support application development
How Does AI-Based Ransomware Work?
The way AI-based ransomware works consists of several sophisticated stages: System Infiltration, Environmental Analysis Using Machine Learning, Avoiding Security Detection, Launching an Attack, Displaying Ransom Demands
Sulikan, A,Md., S.Kom.
12/8/20253 min baca
How Does AI-Based Ransomware Work?
1. System Infiltration
Entry into a system is typically achieved through:
Phishing emails using AI-generated natural language,
Fake document attachments,
Pirated software installation files,
Security vulnerabilities,
Unauthorized access via remote desktop (RDP),
AI-based malware loaders.
At this stage, the AI begins analyzing the environment to determine its next move.
2. Environment Analysis Using Machine Learning
Once infiltrated, AI ransomware doesn't immediately attack. It will:
Map the network structure.
Detect what antivirus software is being used.
Analyze the file types on the system.
Determine which ones are high-value.
Check if backups are connected.
This process can take minutes.
3. Evading Security Detection
AI ransomware will attempt to:
Stop certain security services.
Alter file signatures.
Mimic normal system activity.
Disable certain logs.
Use stealth-mode techniques.
Its advantage over traditional ransomware is its ability to change its strategy if detected.
4. Launching the Attack
The AI will begin the process of:
Deleting or encrypting backups.
Encrypting critical files as a priority.
Spreading to other devices on the network.
Selectively disabling critical systems.
Locking users out of system access.
5. Displaying a Ransom Demand
After the attack is complete, the ransomware displays a ransom message, usually accompanied by threats such as:
Data will be sold on the dark web,
System will be unrecoverable,
Payment deadline.
Payment is usually made via cryptocurrency.
Examples of AI-Based Ransomware
Some modern ransomware that are starting to use AI technology include:
BlackCat (ALPHV) – uses machine learning for deployment.
Cl0p Ransomware – utilizes AI-based automation in zero-day exploits.
Hive Ransomware – has an AI module to select the most valuable files.
DarkSide – uses AI for network infrastructure analysis.
While not all are fully AI-powered, they have begun to integrate AI elements to increase the effectiveness of attacks.
Impact of AI-Based Ransomware Attacks
1. Major Financial Losses
Company losses could reach:
System damage,
Loss of critical data,
Decreased productivity,
Ransom costs,
Recovery costs,
The average AI ransomware ransom in 2024–2025 is expected to reach $1–10 million.
2. Reputation Damage
Customer data breaches can damage a company's reputation, causing:
Loss of trust,
Decreased customer base,
Legal repercussions and fines.
3. Sensitive Data Leakage
Ransomware not only encrypts data but also steals it. This data is then sold on the black market.
4. Operational Disruptions
Many companies were down for days or even weeks because their systems could not be restored.
How Can You Prevent AI-Based Ransomware?
Facing such a powerful threat, organizations need to implement layered security.
1. Use Next-Gen Antivirus (NGAV)
NGAV is capable of detecting behavior-based and AI-based ransomware. Best options:
Microsoft Defender for Business
CrowdStrike
SentinelOne
2. Back Up Data Regularly (Air-Gapped Backup)
Ensure backups are not connected to the network and are only accessed when needed.
3. Enable Zero Trust Security
The Zero Trust concept emphasizes:
Trusting no device,
Multi-layered identity verification,
Access restrictions based on need.
4. Regular System Updates
Patch updates are crucial for closing ransomware vulnerabilities.
5. Employee Education and Phishing Training
AI attacks often start from human error, so training is crucial.
6. Use a Latest Generation Firewall
Modern firewalls are capable of:
Detecting anomalies,
Terminating suspicious connections,
Blocking malicious IP addresses.
The Future of Ransomware: Getting Smarter and More Dangerous
In the future, AI-based ransomware is expected to become increasingly sophisticated, with the following capabilities:
Self-learning without human training data,
More realistic video deepfakes,
Automated attacks between IoT devices,
Autonomous zero-day exploits.
With this pace, companies must prepare a robust security infrastructure, not just relying on traditional antivirus.
Conclusion
AI-based ransomware is a highly dangerous new generation of cyber threats. By leveraging artificial intelligence, this type of ransomware can:
Infiltrate undetected,
Learn from target systems,
Attack faster and more effectively,
Select the most valuable files to encrypt,
Delete backups, and
Use advanced social engineering techniques.
The future of cybersecurity requires a new approach that leverages AI to counter AI. Education, system updates, zero-trust strategies, and secure backups are the foundations for countering this threat.
By understanding how it works and how to prevent it, individuals and organizations can protect themselves from the significant risks posed by AI-based ransomware.
