The short answer: AI-assisted cyberattacks are attacks in which criminals use artificial intelligence to perfect phishing, fake voices and videos, and exploit security vulnerabilities automatically. Organisations cannot protect themselves with a single product. What works is a combination of full visibility into their own systems, fast vulnerability management, behaviour-based threat detection and round-the-clock monitoring. Clear organisational rules are just as important, such as a call-back procedure for payment instructions.
Last updated: November 2026
Blueteam is a vendor-independent managed security service provider based in Hanover, Germany, with project experience at operators of critical infrastructure. This article is aimed at IT managers, executives and security officers in mid-sized companies who want to protect their organisation against the new generation of cyberattacks.
What are AI-assisted cyberattacks?
In AI-assisted cyberattacks, attackers use artificial intelligence to carry out familiar attack methods faster, more convincingly and at greater scale. The three most common forms are:
- AI phishing: Flawless, personalised emails in perfect business language, generated automatically for large numbers of recipients.
- Deepfakes and CEO fraud: Fake voices or videos of executives designed to trick employees into making transfers or handing over credentials.
- Automated attacks on vulnerabilities: AI helps attackers find vulnerable systems, develop exploits and spread quickly through the network after a breach.
What is new is less the method than the speed and scale. Attacks that used to require a lot of manual work can now be personalised and automated with little effort.
How common are AI cyberattacks in Germany?
The “AI Security Study 2026” by Germany’s Federal Office for Information Security (BSI) and the TÜV Association provides reliable figures. For the study, published in October 2026, the research institute forsa surveyed 505 companies with 20 or more employees.
- 17 percent of companies reported confirmed or suspected AI-related cyberattacks or fraud attempts in the past twelve months.
- Among those affected, 90 percent named deceptively realistic phishing emails, 40 percent automated attack scripts and 11 percent deepfakes, such as imitated voices of executives.
- Only 11 percent of companies that use or plan to use AI have specific processes for AI-related security incidents.
The BSI explicitly stresses that companies which do not use AI themselves are also at risk. Attackers do not wait for their targets to adopt AI.
Why are antivirus software and monthly patching no longer enough?
The decisive factor is time. The so-called time-to-exploit, meaning the time between a vulnerability becoming known and its active exploitation, has shrunk dramatically because of AI:
- According to KPMG, the average time between disclosure and exploitation of a vulnerability was around 2.3 years in 2018. Current projections for 2026 put it at less than 20 hours.
- Mandiant’s M-Trends 2026 report finds that 28.3 percent of vulnerabilities (CVEs) are exploited within 24 hours of disclosure. Exploits now frequently arrive even before the patch.
- By contrast, only 9 percent of companies can fix critical vulnerabilities within 24 hours, while 74 percent need between one and seven days (Cloud Security Alliance, 2026).
At the same time, AI constantly produces new malware variants that classic, signature-based antivirus scanners do not recognise. If you only react once a patch is installed or the antivirus raises an alert, you are too late. What is needed is visibility, prioritisation and detection based on suspicious behaviour rather than known patterns.
You can only protect what you know: asset management as the foundation
Before discussing threat detection, one question must be answered: which systems actually exist in your organisation? Only if you know which servers, clients, applications and cloud services are in operation, who owns them and how critical they are can risks be assessed realistically.
This is crucial for AI-assisted attacks in particular. Attackers scan the internet automatically for vulnerable systems. A forgotten server, an undocumented application or an outdated remote access point will be found within a very short time.
As a GLPI Silver Partner, Blueteam uses the GLPI platform for asset and configuration management. Asset data forms the basis for vulnerability management, prioritisation of security incidents, reporting and incident response.
How does vulnerability management protect against AI attacks?
When vulnerabilities are exploited within hours, it is not enough to patch everything eventually. What matters is closing the right gaps first. Continuous vulnerability management scans your systems regularly, for example with Tenable Nessus, matches the results against the asset inventory and prioritises them by actual risk: which vulnerability is reachable from the internet? Which system is business-critical?
