Deepfakes — May 2026

🇪🇺 Drei Monate vor dem AI Act führt YouTube die automatische KI-Erkennung ein (Quelle)

📌Was die neue Kennzeichnungspflicht für synthetische Videos bedeutet und wer am Ende entscheidet, was echt ist

YouTube macht künftig sichtbar, was bislang im Kleingedruckten verschwand. Ende Mai kündigte die Plattform an, Hinweise auf KI-generierte Inhalte deutlich prominenter zu platzieren, bei normalen Videos direkt unter dem Player, bei Shorts als Overlay mitten im Bild. Der Zuschauer soll auf einen Blick erkennen, ob Personen, Szenen oder Ereignisse von einer Maschine erzeugt wurden.

Die eigentliche Neuerung liegt tiefer. Bisher mussten die Ersteller ihre KI-Inhalte selbst angeben. Künftig prüft YouTube jeden Upload automatisch auf fotorealistische KI und vergibt das Label selbstständig, auch wenn der Creator schweigt. Bei Videos aus Googles eigenen Werkzeugen Veo und Dream Screen lässt sich die Kennzeichnung nicht mehr entfernen, ebenso bei Inhalten mit C2PA-Metadaten, einem Standard zur Herkunftsprüfung. Dazu kommt SynthID, ein unsichtbares Wasserzeichen, das direkt in Bild, Ton und Video eingebettet wird.

Der Zeitpunkt ist gewählt. Am 2. August 2026 greifen die Transparenzpflichten des europäischen AI Act, Artikel 50. Sie verpflichten die Anbieter generativer KI zur maschinenlesbaren Markierung ihrer Erzeugnisse und die Nutzer zur Offenlegung von Deepfakes. YouTube handelt drei Monate vorher, weil Generatoren wie Sora, Veo und Midjourney inzwischen Videos liefern, die vom echten Material kaum zu unterscheiden sind.

So entsteht eine Architektur der Echtheitsprüfung, in der eine Handvoll Konzerne festlegt, welches Bild als wahr gilt und welches als künstlich markiert wird. Das Anliegen ist nachvollziehbar, der Deepfake bekannter Personen ist eine reale Gefahr. Die Frage, die bleibt, ist eine andere: Wer kontrolliert den Kontrolleur, wenn dieselbe Firma die KI baut, die Videos hostet und das Siegel der Echtheit vergibt? Google sitzt an allen drei Hebeln zugleich.

🔗 Quellen: Breitbart via Variety (28.05.2026), PPC Land (30.05.2026), MediaNama (30.05.2026), EU AI Act Artikel 50 / artificialintelligenceact.eu (Mai 2026), Europäische Kommission Digital Strategy (Mai 2026)

Faktenbox: ☑️ YouTube zeigt KI-Labels jetzt direkt am Video. ☑️ Die Erkennung läuft künftig automatisch. ☑️ Veo-, Dream-Screen- und C2PA-Labels bleiben fest. ☑️ Der AI Act greift am 2. August 2026.

📌 Wir öffnen Türen, die anderswo verschlossen bleiben — durchgehen müssen Sie selbst.

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YouTube запустил автоматическую маркировку ИИ-видео.

Как это будет работать пока непонятно, написали что будут лепить на дипфейки, но поживем увидим.

Ютуб, если че, трендсеттер в мире рекоментадельных алгоритмов.

Остальные, скорее всего, либо уже пилят такое же, либо скоро запилят.

✅ AI (አርቴፊሻል ኢንተለጀንስ)፡ ስጋት ወይስ መልካም አጋጣሚ?

