TL;DR

CrowdStrike flagged suspicious MFA bypass activity via legacy authentication. Dropzone AI investigated and found the behavior was legitimate, tied to sanctioned business processes using outdated protocols. Consistent login patterns, internal IPs, and directory group membership confirmed it wasn’t a breach—just technical debt. The case demonstrates how AI-powered investigation can quickly differentiate between genuine threats and false positives, reducing alert fatigue for security teams.

Executive Summary

When CrowdStrike flagged a potential MFA bypass using legacy client authentication, it appeared to be a classic security compromise. Two user accounts were authenticating via outdated "BAV2ROPC" protocols from various IP addresses, including AWS cloud infrastructure. However, Dropzone AI's investigation revealed legitimate business activity: both users belonged to a directory group named "LegacyAuthException-AuthenticatedSMTP," indicating sanctioned legacy authentication for business-critical systems. The key differentiators were consistent historical login patterns over weeks, proper group assignments, and a mix of internal and documented cloud IP addresses. This case demonstrates how context and historical analysis distinguish genuine threats from operational reality.

Introduction

Some alerts scream "breach." This one whispered it. It looked like a textbook MFA bypass using legacy client authentication. But after a fast, deep dive, Dropzone’s AI SOC analyst found that this wasn't an attack—just outdated, sanctioned behavior. Here's what tipped the scales.

CrowdStrike flagged an incident as "Potential MFA Bypass Using Legacy Client Authentication." The alert centered on two accounts: User A (s**)** and User B (no-reply-****). The concern? Both users had successfully authenticated using legacy protocols from a variety of IP addresses. The user agent used in each case was "BAV2ROPC"—a well-known legacy authentication flow associated with Basic Authentication and Resource Owner Password Credentials.

Initial Indicators

Right away, enriching the involved IP addresses was prioritized. Dropzone found the context:

  • 192.X.X.195: Part of an CIDR block owned and operated by the organization.
  • 52.x.x.102 and 52.x.x.27: Belonged to Amazon Web Services’ public cloud infrastructure.

On the surface, cloud-based IPs from a public provider like AWS can look risky. They're frequently abused in attacks and allow threat actors to blend into legitimate-looking traffic. But raw IP alone doesn’t make something malicious. The AI SOC analyst knew to look deeper.

What the User History Added to the Investigation

Dropzone pulled user behavior logs and began to trace patterns. The results were illuminating.

User A:

  • Logged in 37 times from the same internal IP using "BAV2ROPC."
  • The behavior was consistent, recurring almost daily over a full month.

User B:

  • Used two separate AWS-based IPs.
  • Recorded 31 logins from 52.x.x.102 and 28 logins from 52.x.x.27.
  • The agent was always the same, with no sign of escalation or deviation.

If this had been a threat actor, they were behaving like the most punctual employee in the company.

The Context That Closed the Case

The tipping point came from user group analysis. Both users belonged to a directory group named something like ***-LegacyAuthException-AuthenticatedSMTP. That name isn’t subtle—it pointed directly to a known and accepted business exception.

These users were allowed to bypass modern authentication policies due to legacy system requirements. Likely a mail relay, scan-to-email service, or proprietary app that didn’t yet support OAuth. Yes, legacy authentication is inherently less secure. Microsoft has made clear recommendations to deprecate it. But sanctioned use of older protocols still exists in many environments, particularly those with deeply embedded infrastructure.

This wasn’t a breach. It was technical debt playing out predictably.

Analyst Takeaways

When faced with a suspicious alert, a good analyst doesn't just look for what's different. They look for what makes sense. In the above case, we can learn from the Dropzone AI SOC analyst:

  • Check your groups. Naming conventions often reveal intent. "Exception" groups are worth tracking closely.
  • Validate history. If a user has been logging in with the same pattern for weeks or months, the behavior is likely expected.
  • Know your CIDRs. Recognizing your own IP space versus public cloud helps triage faster.
  • User agent consistency matters. Yes, user agents can be spoofed, but consistent use is a valuable piece of evidence alongside other indicators. Repetition suggests routine.

Alert Investigation Verdict: Benign

Ultimately, this alert did what it was supposed to: it surfaced something that could be risky. But during the investigation, the supporting evidence told a different story. Everything lined up—IP history, group assignment, user behavior, and organizational policy.

This wasn’t noise. It was a call to double-check policy exceptions, reassess your roadmap for modern authentication adoption, and make sure legacy paths are still being monitored. But it wasn’t a compromise.

When legacy auth is part of your reality, your context becomes your best defense.

More Investigations Like This

This case wasn’t a breach, but many others are. Knowing the difference requires experience, context, and speed. Dropzone AI brings all three to the table.

