It watches every layer of your Internet connection simultaneously so it can spot an attack the moment something looks even slightly off, like a security guard with eyes on every door at once.

Crosslayer Labs correlates signals from DNS resolution, BGP routing announcements, TLS certificate issuance, and JavaScript dependencies in real time to detect anomalies that single-layer monitoring tools miss entirely. By fusing heterogeneous data streams—each with different formats, cadences, and trust models—their ML pipeline identifies subtle attack patterns such as BGP hijacks used to fraudulently obtain TLS certificates, DNS poisoning combined with JavaScript supply chain injection, or coordinated multi-vector campaigns targeting healthcare and fintech infrastructure. Their ACM/IRTF ANRW 2022 research demonstrated ML-based network outage classification, and the production system likely extends this with streaming anomaly detection models (autoencoders, isolation forests, or LSTM-based sequence models) that learn normal cross-layer behavior and flag deviations with high precision and low false-positive rates. This approach transforms Internet security from reactive, siloed alerting into proactive, holistic threat detection.

It's like having a doctor who checks your blood pressure, heart rate, temperature, and bloodwork all at once instead of four separate specialists who never talk to each other.

It double-checks every new website security certificate from multiple locations around the world so no one can trick the system into issuing a fake one.

MPIC, invented by Crosslayer Labs' founders, fundamentally changes how certificate authorities validate domain ownership before issuing TLS certificates. Instead of relying on a single validation check from one network location—which is vulnerable to localized BGP hijacks or DNS poisoning—MPIC performs corroborating checks from multiple geographically and topologically diverse vantage points simultaneously. ML models analyze the responses for consistency, flagging statistical outliers that indicate an adversary is manipulating routing or DNS to fraudulently pass domain validation. The system must handle massive scale (millions of certificate issuance events), extremely low latency requirements, and adversarial conditions where attackers actively try to evade detection. By embedding this intelligence directly into the certificate issuance pipeline, Crosslayer Labs has created a security primitive that protects every HTTPS connection on the Internet—a rare example of a startup's core technology becoming a global infrastructure standard through the CA/Browser Forum.

It's like requiring three different notaries in three different cities to independently verify your identity before you can get a passport, so no single forger can fool the system.

It automatically finds every door, window, and hidden entrance to your online presence that you didn't even know existed, then tells you which ones are unlocked.

Crosslayer Labs' attack surface discovery engine uses ML to automatically enumerate and map all externally facing assets—APIs, web applications, subdomains, cloud services, third-party JavaScript dependencies, and certificate relationships—that constitute an organization's Internet presence. Unlike traditional scanners that rely on known asset inventories, the system employs graph-based exploration algorithms that follow certificate transparency logs, DNS record chains, BGP prefix relationships, and code dependency trees to uncover shadow IT, forgotten services, and supply chain risks. NLP and semantic analysis may be applied to identify brand impersonation or typosquatting domains. Each discovered asset is scored for risk based on configuration, exposure, patch status, and contextual threat intelligence, enabling security teams to prioritize remediation. For high-risk verticals like healthcare (HIPAA compliance) and cryptocurrency (exchange security), this continuous, automated mapping replaces manual audits that are outdated the moment they're completed, providing a living, always-current view of organizational risk.

It's like hiring a drone to fly around your entire property every hour and flag every new crack, open gate, or suspicious person—instead of walking the perimeter yourself once a quarter with a clipboard.