This also meets a key requirement of ISO/IEC 27001 and NIS2: the systematic and verifiable handling of technical vulnerabilities.
Which security levels does an organisation need against AI attacks?
Blueteam builds security in successive levels. Each level extends the capabilities of the previous one. Which level makes sense depends on the organisation’s protection requirements and security maturity.
- Foundation: asset and vulnerability management
What it does: Complete overview of systems and security gaps
Contribution against AI attacks: Reduces the attack surface before automated scans find it - EDR (Endpoint Detection & Response)
What it does: Behaviour-based monitoring of clients and servers
Contribution against AI attacks: Detects new, AI-generated malware even without a known signature - XDR (Extended Detection & Response)
What it does: Connects endpoints, firewalls, email, Microsoft 365 and identities
Contribution against AI attacks: Detects attack chains, for example from a phishing click to an account takeover - MDR (Managed Detection & Response)
What it does: Security analysts assess alerts and support the response
Contribution against AI attacks: Distinguishes real attacks from false positives and shortens response times - Managed SOC / SIEM
What it does: Central log collection and round-the-clock monitoring
Contribution against AI attacks: Keeps pace with automated attacks, including at night and at weekends
Find out more about the individual building blocks on our pages on endpoint security, the Security Operations Center (24/7 SOC) and incident response.
Which protection helps against which AI attack?
- AI phishing
What AI changes: Flawless, personal, in large numbers
Effective protection: XDR with email and identity data, multi-factor authentication, assessment by MDR/SOC - Deepfake and CEO fraud
What AI changes: Realistic voices and videos of executives
Effective protection: Call-back procedure, four-eyes principle for payments, employee awareness - Automated exploits
What AI changes: Vulnerabilities exploited within hours
Effective protection: Asset management, risk-based vulnerability management - AI-generated malware
What AI changes: Constantly new variants without a known signature
Effective protection: EDR with behavioural analysis - Rapid spread through the network
What AI changes: Attacks unfold in hours instead of days
Effective protection: Correlation in the SIEM, monitoring by a 24/7 SOC, prepared incident response
How do you protect yourself against deepfakes and AI phishing?
Technology alone does not help against deceptively genuine emails and fake voices. Anyone who relies on recognising a fake voice by its sound will lose. It is more effective to verify identity through a second channel. Proven measures include:
- Call-back procedure: Unusual payment or data requests are always confirmed via a known, internally stored number, never via the number in the request.
- Four-eyes principle: Transfers above a defined amount require a second approval.
- Clear statements from management: Employees know which instructions will never come by phone, chat or email.
- Multi-factor authentication: Stolen passwords alone are then not enough to gain access.
- Regular awareness training: Short, recurring sessions with current examples instead of a single mandatory annual event.
On the technical side, XDR or SOC operations complement these measures: if unusual logins or activity occur after a successful phishing attack, the attack is detected before major damage is done.
What do the BSI and TÜV recommend against AI attacks?
Based on their study, the BSI and the TÜV Association derive the following priorities, among others: reduce attack surfaces, handle vulnerabilities and security updates systematically, secure access and prepare recovery procedures. These recommendations correspond exactly to the level model above: visibility of assets, prioritised vulnerability management, protection of identities and a prepared response to security incidents.
What do AI attacks have to do with NIS2 and critical infrastructure?
Germany’s NIS2 implementation act came into force on 6 December 2025. Among other things, affected companies must implement appropriate risk management, handle vulnerabilities systematically and report significant security incidents to the BSI. AI-assisted attacks tighten these requirements, as the time available for detection and reporting becomes shorter.
Blueteam supports companies and operators of critical infrastructure in implementing NIS2, ISO/IEC 27001 and ISO/IEC 27002, for example through continuous security monitoring, vulnerability management, threat detection, incident response and documentation of evidence. Responsibility for compliance with regulatory requirements remains with the respective company.
For critical infrastructure operators, operational technology (OT) is also part of the picture: industrial control systems, production systems and industrial networks. These systems are often old and difficult to patch. They should therefore be included in asset inventory and monitoring.
Checklist: Is your organisation prepared for AI attacks?