Explore the Dropzone AI Demo Gallery to see real-world investigations involving:

  • Initial Access alerts
  • Cloud Account Compromise
  • Suspicious Login Patterns
  • Abused Service Accounts

Dropzone AI helps you analyze faster, eliminate false positives, and focus on the threats that matter. Want to see more real-world investigations performed by the Dropzone AI SOC analyst? Check out these previous AI SOC Diary entries:

  1. Silent Threat or Software Update? Decoding a Suspicious Dell Installer Alert
  2. Unmasking the Relay: Navigating Alerts Triggered by Anonymized IP Services
  3. How Dropzone AI Cracked a Tricky VPN Logon Alert—and Why Context Matters

MFA Bypass: Attack vs. Legitimate Behavior Comparison

Malicious MFA Bypass Indicators Observed Legitimate Behavior
Authentication Frequency Sporadic, irregular login attempts Consistent daily pattern (37 logins/month User A)
IP Address Consistency Multiple random/suspicious locations Stable internal IP (192.X.X.195) and documented AWS IPs
User Agent Behavior Varying or suspicious user agents Consistent "BAV2ROPC" across all sessions
Time Patterns Unusual hours, weekend spikes Regular business hours alignment
Account Types High-privilege or compromised accounts Service accounts with specific functions
Geographic Distribution Impossible travel, foreign locations Expected organizational locations
Directory Group Membership Standard user groups, privilege escalation "LegacyAuthException-AuthenticatedSMTP" group
Historical Context Recent password changes, new behavior Established pattern over weeks/months
Authentication Success Rate Failed attempts followed by success Consistent success without brute force
Associated Network Activity Lateral movement, data exfiltration Expected SMTP relay functionality

FAQs

What made these authentications suspicious in the first place?
Legacy authentication protocols like "BAV2ROPC" lack modern MFA protections, making them prime targets for attackers leveraging techniques like password spray attacks.
What’s so risky about IP addresses from cloud providers?
Cloud provider IP addresses can be leveraged by threat actors for anonymity, obscuring malicious origins behind common and trusted third-party infrastructure.
How does historical data help in these alert investigations?
Understanding normal user behavior incorporates historical authentication actions. Established consistent historical patterns strongly indicate normalcy rather than anomalous behaviors.
Should legacy authentication always be flagged as malicious?
Not always—some organizations have legitimate (yet frequently discouraged) needs for legacy authentication due to older proprietary applications or services.
Why is group membership significant within this analysis?
Group assignments can indicate explicit administrative permissions or exceptions that denote compliance-approved and documented legacy authentication use-cases.
How critical is knowing an IP address range allocation (CIDR blocks)?

Identifying the ownership and management of IP ranges helps distinguish between internal trusted use and external unknown or risky activity.

What should I do if legacy authentication protocols trigger frequent alerts?

Review historical user activity, validate existing MFA configurations, and consider initiating a phased plan migrating towards more secure Modern Authentication processes.

What's the main lesson from this investigation?

Not all signals of risky authentication are malicious; historical usage and operational context significantly influence alert triage outcomes and reduce false positives.

Where can I see more real-world alert investigations like this?

Head over to Dropzone AI’s demo gallery to explore a variety of investigations across tactics like Initial Access and Cloud Account Compromises.

Key Technical Definitions

What is Legacy Client Authentication?

Legacy client authentication refers to older authentication protocols that predate modern multi-factor authentication (MFA) standards. These protocols, including Basic Authentication and Resource Owner Password Credentials (ROPC), transmit credentials without the enhanced security layers found in contemporary OAuth 2.0 implementations. While inherently less secure, legacy authentication remains necessary for older applications and services that haven't been updated to support modern authentication frameworks.

Understanding BAV2ROPC Protocol

BAV2ROPC (Basic Authentication Version 2 Resource Owner Password Credentials) is a specific legacy authentication flow that allows applications to authenticate users by directly handling their username and password credentials. This protocol bypasses multi-factor authentication requirements and is commonly used by automated systems, mail relays, and legacy applications that require programmatic access to Microsoft 365 services.

CIDR Block Analysis in Security Investigations

CIDR (Classless Inter-Domain Routing) blocks represent ranges of IP addresses under common ownership or management. In security investigations, identifying whether an IP address belongs to an organization's internal CIDR blocks versus external public cloud providers helps analysts quickly assess the legitimacy of network traffic and authentication attempts.

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Andrew Jerry
SOC Automation Lead

Andrew Jerry is a SOC Automation Lead at Dropzone AI, where he drives innovation for AI-powered security solutions tailored to SOC analysts. With a focus on aligning technology with real-world user workflows, Andrew ensures that Dropzone AI's platform empowers analysts to respond decisively and efficiently to security threats. Before joining Dropzone AI, he honed his expertise as a Senior Detection & Response Analyst at Expel, leading high-stakes investigations and mentoring security teams. Passionate about redefining modern security operations, Andrew Jerry combines technical acumen with a user-first approach to deliver impactful solutions.

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Self-Guided Demo

Test drive our hands-on interactive environment. Experience our AI SOC analyst autonomously investigate security alerts in real-time, just as it would in your SOC.
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A screenshot of a dashboard with a purple background and the words "Dropzone AI" in the top left corner.