TL;DR: Cybercriminals use AI to research targets, personalize phishing attempts, create deepfakes, develop malware, crack passwords, and evade detection. Organizations need stronger identity controls, continuous monitoring, employee training, automated security hygiene, and human oversight to manage these rapidly evolving threats.

Artificial intelligence is changing cybersecurity for defenders and attackers alike. Cybercriminals are turning to AI because it makes many parts of an attack faster, cheaper, and easier to scale. Tasks that once required strong language skills, coding expertise, or hours of research can now be completed in minutes.

AI does not necessarily create entirely new forms of cybercrime. Instead, it improves familiar tactics such as phishing, malware, impersonation, and credential theft. It also lowers the technical barrier for less-skilled criminals while helping experienced groups run more sophisticated campaigns.

According to the FBI, cybercriminals increasingly use AI-generated text, images, videos, and voice recordings to commit fraud and impersonate trusted individuals. This makes suspicious communication much harder for ordinary users to recognize.

What Are AI-Powered Cyberattacks?

AI-powered cyberattacks are attacks in which criminals use artificial intelligence or machine learning to automate, accelerate, or improve malicious activities.

For example, an attacker may use an AI tool to collect information about a company, identify employees with valuable access, write personalized emails, generate malicious code, and alter that code to avoid detection. AI can support one stage of an attack or remain involved throughout the campaign.

Unlike completely manual attacks, AI-enabled campaigns can process large volumes of data, create thousands of customized messages, and adapt quickly. CrowdStrike explains that AI can assist with everything from identifying vulnerabilities and establishing backdoors to stealing data and disrupting operations.

However, AI is usually an accelerator rather than an independent attacker. Human criminals still choose targets, set objectives, operate infrastructure, and decide how stolen information will be used.

Learn 18+ in-demand cybersecurity skills, including ethical hacking, system penetration testing, AI-powered threat detection, network packet analysis, and much more with Cyber Security Experts Masters Program.

How Attackers Use AI Across the Cyberattack Lifecycle?

AI can support criminals at almost every point in the cyberattack lifecycle:

  • Reconnaissance: AI gathers data from company websites, social media, job listings, leaked databases, and technical sources.
  • Target selection: Algorithms help identify employees with financial authority, privileged access, or useful professional relationships.
  • Initial access: Generative AI produces phishing messages, fake login pages, malicious documents, and convincing impersonations.
  • Execution: Coding assistants help attackers write or troubleshoot scripts and malware.
  • Persistence and movement: AI can help analyze compromised systems and identify routes to more valuable accounts or data.
  • Evasion: Attackers modify malicious code, messages, and infrastructure to reduce the chance of detection.
  • Data theft and extortion: AI can sort stolen information, identify sensitive files, translate documents, and generate targeted ransom demands.

This allows attackers to move faster. It can also shorten the time defenders have to discover and contain malicious activity.

10 Ways Attackers Are Using AI in Cyberattacks

1. Writing More Convincing Phishing Emails

Generative AI can create clear, natural-looking emails without the spelling mistakes or unusual phrasing traditionally associated with phishing. Attackers can adjust the message for a particular industry, role, event, or language.

2. Automating Target Research

AI tools can examine large amounts of publicly available information and summarize useful details. An attacker may learn who approves payments, which suppliers a company uses, and how its employees communicate.

3. Creating Deepfake Audio and Video

Voice cloning allows criminals to imitate executives, colleagues, customers, or family members. Deepfake video can make an impersonation even more believable. Victims may then be pressured to transfer money, disclose credentials, or bypass normal procedures.

4. Scaling Business Email Compromise

AI helps criminals write realistic payment requests and maintain longer conversations with victims. It can reproduce an executive’s tone, explain a supposedly urgent situation, and respond convincingly to follow-up questions.

5. Generating and Debugging Malicious Code

Large language models can assist with writing scripts, finding coding errors, translating code between programming languages, and creating basic malware components. Safety controls restrict many legitimate platforms, but attackers try to bypass them or use less-regulated tools.

6. Producing Polymorphic Malware

Polymorphic malware changes parts of its code or appearance while keeping its harmful purpose. AI can help generate variations more quickly. Each version may have a different signature, making traditional signature-based detection less reliable.

7. Improving Password Attacks

Machine learning can study leaked password patterns and predict likely combinations. Attackers may combine this capability with personal information or automated login attempts to make password guessing more targeted.

8. Evading Security Controls

AI can help attackers rewrite phishing content, alter code, disguise malicious files, or imitate normal user behavior. Microsoft documented a credential-phishing campaign that appeared to use AI-generated code to conceal malicious behavior inside an SVG file.