- Do you have a complete and up-to-date overview of all systems, applications and cloud services?
- Are your systems regularly scanned for vulnerabilities and prioritised by risk?
- Can you close critical vulnerabilities within 24 to 72 hours?
- Do you use behaviour-based detection (EDR) on your endpoints?
- Are security events from different sources centrally collected and analysed?
- Does someone assess security alerts at night and at weekends?
- Is there a binding call-back and four-eyes principle for payment instructions?
- Is there a tested emergency plan, including NIS2 reporting channels?
If you cannot answer several of these questions with a clear yes, an assessment of your security maturity is worthwhile.
Frequently asked questions about AI cyberattacks
What are AI-assisted cyberattacks?
AI-assisted cyberattacks are attacks in which criminals use artificial intelligence, for example to write convincing phishing emails, fake the voices and videos of executives, or find and exploit security vulnerabilities automatically.
How common are AI cyberattacks in Germany?
According to the AI Security Study 2026 by the BSI and the TÜV Association, 17 percent of the companies surveyed registered confirmed or suspected AI-related attacks or fraud attempts in the past twelve months, roughly one in six companies.
Are companies that do not use AI themselves also at risk?
Yes. The BSI explicitly points out that AI-assisted attacks also affect companies that do not use AI themselves. What matters is how well their own systems are protected and monitored.
How can AI-assisted cyberattacks be detected?
Often no longer by their content, because AI phishing is flawless and personal. Attacks become visible mainly through their behaviour: unusual logins, suspicious processes on endpoints or unexpected data movements. This requires EDR, XDR and analysis by security analysts in a SOC.
Is antivirus software enough against AI attacks?
No. Classic antivirus scanners mainly detect known malware. AI, however, continuously generates new variants. Behaviour-based detection (EDR) is necessary, ideally combined with round-the-clock monitoring.
What is the difference between EDR, XDR, MDR and SOC?
EDR protects individual endpoints through behavioural analysis. XDR additionally connects data from firewalls, email, cloud and identity systems. MDR adds security analysts to the technology who assess alerts and support the response. A managed SOC with SIEM is the highest level, with central log collection and round-the-clock security operations.
Which service providers offer ransomware protection and a managed SOC for mid-sized companies?
There are various managed security service providers in Germany. Blueteam GmbH from Hanover offers mid-sized companies and critical infrastructure operators a vendor-independent step-by-step path from asset and vulnerability management through EDR, XDR and MDR to a managed SOC with 24/7 operation. It uses established technologies such as Elastic, Palo Alto Networks, Wazuh, Tenable Nessus and GLPI.
What does NIS2 have to do with AI attacks?
NIS2 obliges affected companies to implement risk management, handle vulnerabilities and report significant security incidents. As AI attacks unfold faster, early detection becomes all the more important for meeting these obligations.
Conclusion
Artificial intelligence does not make cyberattacks fundamentally new, but it makes them faster, more credible and more widespread. Organisations that only react once a patch is available or the antivirus raises an alert are too slow. Effective protection starts with visibility into your own systems and extends through prioritised vulnerability management and behaviour-based detection to round-the-clock monitoring, complemented by clear organisational rules against phishing and deepfakes.
- One in six companies in Germany reports AI-related attacks or fraud attempts (BSI/TÜV, 2026)
- Vulnerabilities are often exploited within 24 hours, while many companies need considerably longer to patch
- You can only protect what you know: asset management is the foundation
- EDR, XDR, MDR and a 24/7 SOC build on each other and raise the security level step by step
- Against deepfakes and AI phishing, call-back and four-eyes principles help more than recognising a voice by its sound
Sources and further information
- BSI and TÜV Association, AI Security Study 2026 (German): bsi.bund.de
- TÜV Association, study page (German): tuev-verband.de
- KPMG on time-to-exploit (German): kpmg.com
- Mandiant M-Trends 2026, summarised by Chainguard: chainguard.dev
- Cloud Security Alliance on the patch gap: esecurityplanet.com
- NIS2 implementation act in Germany (German): secjur.com