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20.4 Application Security Implementation
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🧠 AI Threats in Cybersecurity
AI is a double-edged sword: Can be used for security and cyber attacks.
AI-enhanced cyberattacks are more:
Sophisticated
Targeted
Scalable
## ☠ How Attackers Use AI Tools Like ChatGPT
- Phishing & Social Engineering:
- AI writes realistic phishing emails/messages.
- Bypassing Filters:
- AI generates obfuscated code to slip past security tools (e.g., CAPTCHA).
- Malicious Code Generation:
- AI can help write or test malware/code for exploits.
- Chatbot Abuse:
- Attackers manipulate AI-powered bots to leak data or execute harmful commands.
## 🛠 Common Web Application Attack Vectors
- Exploiting Known Vulnerabilities:
- In web servers, databases, CMS platforms, or third-party libraries.
- AI-Assisted Reconnaissance:
- AI reads pseudo-code to find and exploit vulnerabilities (proof-of-concept code).
SAST
Static Application Security Testing
scans your app's raw code (the blueprint) for security flaws before it even runs.
Scans source code (at rest)
White-box testing
(Static Application Security Testing):
- "Static" = No running.
- Early in development.
DAST
(Dynamic Application Security Testing):
It's like a hacker trying to break into your app while it's actually running, without knowing how the inside code works, to find vulnerabilities.
Tests running applications
Black-box testing
Automated Scanners
Automatic checks.
Runs scheduled scans for known vulnerabilities.
Efficient for common issues, but can miss complex or zero-day flaws.
PTaaS
(Penetration Testing as a Service) - Quick Notes
What it is: Pen testing delivered as an ongoing service, not a one-time thing.
Key Idea: Combines automation with human ethical hackers.
Why it's Good (Benefits to Remember):
Continuous: Always testing, ongoing protection.
Scalable/Flexible: Easy to adjust what's being tested.
Real-Time: Fast alerts for new threats.
Expert-Driven: Real pros are involved.
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