been working on a phishing link detector, the false positives were way harder than i thought
Description
This content discusses the development of a phishing URL detector focused on identifying phishing attempts based solely on URL text analysis. The detector achieves about 90% detection on unseen phishing URLs but struggles with false positives and phishing hosted on compromised legitimate sites. It highlights challenges such as phishing URLs hosted on trusted domains like docs.google.com and the difficulty of blocking such domains outright. The tool is open source and intended as a learning resource rather than an active threat report.
Reddit Discussion
I've been building a phishing URL detector to learn more about detection, using about 15k verified PhishTank URLs. A few things surprised me.
The most common phishing host in the whole dataset was docs.google.com. Firebase, 000webhost and other free hosting sites were near the top too. Kind of obvious in hindsight, but domain reputation doesn't help much when the domain is Google.
A lot of it is just simple URL tricks: paypal.com.account-verify.xyz, paypa1.com, punycode look-alikes, and the old [email protected] one where the browser ignores everything before the @.
False positives were honestly the hardest part. An early version flagged github.com/login as phishing because to the model every login page looked sketchy. I ended up tuning it so it stays under about 2% false alarms, since a tool that cries wolf just gets ignored.
It only looks at the URL text and never visits the site, and it tells you why it flagged something. Right now it catches about 90% of phishing on sites it hasn't seen before. The weak spot is hacked legit sites, like a small business site with a phishing kit dropped in /wp-includes/. Really hard to tell from the URL alone.
I made it open source and wrote up everything including my mistakes, so if you're just getting into cybersecurity it might be useful as a reference.
For people who work in a SOC or on email security, how do you deal with phishing on Google Docs, SharePoint etc? You obviously can't just block the domain.
Links cited in this discussion
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The post describes the creation of a phishing URL detection tool trained on approximately 15,000 verified phishing URLs from PhishTank. It identifies common phishing tactics including use of trusted domains (e.g., docs.google.com), URL obfuscation techniques (e.g., punycode, misleading subdomains), and look-alike domains. The detector analyzes URL text only, without visiting sites, and flags URLs with explanations. False positives were a significant challenge, requiring tuning to maintain a false alarm rate under 2%. The tool detects about 90% of phishing URLs it has not previously seen but is less effective against phishing hosted on hacked legitimate sites. The author shares the tool and methodology openly for educational purposes.
Potential Impact
The content does not describe a specific vulnerability or active threat but rather a detection tool and its limitations. The impact is primarily educational, providing insights into phishing URL characteristics and detection challenges. There is no direct exploitation or compromise described.
Defensive Guidance
No direct mitigation is required as this is not a vulnerability or active threat. The author’s tool may assist defenders in detecting phishing URLs with reasonable accuracy. Users should be aware of the limitations, especially regarding phishing on compromised legitimate domains. Blocking entire trusted domains like Google Docs is not practical, so detection must rely on more nuanced URL analysis and additional context.
Technical Details
- Source Type
- Subreddit
- cybersecurity
- Reddit Score
- 0
- Discussion Level
- minimal
- Content Source
- reddit_link_post
- Post Type
- link
- Newsworthiness Assessment
- {"score":27,"reasons":["external_link","established_author","very_recent"],"isNewsworthy":true}
- Has External Source
- false
- Trusted Domain
- false
Threat ID: 6ad517f42cdf04f656959a8e
Added to database: 10/18/2026, 19:03:16 UTC
Last enriched: 10/18/2026, 19:03:22 UTC
Last updated: 10/19/2026, 01:48:13 UTC
Views: 7
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