Identity Threat Detection and Response Use Cases

Auth Sentry's ITDR platform detects identity-based attacks that bypass traditional security tools. Here's how we protect against the most critical threats.

Compromised Credential Detection

Attackers with valid credentials don't trigger traditional security alerts. Auth Sentry detects when legitimate credentials are being used by unauthorized actors—even after successful authentication—by analyzing behavioral patterns that deviate from established baselines.

  • Detect credential stuffing and password spray attacks
  • Identify impossible travel patterns and location anomalies
  • Spot dormant accounts suddenly becoming active
  • Correlate failed login attempts with successful access
  • Track credential usage across multiple applications
See It In Action

Real-World Scenario

An employee's credentials are stolen via phishing. The attacker logs in successfully from a new location at 2 AM, accesses the corporate VPN, and begins downloading files from SharePoint.
Auth Sentry Detection: Flags impossible travel (employee in NYC, login from Eastern Europe), unusual access time, and abnormal data access pattern. Alert generated with 97% confidence before data exfiltration completes.

Lateral Movement Prevention

Once inside your network, attackers pivot between systems using harvested credentials and session tokens. Auth Sentry maps identity relationships across your environment and detects unusual access chains that indicate lateral movement in progress.

  • Track identity usage across connected systems
  • Detect unusual system-to-system access patterns
  • Identify credential hopping and pass-the-hash attacks
  • Map access chains from dev to staging to production
  • Alert on rapid multi-system access within short timeframes
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Real-World Scenario

An attacker compromises a developer workstation and uses cached credentials to access 4 different production systems in 5 minutes, escalating privileges at each hop.
Auth Sentry Detection: Graph-based analysis identifies the unusual access chain. AI Agent correlates with dormant account pattern and privilege escalation signatures. Tokens revoked automatically after user confirmation via Slack.

Insider Threat Detection

Distinguishing between legitimate employee behavior and malicious insiders is one of security's hardest problems. Auth Sentry's continuous behavioral analysis detects subtle changes that indicate compromised accounts or employees acting outside their normal patterns.

  • Baseline normal behavior for every identity
  • Detect access to resources outside job function
  • Identify bulk data downloads or unusual export patterns
  • Monitor for privilege abuse by administrators
  • Track behavioral changes indicating account compromise

Real-World Scenario

A departing employee begins accessing customer databases they haven't touched in months, downloading contact lists and proprietary data during their notice period.
Auth Sentry Detection: Behavioral baseline shows zero database access for 6 months. Sudden access to sensitive customer data triggers investigation. Pattern matches known data exfiltration signatures. Security team alerted before data leaves the organization.

Service Account Abuse

Service accounts and machine identities are chronically over-permissioned and under-monitored. Auth Sentry learns the expected behavior of every non-human identity and detects deviations that indicate compromise or misconfiguration.

  • Monitor API keys, service accounts, and OAuth tokens
  • Detect access from unexpected IP ranges or times
  • Identify privilege escalation and permission changes
  • Track dormant service accounts becoming active
  • Alert on API call patterns outside normal operations

Real-World Scenario

A CI/CD pipeline service account with broad AWS permissions is compromised. The attacker uses it to spin up cryptocurrency mining instances at 3 AM on a Saturday.
Auth Sentry Detection: Service Account Agent detects API calls outside the normal deployment window, resource creation in unexpected regions, and access patterns inconsistent with CI/CD workflows. Alert raised within minutes.

MFA Bypass & Fatigue Attacks

MFA is critical but not foolproof. Attackers exploit MFA fatigue by bombarding users with push notifications until they approve, or bypass MFA entirely through session hijacking. Auth Sentry detects these attacks even when authentication technically succeeds.

  • Detect repeated MFA push denials followed by approval
  • Identify sessions authenticated at unusual times
  • Monitor for authentication from impossible locations
  • Track MFA method changes and recovery events
  • Correlate authentication events with threat intelligence
See How It Works

Real-World Scenario

An attacker with stolen credentials sends 50+ MFA push notifications to a user at 2 AM. Exhausted and confused, the user finally taps "Approve." The attacker gains access.
Auth Sentry Detection: MFA fatigue pattern detected—multiple denials followed by approval at unusual hour. AI Agent immediately messages user via Slack: "Did you just approve an MFA request?" User confirms compromise. Session terminated automatically.

Session Hijacking

Stolen session tokens and cookies let attackers bypass authentication entirely. Auth Sentry monitors post-authentication activity and detects when valid sessions are being used from unexpected contexts—catching hijacked sessions before damage is done.

  • Monitor session usage across IP addresses and devices
  • Detect token replay attacks and cookie theft
  • Identify sessions active from multiple locations
  • Track OAuth token usage patterns
  • Alert on session activity outside normal hours

Real-World Scenario

Malware on an employee's laptop steals browser cookies. The attacker imports the cookies to their own browser in another country and accesses the victim's email and cloud storage.
Auth Sentry Detection: Same session token used from two different countries within minutes. Impossible travel detected. Session invalidated and user notified. All active tokens for the identity revoked pending security review.

Agentic AI & MCP Security

AI agents are service accounts with autonomy—and that makes them dangerous. Organizations racing to deploy agentic AI often grant broad permissions "to make it work," creating over-privileged identities that operate with little visibility. When AI agents connect to tools via MCP or similar protocols, they can access data and systems far beyond their intended scope. Auth Sentry monitors AI agent behavior just like any other identity.

  • Detect over-permissioned AI agents accessing sensitive resources
  • Monitor MCP tool calls and data access patterns
  • Identify AI agents operating outside intended scope
  • Track AI-to-AI delegation and credential sharing
  • Alert when AI agent behavior deviates from baseline
Get Started

Real-World Scenario

A company deploys an AI coding assistant with repository access. The agent is manipulated through a prompt injection in a pull request to access credentials stored in a private repo and exfiltrate them via an external API call.
Auth Sentry Detection: AI agent accessing credential files outside normal code review patterns. Outbound API call to unrecognized endpoint flagged. Agent permissions automatically scoped down and security team alerted for investigation.

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