9. Attacking AI Systems

Organizations’ own AI tools can become targets. Criminals may poison training data, manipulate model inputs, steal models, extract confidential information, or use prompt injection to make AI applications perform unintended actions.

10. Running Fraudulent Chatbots and Personas

Attackers can create fake customer support agents, recruiters, romantic partners, or investment advisers who communicate with many victims at once. AI-generated profile images, documents, messages, and websites make these identities appear more credible.

Break into one of the world’s most recession-proof careers with the Advanced Executive Program in Cybersecurity. Designed for beginners and career-switchers, this program builds your confidence step by step, covering networks, threat hunting, cryptography, and cloud security.

Real-World Examples of AI in Cyberattacks

AI-enabled impersonation is already being used in active campaigns. In 2025, the FBI warned that criminals were sending AI-generated voice messages while impersonating senior US officials. The attackers attempted to build trust before directing targets to malicious links or separate messaging platforms.

Microsoft has also observed threat actors using AI to draft phishing lures, translate content, summarize stolen data, create scripts, and debug malware. Its research indicates that current criminal use generally focuses on improving existing operations rather than handing an entire attack to a fully autonomous AI system.

Deepfake-enabled financial fraud presents another serious risk. A fake voice or video call can appear to confirm an unusual payment request, weakening the value of verbal approval. These cases show why seeing or hearing a familiar person is no longer sufficient proof of identity.

How Organizations Can Defend Against AI-Powered Attacks?

Organizations need layered controls that address people, identities, devices, data, and AI systems.

  • Use phishing-resistant multifactor authentication, such as passkeys or hardware security keys.
  • Require independent verification for payments, password resets, and requests for sensitive data.
  • Establish a safe word or verification process for urgent voice and video instructions.
  • Apply least-privilege access and regularly review privileged accounts.
  • Monitor endpoints, email, cloud platforms, identities, and network behavior continuously.
  • Patch vulnerabilities promptly and maintain tested, isolated backups.
  • Train employees with realistic AI phishing, voice-cloning, and deepfake scenarios.
  • Secure AI models, prompts, plugins, training data, and application programming interfaces.
  • Test incident response plans and clearly assign decision-making responsibilities.

AI-powered security tools can process large amounts of activity and highlight unusual patterns. Nevertheless, human oversight remains essential when context, business risk, ethics, or high-impact decisions are involved.

Looking for a high-paying cybersecurity career? Explore the Security Engineer roadmap covering in-demand skills, salary potential, and the fastest path into this growing field.

Key Takeaways

  • AI makes conventional attacks faster, more personalized, and easier to scale.
  • Phishing, deepfakes, malware development, impersonation, and evasion are major areas of misuse.
  • AI can support the entire attack lifecycle, but human criminals still direct most campaigns.
  • Organizations must verify identities through trusted channels rather than relying on appearance or voice.
  • Strong security requires automated protection, intelligent detection, employee awareness, and executive oversight.

FAQs

1. How do attackers use AI to create phishing emails?

Attackers collect information about a person or organization and ask generative AI to create a relevant message in the right language and tone. They can produce many customized versions, remove grammatical errors, imitate an executive, and automate follow-up replies.

2. What is polymorphic malware, and how does AI generate it?

Polymorphic malware repeatedly changes identifiable elements of its code while retaining its malicious function. AI can help rewrite sections, vary file structures, rename variables, or generate alternative code. These changes may help the malware avoid tools that depend heavily on known signatures.

3. Which malicious LLMs are being used by hackers today?

Names such as WormGPT, FraudGPT, Evil-GPT, and DarkBERT-style services have been advertised in criminal communities. However, availability and capability claims are difficult to verify, and some offers may be scams. Attackers also misuse general-purpose models, stolen accounts, jailbroken systems, and privately hosted open models.

4. How will AI change cyberattacks by 2026?

In 2026, AI is enabling faster reconnaissance, multilingual phishing, realistic impersonation, automated fraud, code generation, and more adaptive evasion. Fully autonomous attacks remain less common than AI-assisted operations, but defenders should expect attack cycles to become faster and more personalized.

5. What are the three pillars for defending against AI cyberattacks?

The three pillars identified by MIT Sloan are automated security hygiene, autonomous and deceptive defense systems, and augmented oversight and reporting. They help organizations prevent recurring weaknesses, detect evolving threats in real time, and provide leaders with better information for managing cyber risk.

Our Cyber Security Program Duration and Fees

Cyber Security programs typically range from a few weeks to several months, with fees varying based on program and institution.

Program NameDurationFees
Professional Certificate Program in AI-Powered Cybersecurity

Cohort Starts: 14 Sep, 2026

18 weeks$3,790
AI-Integrated Cyber Security Expert Master's Program4 months$2,599

Recommended Reads