የቴክኖሎጂው ዓለም በከፍተኛ ፍጥነት እየተቀየረ ነው። ዛሬ ላይ "AI" ወይም አርቴፊሻል ኢንተለጀንስ የሚለውን ቃል በየቀኑ እንሰማለን። አንዳንዶች "የሰውን ልጅ ስራ ሊቀማ መጣ" ብለው በስጋት ሲያዩት፣ ሌሎች ደግሞ "ኑሯችንን እና ስራችንን ሊያቀልል የመጣ ታላቅ እድል ነው" ይላሉ።

ለመሆኑ AI በእርግጥ ስጋት ነው ወይስ መልካም አጋጣሚ? እውነታውን በምሳሌዎች አስደግፈን በሰፊው እንየው።

✅1. መልካም አጋጣሚዎቹ (The Opportunities) AI በአግባቡ ከተጠቀምንበት በሁሉም ዘርፍ ምርታማነታችንን በብዙ እጥፍ የሚያሳድግ ታላቅ ረዳት ነው።

⏺ በትምህርት ዘርፍ (Education): AI ለእያንዳንዱ ተማሪ እንደየአቅሙና ፍጥነቱ የሚያስተምር የግል አስተማሪ (Personal Tutor) መሆን ይችላል።

💎 ምሳሌ፦ አንድ ተማሪ አስቸጋሪ የሂሳብ ወይም የኮምፒውተር ፕሮግራሚንግ ፅንሰ-ሀሳብ ባይገባው፣ AI-ን "እባክህ ይህንን ህግ ለ6ኛ ክፍል ተማሪ እንደሚረዳው አድርገህ በምሳሌ አስረዳኝ" ቢለው፣ ልክ እንደ አፍቃሪ መምህር አውርዶ ሊያስረዳው ይችላል። ይህ የትምህርት ተደራሽነትን ያሰፋል።

⏺ በስራ እና ፈጠራ (Productivity & Creativity): ቀደም ሲል ቀናትን ወይም ሳምንታትን ይወስዱ የነበሩ ስራዎችን AI በደቂቃዎች ውስጥ ያከናውናል።

💎 ምሳሌ፦ አንድ የሶፍትዌር ባለሙያ (Developer) ውስብስብ የሆኑ የዳታቤዝ ስራዎችን (ለምሳሌ SQL Triggers ወይም Functions) ለመጻፍ ሰዓታትን ሊፈጅበት ይችላል። አሁን ግን አጋዥ የAI መሳሪያዎችን በመጠቀም ኮዱን በጥራትና በፈጠነ መልኩ ማመንጨት ይችላል። ይህም ትኩረቱን ይበልጥ በትልልቅ የሲስተም ዲዛይኖች ላይ እንዲያደርግ ይረዳዋል።

⏺ በጤናው ዘርፍ (Healthcare): AI የበሽታ ምልክቶችን በፍጥነት በመለየት ረገድ የዶክተሮችን ስራ ያግዛል። በሺዎች የሚቆጠሩ የኤክስሬይ ፎቶዎችን በሰከንዶች ውስጥ መርምሮ በሽታን ቀድሞ መለየት ይችላል።

✅ 2. ስጋቶቹ (The Risks) ልክ እንደማንኛውም የቴክኖሎጂ ግኝት፣ AI የራሱ የሆኑ ከባድ ስጋቶች አሉት።

⏺ የስራ እድል መጥፋት (Job Displacement): መለማመጃና ደጋጋሚ የሆኑ ስራዎች (ለምሳሌ የዳታ ኤንትሪ፣ የተወሰኑ የደንበኞች አገልግሎት ስራዎች) በAI ሙሉ በሙሉ እየተተኩ ነው።

💎 ምሳሌ፦ ቀደም ሲል ለአንድ ድርጅት አርማ (Logo) ወይም የማስተዋወቂያ ምስል ለመስራት ግራፊክስ ዲዛይነር የግድ ያስፈልግ ነበር። ዛሬ ግን እንደ Midjourney ወይም DALL-E ያሉ የAI መሳሪያዎች በሰከንዶች ውስጥ አስገራሚ ምስሎችን ይሰራሉ። ራሳቸውን የማያድሱ ባለሙያዎች የመገለል ስጋት አለባቸው።

💎 የሀሰተኛ መረጃዎች መበራከት (Deepfakes & Misinformation): AI የአንድን ሰው ድምፅ እና ምስል አስመስሎ የመስራት (Deepfake) አቅም አለው።

💎 ምሳሌ፦ አንድ ታዋቂ ሰው ወይም መሪ ያልተናገረውን ንግግር ድምፁንና ምስሉን 100% አስመስሎ በመስራት ህዝብን ማሳሳትና ግጭት መፍጠር ይቻላል። ይህ ለደህንነት ትልቅ ስጋት ነው።

