What I Studied
This exercise involved using a reverse image search on a search engine to obtain related images and online information. The goal was to see how images can reveal patterns, sources, or identities important for cybersecurity and open-source investigations.
Tools/Techniques Used: Google Images, TinEye, Yandex Reverse Image, browser inspection
Core Concepts: Image metadata, visual pattern recognition, OSINT collection ethics
What I Learned
Practice looking at pictures to find important details. Check websites, similar pictures, and location clues to verify authenticity. Small elements like logos, landmarks, and timestamps can provide key information. Learned that if metadata is wrong or the same image appears on multiple sites, it may be reposted or false.
Hands-on Skills Gained:
- Extracting and analyzing image metadata
- Recognizing visual patterns to verify authenticity
- Cross-referencing images across sources
Observation:
Reverse image search helps identify reposted content, track sources, and detect misleading or fake information.
Why It Matters
In business or investigations, reverse image search helps uncover data leaks, fake brands, and scams. It encourages critical thinking and shows how open data can be used responsibly. It also verifies media authenticity and tracks false information.
How It Maps to the Job / Framework
- NIST NICE: IN-INT-001 (Cyber Threat Intelligence)
- ASD Cyber Skills Framework: INT01 – Collect and Analyse Information
These skills are useful for analysts gathering intelligence, validating sources, and producing actionable insights.
Key Takeaways
- Reverse image search exposes context beyond what’s visible
- Metadata and visual similarities validate or disprove authenticity
- Effective OSINT depends on cross-referencing and ethical analysis
- Visual forensics is an underrated cybersecurity skill
- Documenting evidence supports professional transparency