Email-Like Account Takeover Protection

Detect compromised user accounts across Slack and Zoom.
See a Demo

Account Takeovers Go Unnoticed

Lateral Movement Risks

With corporate credentials tied to employee email accounts, an email compromise can provide full access to collaboration apps.

Lack of Risk Detection

Account takeovers beyond the inbox bypass the visibility of legacy email security tools.

Hard to Detect

Security teams lack methods to correlate and contextualize suspicious activity across tools to determine the scope and impact of a threat.

Protect Users Across Collaboration Apps

Detects Suspicious Activity Across Applications

It is critical to quickly identify when a compromised account has access to highly-used collaboration apps. Abnormal surfaces suspicious authentication activity, correlating against known-bad IPs and sign-in locations to highlight compromised accounts.

Recreates the Crime Scene in Detail

Once a compromised account has been identified, Abnormal automatically builds a case—giving security teams a detailed timeline of suspicious authentication activity across collaboration applications. From there, teams can further investigate and coordinate remediation.

Enhances Investigation with Identity Integrations

By integrating with major identity providers like Okta, Abnormal enriches each case with single sign-on activity. This gives greater insight into each session, allowing security teams to see discrepancies between IdP sessions and those initiated on Slack and Zoom.

Email-Like Account Takeover Protection Features

Account Takeover Detection

Detect risky sign-in events from known-bad IPs, suspicious locations, or clients.

Account Takeover Investigation

View automatically-generated cases in the Account Takeover tab of your Abnormal Portal, enriched with a timeline of risky activity.

Identity Integration

Ingest data from Okta or Azure Active Directory to further enrich investigation.

Detect the Signs of Compromise Across Slack and Zoom

Catch account takeover attempts that other solutions miss with a behavioral AI-based approach to detection.
See a Demo