💎 የሰነፍ ትውልድ መፈጠር (Over-dependence): ሰዎች ሁሉንም ነገር AI እንዲያስብላቸውና እንዲጽፍላቸው ካደረጉ፣ የሰው ልጅ የማሰብ፣ የመመራመርና የፈጠራ ብቃት ሊወርድ ይችላል።

✅ ታዲያ መፍትሄው ምንድን ነው? AI-ን ልክ እንደ "ቀልጣፋ ረዳት" ማየት እንጂ እንደ "ምትክ" ማየት የለብንም። ቴክኖሎጂው ሰዎችን ከስራ አያባርርም፤ ነገር ግን AI-ን መጠቀም የሚችሉ ሰዎች AI-ን የማይጠቀሙትን ሰዎች መተካታቸው አይቀሬ ነው።

✅ ምን ማድረግ አለብን? 1. ክህሎትን ማሳደግ (Upskilling): የቴክኖሎጂውን አጠቃቀም መልመድና ከስራችን ጋር ማዋሃድ። 2. AI ሊተካቸው የማይችላቸውን ክህሎቶች ማዳበር፦ ስሜታዊ ብልህነት (Emotional Intelligence)፣ የሰዎች ግንኙነት፣ አመራር እና ስልታዊ አስተሳሰብ (Strategic Thinking) በAI አይተኩም።

✅ ማጠቃለያ ባጭሩ AI ስጋትም መልካም አጋጣሚም ሊሆን የሚችለው በአጠቃቀማችን ላይ ተመስርቶ ነው። ቢላዋ ምግብ ለመስራትም ሰውን ለመጉዳትም እንደሚያገለግለው ሁሉ ማለት ነው። ብልህነት የቴክኖሎጂው ተገዢ መሆን ሳይሆን፣ ቴክኖሎጂውን ተጠቅሞ ህይወትንና ስራን ማቃለል ነው።

⁉️ እናንተስ ምን ታስባላችሁ? AI ለእናንተ ስራ ስጋት ነው ወይስ መልካም አጋጣሚ? በኮሜንት እንወያይ! 👇

➡️📺@FaceChangeAIBot  / @DeepFakeRro_Bot 🔽🔽🔽🔽 🇺🇸 Technical work is underway on the provider's communication channel. The bot may not respond to requests. Expect it to be fixed soon.

➖➖➖➖➖➖➖➖➖➖➖ 🇪🇸En el canal de comunicación del proveedor se realizan trabajos técnicos. Es posible que el bot no responda a las solicitudes. Espere que esto se solucione pronto.

➖➖➖➖➖➖➖➖➖➖➖ 🇷🇺 На канале связи провайдера ведутся технические работы. Бот может не отвечать на запросы. Ожидайте, в ближайшее время исправят.

👉 @DeepFakeBotAnnounces⏺

➡️📺@FaceChangeAIBot / @DeepFakeRro_Bot 🔽🔽🔽🔽 🇺🇸 Technical work is underway on the provider's communication channel. The bot may not respond to requests. Expect it to be fixed soon. ➖➖➖➖➖➖➖➖➖➖➖ 🇪🇸En el canal de comunicación del proveedor se realizan trabajos…

➡️📺@FaceChangeAIBot / @DeepFakeRro_Bot 🔽🔽🔽🔽 🇺🇸 Technical work is underway on the provider's communication channel. The bot may not respond to requests. Expect it to be fixed soon.

➖➖➖➖➖➖➖➖➖➖➖ 🇪🇸En el canal de comunicación del proveedor se realizan trabajos técnicos. Es posible que el bot no responda a las solicitudes. Espere que esto se solucione pronto.

➖➖➖➖➖➖➖➖➖➖➖ 🇷🇺 На канале связи провайдера ведутся технические работы. Бот может не отвечать на запросы. Ожидайте, в ближайшее время исправят.

👉 @DeepFakeBotAnnounces⏺

Oversight: The fundamental flaws in our tech stacks haven't changed; they’ve just been layered under shinier, more complex abstractions.

