Web-LLM-Attacks-PortSwigger Sam33r-Shahzad · COMPLETED
Complete hands-on writeups and practical walkthroughs for PortSwigger Academy's Web LLM Attacks and AI Agent labs. Covers critical vulnerabilities including Indirect Prompt Injection, Excessive Agency, Insecure Output Handling, and Data Exfiltration. Designed to master AI-driven security flaws.
github.com/Sam33r-Shahzad/Web-LLM-Attacks-PortSwigger · ★ 0 · Forks 0 · Size 12.8 MB
SUMMARY
Technologies 1
Scored 1
Observed 1
Practices 6
Evidence 1
Skips 0
COVERAGE
Analyzed 41 files · 10 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
8 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2026-06-15
Last commit 2026-07-03
Active months 2
Commits 10