Credential Theft Prevention

Protect users with an IRONSCALES™  solution that detects and blocks credential theft in real-time by analyzing content, communication patterns, and relationship mapping.

We have had well over 100,000 blocks using the IRONSCALES platform.
- Global Director of Infrastructure, Global Manufacturer

Credential Theft Attacks

Credential phishing is the practice of stealing user credentials by masquerading as a reputable brand or known person. Credential phishing commonly includes a malware-less link to a URL that will capture the credentials entered by the victim, compromising user accounts for further attacks.

IRONSCALES uses a 3-pronged approach that analyzes content, communication patterns, and internal/external relationship mapping to prevent credential theft attacks.

Features & Benefits


Computer vision and deep learning block fake login pages in real time

Continuous monitoring of communication patterns to detect anomalies

Real-time identity profiling and scoring of internal and external senders

Block Hard to Detect Fake Login Attacks

Fake login attacks lure victims by mimicking real login pages. Utilizing advanced deep learning algorithms, neural networks and computer vision, IRONSCALES detects in real-time any visual deviations such as layout, images, or logos to determine whether or not a login page is authentic.

Beyond Legacy Credential Theft Protection

Conventional credential theft prevention tactics such as MFA and conventional awareness training are no match for sophisticated attacks that rely on social engineering to exploit human error and weaknesses.

IRONSCALES’ alternative approach ingests numerous data sources via API integration to provide real-time identity profiling and scoring for all internal and external senders. Continuous inspection of suspicious URLs and attachments identifies and removes threats in your inbox, before users can engage.

Bespoke Credential Theft Machine Learning Models

Traditional URL scanning technology analyzes the source code of a suspicious HTML page in order to detect signatures of known attacks. But many attacks avoid malicious code in order to slip past your defenses. They simply wait for users to enter their credentials.

IRONSCALES uses multiple machine learning and AI analysis to detect the typical BEC language that can signal credential harvesting or password spraying attacks.


Malware attacks peaked in 2016, and since then have been declining, while phishing and credential theft are on the rise


24 months is the average time to discover and report credential spills


Credential theft is easier and more cost effective than malware

Phishing remediation through crowdsourcing...
That's the ticket.
- CISO -- Global Financial Services firm





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