ‎that ‎this ‎blockchain-based ‎transaction‏ ‎system‏ ‎for‏ ‎the ‎medical‏ ‎Internet ‎of‏ ‎Things ‎is‏ ‎more‏ ‎than ‎just‏ ‎another ‎buzzword ‎bingo ‎winner.

-----

This ‎document‏ ‎presents ‎a‏ ‎comprehensive‏ ‎analysis ‎of ‎the‏ ‎Medical ‎Internet‏ ‎of ‎Things ‎(IoMT) ‎transaction‏ ‎system‏ ‎based ‎on‏ ‎blockchain ‎technology,‏ ‎specifically ‎focusing ‎on ‎the ‎Chinese‏ ‎patent‏ ‎CN111913833A. ‎The‏ ‎analysis ‎delves‏ ‎into ‎various ‎aspects ‎of ‎the‏ ‎system,‏ ‎including‏ ‎its ‎architecture,‏ ‎security ‎features,‏ ‎the ‎enhancement‏ ‎of‏ ‎data ‎security‏ ‎and ‎privacy, ‎interoperability ‎among ‎different‏ ‎healthcare ‎systems,‏ ‎and‏ ‎the ‎facilitation ‎of‏ ‎secure ‎and‏ ‎transparent ‎transactions ‎and ‎potential‏ ‎applications‏ ‎within ‎the‏ ‎healthcare ‎sector.

A‏ ‎qualitative ‎summary ‎of ‎the ‎document‏ ‎is‏ ‎provided, ‎ensuring‏ ‎that ‎the‏ ‎essence ‎of ‎the ‎patent ‎is‏ ‎captured‏ ‎succinctly‏ ‎for ‎the‏ ‎benefit ‎of‏ ‎security ‎professionals‏ ‎and‏ ‎specialists ‎across‏ ‎various ‎industries. ‎The ‎analysis ‎is‏ ‎particularly ‎beneficial‏ ‎for‏ ‎cybersecurity ‎experts, ‎DevOps‏ ‎engineers, ‎healthcare‏ ‎IT ‎professionals, ‎medical ‎device‏ ‎manufacturers,‏ ‎and ‎forensic‏ ‎analysts ‎in‏ ‎understanding ‎the ‎implications ‎of ‎combining‏ ‎blockchain‏ ‎technology ‎with‏ ‎IoMT. ‎It‏ ‎offers ‎insights ‎into ‎how ‎this‏ ‎integration‏ ‎can‏ ‎address ‎common‏ ‎challenges ‎in‏ ‎the ‎healthcare‏ ‎industry,‏ ‎such ‎as‏ ‎data ‎breaches, ‎unauthorized ‎access, ‎and‏ ‎the ‎lack‏ ‎of‏ ‎a ‎standardized ‎protocol‏ ‎for ‎secure‏ ‎data ‎exchange.


Unpacking ‎in ‎more‏ ‎detail

Читать: 2+ мин
logo Snarky Security

Cyber Insurance Market

Cyber ‎Insurance‏ ‎Market ‎is ‎delightful ‎paradox ‎where‏ ‎businesses ‎shell‏ ‎out‏ ‎big ‎bucks ‎to‏ ‎protect ‎themselves‏ ‎from ‎the ‎very ‎technology‏ ‎they‏ ‎can’t ‎live‏ ‎without. ‎It’s‏ ‎like ‎buying ‎a ‎guard ‎dog‏ ‎that‏ ‎might ‎bite‏ ‎you ‎if‏ ‎you ‎forget ‎the ‎safe ‎word.

The‏ ‎market‏ ‎has‏ ‎grown ‎from‏ ‎a ‎niche‏ ‎product ‎to‏ ‎a‏ ‎multibillion-dollar ‎industry,‏ ‎proving ‎that ‎there’s ‎nothing ‎like‏ ‎a ‎global‏ ‎digital‏ ‎pandemic ‎to ‎open‏ ‎up ‎wallets.‏ ‎By ‎using ‎data ‎to‏ ‎drive‏ ‎policy ‎underwriting,‏ ‎cyber ‎insurance‏ ‎companies ‎can ‎now ‎offer ‎coverage‏ ‎without‏ ‎a ‎price‏ ‎tag ‎that‏ ‎drives ‎customers ‎away?

In ‎2024, ‎after‏ ‎years‏ ‎of‏ ‎rising ‎premiums‏ ‎and ‎capacity‏ ‎constriction, ‎the‏ ‎cyber‏ ‎insurance ‎market‏ ‎decided ‎to ‎surprise ‎everyone ‎by‏ ‎softening ‎conditions.‏ ‎But‏ ‎don’t ‎get ‎too‏ ‎excited, ‎there’s‏ ‎still ‎an ‎underlying ‎concern‏ ‎about‏ ‎systemic ‎cyber‏ ‎risk ‎not‏ ‎covered ‎by ‎premiums.


