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Automatically stop data breaches and security threats caused by employees on email. Powered by machine learning, Tessian detects anomalies in real-time, integrating seamlessly with your email environment within minutes and starting protection in a day. Provides you with unparalleled visibility into human security risks to remediate threats and ensure compliance.

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Account Takeover Protection

Defend Against Account Takeover Attacks.

Account takeover (ATO) is one of the fastest growing threats over email as these originate from trusted sources and have low detection rates. Tessian can stop even the most advanced ATO attacks with machine learning-powered anomaly detection, behavioral analysis, and natural language processing (NLP).



The ATO Challenge


ATO threats pose an immense danger to organizations as hackers use sophisticated impersonation techniques and trusted email accounts to launch attacks that evade conventional threat detection tools. While organizations can secure their own email infrastructure, they have no control over their extended network of customers, partners, and suppliers.


Detecting attacks from trusted accounts is extremely difficult:
  • The malicious email is from a trusted source. As a result, the recipient is less cautious.
  • The emails are 100% real with legitimate headers and metadata that pass email authentication.
  • Organizations have no visibility over breaches that happen across this trusted network.

The ATO Attack Chain:

  • 1. Credential Theft

    An attacker steals the credentials of an employee in your trusted external network using a variety of techniques such as a non-targeted phishing attack, a targeted spear phishing email, brute force attack, password compromise, or leaked credentials online.

  • 2. Account Takeover

    Once the attacker gets hold of the account credentials, they choose a target organization in the network of the victim and start sending out emails from the compromised account. The emails usually contain a malicious link, malware or even request confidential information about the target company/employees/customers, funds transfer, credentials etc.

  • 3. Breach

    The recipients of these emails have no idea that their trusted network has been compromised. These emails appear genuine, are from a trusted contact, have legitimate headers, and pass authentication. The unsuspecting receiver performs the requested task, which usually results in a breach.

ATO Can Lead to Business Email Compromise


ATO is one of the pathways to Business Email Compromise (BEC), which is the biggest cause of email breaches globally.


Sometimes, the ATO attack chain does not end with an individual employee’s credentials being compromised. The attacker might use this account to access the email credentials of other employees within the same organization, especially the C-suite executives to execute a breach.



Detecting Email Credential Theft Could Take Months


One of the biggest challenges before CISOs is to lower their risk exposure by building a proactive security strategy that can anticipate, identify, and prevent potential ATO attempts well ahead of an actual breach.


Most legacy email security tools largely rely on previously known attack signatures to stop threats. As a result, organizations today learn about these attacks months after they have been breached and have incurred significant damages.



How Tessian Stops ATO Attacks with Human Layer Security

  • Detect Anomalous Signals

    Using machine learning, behavioral analysis, and NLP, Tessian detects a broad range of threat signals such as anomalous geophysical location, time email is sent, IP address, email client, unusual reply-to addresses, anomalous recipients, and more. Such granular analysis allows Defender to detect anomalies in even the most sophisticated and painstakingly crafted attacks.

  • Spot Suspicious Payloads

    Tessian can also spot with precision any language that conveys suspicious intent using NLP; suspicious URLs using machine learning; and suspicious attachments through content interrogation. The algorithm does all these in sub-seconds, without any perceived impact on the user experience.

  • Model Threats, Alert Users, and Remediate

    Tessian’s machine learning algorithm continuously analyzes and learns from email communications across its global network to build profiles and models of companies and their employees to understand what their normal email communication looks like.

    Combining this with end user alerts allows employees to identify and self-triage ATO emails. Tessian also offers administrators a variety of remediation options and the flexibility to determine the type of controls and alerts for end users.

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Learn more about the risks in your trusted vendor network.
Learn how Tessian Defender detects and stops external ATO threats with precision.

The Value of Tessian against ATO

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Stop ATO Attacks with Tessian.
Tessian Defender uses machine learning, communication patterns, and behavior analysis to stop difficult-to-detect inbound threats like ATO. Learn how.