This content originally appeared on DEV Community and was authored by Ibrahim S
Cyber attacks are malicious attempts to access, damage, or disrupt systems, networks, or data.
Phishing Attacks
• What it is: Attackers use deceptive emails to steal credentials or deploy malware.
• Why it matters: AI-powered automation enhances phishing sophistication.
•How to prevent it: AI-driven email security, user training, and multi-factor authentication (MFA).Ransomware
• What it is: Malware encrypts AI models or training data, demanding payment.
• Why it matters: AI-dependent businesses risk model corruption and financial loss.
•How to prevent it: Secure offline backups, endpoint protection, and zero-trust access.Denial-of-Service (DoS) Attacks
• What it is: Overloading AI APIs or inference systems to cause failures.
• Why it matters: Real-time AI services (finance, healthcare) must remain online.
•How to prevent it: Rate limiting, cloud-based DoS protection, AI-driven anomaly detection.Man-in-the-Middle (MitM) Attacks
• What it is: Intercepting AI model inputs or outputs to alter decisions.
• Why it matters: AI-driven automation in finance, healthcare, and security can be compromised.
•How to prevent it: End-to-end encryption, TLS 1.3, AI model watermarking.SQL Injection
• What it is: Attackers manipulate AI databases to alter training data.
• Why it matters: Corrupt training data skews AI decision-making.
•How to prevent it: Parameterized queries, strict database access controls.Cross-Site Scripting (XSS)
• What it is: Injecting malicious scripts into AI-powered interfaces.
• Why it matters: AI chatbots and LLM-driven apps can be hijacked.
•How to prevent it: Input sanitization, Content Security Policy (CSP), AI-based anomaly detection.Zero-Day Exploits
• What it is: Exploiting unknown AI system vulnerabilities.
• Why it matters: Zero-day attacks on AI can lead to data breaches, fraud, or misinformation.
•How to prevent it: Threat intelligence tools, security patches, AI-driven attack simulations.DNS Spoofing
• What it is: Manipulating DNS records to reroute users to fake AI platforms.
• Why it matters: Attackers can steal credentials or inject adversarial inputs into AI models.
•How to prevent it: DNSSEC, AI-driven DNS monitoring, endpoint verification.
This content originally appeared on DEV Community and was authored by Ibrahim S