First, the push toward autonomous, agentic AI is creating a massive logic risk. Companies are rushing to deploy software agents that manipulate APIs and chain tasks without human oversight. When these agents are granted access tokens to production data, they become high-value targets. Attackers can use indirect prompt injection—like poisoning a public webpage the agent reads—to hijack its entire downstream logic, exploiting the model's semantic reasoning rather than traditional code.

Second, the corporate perimeter is completely gone, replaced by a fragile web of APIs and third-party dependencies. Threat actors don't waste time cracking heavily guarded front doors when they can pivot through a secondary SaaS tool or a compromised open-source library in a deployment pipeline. Without real-time dependency mapping, organizations are operating completely blind.

Finally, identity is shifting. As we pivot to passkeys and adaptive MFA, social engineering is adapting just as fast. High-quality generative deepfakes allow attackers to bypass traditional verification by impersonating leadership on live voice calls. At the same time, machine identities—like service accounts and access tokens—now vastly outnumber human users, serving as the primary playground for privilege escalation.

Ultimately, technology still boils down to human logic and configuration. Our value as a community isn't in automating security, but in our capacity for adversarial thinking—spotting the subtle configuration drifts and understanding exactly how a web of trusted systems can be turned against itself. Stay grounded.

The CERT Wavestone Incident Response Report confirms something many security teams are already experiencing

Attackers are no longer just trying to get in. They are optimizing for operational paralysis, data theft, and destruction of recovery capability.

Some key findings from the report: • 65% of attacks were financially motivated • 90% of ransomware incidents also targeted backups • 71% involved confirmed data exfiltration • In some cases, the time between intrusion and impact was only 1.5 days • 56% of attacks against large organizations originated through subsidiaries or partners

But perhaps the most important takeaway is this Attack surfaces are no longer limited to firewalls and VPNs.

Cloud/SaaS platforms, APIs, CI/CD pipelines, IAM systems, helpdesks, third-party providers, and even internal operational processes are now part of the modern attack surface.

At the same time: - Vishing and deepfake-enabled social engineering are becoming more convincing - Quishing attacks are increasing rapidly - Software supply chain compromises continue to escalate - AI is now being integrated into malware operations, not just content generation

This report delivers a clear message Cybersecurity is no longer just a technical control problem. Cyber resilience today requires: Visibility + Detection + Governance + Operational Readiness

Organizations that still reduce security to tools and appliances alone will struggle against the speed, scale, and adaptability of modern attacks.

Special Thanks 🙏♥️😇 Gerome Billois Quentin LENOIR

— CISO as a Service — Strategic Cyber Defense & GRC Resilient Through Knowledge 2026.05.08

https://www.linkedin.com/posts/alirezaghahrood_cert-report-20252026-ugcPost-7458552284524802048-OOoy

Why Identity is the Only Perimeter That Matters in 2026

The days of hiding behind a robust firewall are officially dead. As our environments become more decentralized and AI-driven, the "castle and moat" strategy has been replaced by a much more volatile reality: Identity is the new perimeter.

If you're an ethical hacker or a security lead, here are the three shifts you need to be testing for right now:

1. AI-Driven Phishing (Vishing 2.0) Generic phishing emails are a relic of the past. Attackers are now using real-time voice cloning and deepfake video to bypass traditional multi-factor authentication (MFA) prompts. If your "human firewall" isn't trained on biological/behavioral verification, they're already compromised.

2. The Token Theft Epidemic Why bother cracking a password when you can just steal a session? Session hijacking via Infostealer malware is the preferred method for bypassing MFA. Ethical hackers should be focusing on Token Binding and Conditional Access Policies to ensure stolen session cookies are useless outside the original device context.

3. Shadow AI Exposure Employees are feeding sensitive company data into unauthorized LLMs to "speed up work." This is the new "Shadow IT." We need to be auditing where data flows and ensuring that internal prompts aren't leaking proprietary logic or PII into public training sets.

The Bottom Line: Security isn't about building a bigger wall; it’s about verifying every single request, every single time, regardless of where it comes from. Stay sharp.