The company relied on an outdated security stack, which failed to generate actionable intelligence from its high volume of network traffic. This lack of return on investment (ROI) prevented the security team from decommissioning redundant tools and streamlining their technical environment.

While the perimeter was monitored, the team lacked the specialized tools to inspect lateral traffic. This left the company blind to internal movement, making it difficult to stop threats that had already bypassed north-south defenses to target sensitive manufacturing segments.

With a mature network team managing thousands of endpoints worldwide, any new solution had to integrate seamlessly into a high-volume, high-stakes environment. The company needed a platform that could scale globally without introducing performance risk.

As an engineering giant, the company maintains proprietary data privacy standards that exceed standard regulations. Any network-based detection platform had to provide deep forensic evidence while respecting these strict internal data-handling rules.

The automotive parts leader secured the required forensic depth and network control when it deployed ExtraHop, which analyzes 100 Gbps of east-west traffic and uses high-speed decryption to immediately find threats previously hidden within encrypted flows.

The cloud-scale machine learning built into the ExtraHop platform reduced the SOC's operational burden by providing high-fidelity, low-noise detections. This shift allowed analysts to move their focus from low-value false positives to highly reliable network activity, signaling true post-compromise threats and endpoint detection and response (EDR) evasion tactics.

The security team achieved comprehensive insight by using identity-based investigation, which links malicious network activity directly to user and service accounts, finally enabling the detection of all missed AD and lateral movement attacks.

ExtraHop fundamentally simplified incident response workflows because it established itself as the definitive source of network truth, automatically feeding high-value contextual data to the customer’s existing SIEM and EDR platforms.

The company gained efficiency and reduced complexity by consolidating NDR, NPM, and IDS capabilities into one unified, integrated solution for comprehensive network security and observability.

The automotive parts leader mitigated major risk by gaining deep fluency (parsing over 90 protocols) that allowed for accurate decoding of all traffic, including sensitive database communications, without introducing performance risk. This was critical for detecting hidden AD attacks and lateral movement.