Unpacking ‎in ‎more‏ ‎detail


Показать еще

Обновления проекта

Метки

overkillsecurity 142 overkillsecuritypdf 52 news 47 keypoints 38 nsa 26 fbi 25 adapt tactics 11 Living Off the Land 11 LOTL 11 unpacking 10 vulnerability 9 cyber security 8 Digest 8 edge routers 8 Essential Eight Maturity Model 8 malware 8 Maturity Model 8 Monthly Digest 8 research 8 ubiquiti 8 IoT 7 lolbin 7 lolbins 7 Cyber Attacks 6 phishing 6 Forensics 5 Ransomware 5 soho 5 authToken 4 BYOD 4 MDM 4 OAuth 4 Energy Consumption 3 IoMT 3 medical 3 ai 2 AnonSudan 2 authentication 2 av 2 battery 2 Buffer Overflow 2 console architecture 2 cve 2 cybersecurity 2 energy 2 Google 2 incident response 2 MITM 2 mqtt 2 Passkeys 2 Retro 2 Velociraptor 2 video 2 Vintage 2 vmware 2 windows 2 1981 1 5g network research 1 8-bit 1 Ad Removal 1 Ad-Free Experience 1 ADCS 1 advisory 1 airwatch 1 AlphV 1 AMSI 1 android 1 Android15 1 announcement 1 antiPhishing 1 AntiPhishStack 1 antivirus 1 Apple 1 Atlassian 1 Attack 1 AttackGen 1 BatBadBut 1 Behavioral Analytics 1 BianLian 1 bias 1 Biocybersecurity 1 Biometric 1 bite 1 bitlocker 1 bitlocker bypass 1 Black Lotus Labs 1 blackberry 1 blizzard 1 botnet 1 Browser Data Theft 1 BucketLoot 1 CellularSecurity 1 checkpoint 1 china 1 chisel 1 cisa 1 CloudSecurity 1 CloudStorage 1 content 1 content category 1 cpu 1 Credential Dumping 1 CVE-2023-22518 1 CVE-2023-35080 1 CVE-2023-38043 1 CVE-2023-38543 1 CVE-2024-0204 1 CVE-2024-21111 1 CVE-2024-21345 1 cve-2024-21447 1 CVE-2024-24919 1 CVE-2024-26218 1 cve-2024-27129 1 cve-2024-27130 1 cve-2024-27131 1 cve-2024-3400 1 cvss 1 cyber operations 1 Cyber Toufan Al-Aqsa 1 cyberops 1 D-Link 1 dark pink apt 1 data leakage 1 dcrat 1 Demoscene 1 DevSecOps 1 Dex 1 disassembler 1 DOS 1 e8mm 1 EDR 1 Embedded systems 1 Employee Training 1 EntraID 1 ESC8 1 Event ID 4663 1 Event ID 4688 1 Event ID 5145 1 Evilginx 1 EvilLsassTwin 1 Facebook 1 FBI IC3 1 FIDO2 1 filewave 1 Firebase 1 Firmware 1 Fortra's GoAnywhere MFT 1 france 1 FraudDetection 1 fuxnet 1 fuzzer 1 game console 1 gamification 1 GeminiNanoAI 1 genzai 1 go 1 GoogleIO2024 1 GooglePlayProtect 1 GoPhish 1 gpu 1 ICS 1 ICSpector 1 IDA 1 IncidentResponse 1 Industrial Control Systems 1 jazzer 1 jetbrains 1 jvm 1 KASLR 1 KillNet 1 LeftOverLocals 1 Leviathan 1 lg smart tv 1 lockbit 1 LSASS 1 m-trends 1 Machine Learning Integration 1 Mallox 1 MalPurifier 1 mandiant 1 MediHunt 1 Meta Pixel 1 ML 1 mobile network analysis 1 mobileiron 1 nes 1 nexus 1 NGO 1 Nim 1 Nimfilt 1 NtQueryInformationThread 1 OFGB 1 oracle 1 paid content 1 panos 1 Passwordless 1 Phishing Resilience 1 PingFederate 1 Platform Lock-in Tool 1 PlayIntegrityAPI 1 PlayStation 1 playstation 2 1 playstation 3 1 plc 1 podcast 1 Privilege Escalation 1 ps2 1 ps3 1 PulseVPN 1 qcsuper 1 qemu 1 qualcomm diag protocol 1 radio frame capture 1 Raytracing 1 Real-time Attack Detection 1 Red Team 1 Registry Modification 1 Risk Mitigation 1 RiskManagement 1 rodrigo copetti 1 rooted android devices 1 Router 1 rust 1 Sagemcom 1 sandworm 1 ScamCallDetection 1 security 1 Security Awareness 1 session hijacking 1 SharpADWS 1 SharpTerminator 1 shellcode 1 SIEM 1 Siemens 1 skimming 1 Smart Devices 1 snes 1 SSO 1 stack overflow 1 TA427 1 TA547 1 TDDP 1 telecom security 1 Telegram 1 telerik 1 TeleTracker 1 TEMP.Periscope 1 Terminator 1 Think Tanks 1 Threat 1 threat intelligence 1 threat intelligence analysis 1 Threat Simulation 1 tool 1 toolkit 1 tp-link 1 UK 1 UserManagerEoP 1 uta0218 1 virtualbox 1 VPN 1 vu 1 wargame 1 Web Authentication 1 WebAuthn 1 webos 1 What2Log 1 Windows 11 1 Windows Kernel 1 Windstream 1 women 1 WSUS 1 wt-2024-0004 1 wt-2024-0005 1 wt-2024-0006 1 xbox 1 xbox 360 1 xbox original 1 xss 1 Yubico 1 Z80A 1 ZX Spectrum 1 Больше тегов

Фильтры

Подарить подписку

Будет создан код, который позволит адресату получить бесплатный для него доступ на определённый уровень подписки.

Оплата за этого пользователя будет списываться с вашей карты вплоть до отмены подписки. Код может быть показан на экране или отправлен по почте вместе с инструкцией.

Будет создан код, который позволит адресату получить сумму на баланс.

Разово будет списана указанная сумма и зачислена на баланс пользователя, воспользовавшегося данным промокодом.

Добавить карту
0/2048