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Cryptomining requires massive compute resources and can significantly affect availability and performance of your critical systems and applications. Cryptomining attacks start with a single compromised system that spreads malware across your network to compromise and harness more resources.
Cryptomining attacks succeed because your security controls lack the ability to detect the malicious activity as it moves laterally across your network, the anomalous behavior of your compromised systems, or the external communication with the cryptominer. Network traffic analysis (NTA) tools that apply AI to network traffic in an attempt to identify cryptomining-related activity create low-fidelity, probabilistic alerts that require significant additional follow-up investigation.
Lastline Network Defender™ takes a novel approach to providing network security. Applying AI to both network traffic and malicious behavior gives it unmatched insight into advanced threats. Our AI evaluates network traffic and it learns from our vast repository of malicious behaviors to understand the context of all anomalous behaviors it detects including those generate by cryptomining.
Simply applying AI techniques to NTA will find anomalous behavior within network traffic. However, without context is it difficult to understand if the anomaly is malicious or benign. Lastline uses both NTA and a deep understanding of malicious behaviors generated from our market-leading sandbox to eliminate false positives and deliver the highest fidelity insights possible into threats operating within your network.
Data exfiltration caused by a network breach occurs at the end of the breach chain, starting with the initial compromise of a system. Network perimeter and endpoint protection products can only detect the initial delivery and exploit stages, and don’t see the lateral movement of the attack across the network, access of critical systems, harvesting of data, or exfiltration. NTA tools detect anomalous behavior without any context of how malware and malicious actors operate. Applying AI to network traffic without context results in numerous false positive alerts and requires additional investigation by your over-burdened security team.
Lastline Network Defender provides complete visibility for every stage of the breach chain. We created a unique approach to detecting advanced threats where our AI learns from both anomalous network traffic in your environment and malicious behaviors detected by our market-leading sandbox. We designed our network sensors to detect advanced attack techniques such as lateral movement, discovery, and data exfiltration in network protocols.
This unmatched awareness and visibility enable Lastline Network Defender to analyze both North/South and East/West traffic related to advanced threats and deliver the industry’s highest fidelity alerts of malicious activity. Armed with these alerts, your security team will be able to respond faster and more effectively to threats operating in your network.
Bad actors operating in your network with compromised user credentials, or rogue insiders accessing sensitive data, evade detection from a range of network security controls. Your security controls are not able to stop them:
Lastline Network Defender provides context-aware network visibility by building behavior models for your assets and users, to ensure detection of unauthorized access from inside or outside your network. It applies AI to the anomalous network traffic detected by our network sensors and malicious behavior detected by our market-leading sandbox.
This unique combination of AI learning from both anomalous network traffic and malicious behavior provides high-fidelity detection of unauthorized access. It detects anomalous user and system behaviors as well as malicious behavior within your network, such as credential-stealing malware, with a higher degree of accuracy than other anomaly detection tools. Lastline Network Defender enables your security team to stop the most advanced threats from operating within your network and causing business disruption.
Lastline Email Defender™ is an additional layer of defense that delivers unmatched protection for cloud email as well as customer-managed email systems. It protects your users from advanced threats that are engineered to defeat other security tools, such as spear-phishing, ransomware, and credential stealers.
You can deploy Lastline Email Defender-Cloud to protect Office 365 mail and Gmail, or Lastline Email Defender-Enterprise to protect customer-managed email systems.
In order to defeat Account Takeover (ATO) attacks, Lastline utilizes a unique machine learning algorithm that analyzes 300+ indicators in each email by looking at each email component, including:
The API-based integration also allows Lastline to analyze historical emails to determine the prior trust relations between the sender and receiver. Even with these security measures, users may still lose their credentials.
To provide a complete solution for phishing, Lastline analyzes login and account activity to detect and block account takeovers. This is done by correlating login events with past activity based on geography, time of day, and other indicators and account activity, such as sending outgoing phishing emails, sending a high volume of emails, or emails with multiple recipients. By correlating these indicators through another machine learning filter, the algorithm is able to flag compromised accounts while minimizing false alerts.
Lastline’s anti-phishing algorithm combines traditional analysis capabilities with a proprietary machine learning algorithm that looks at all aspects of the email and is specifically trained to catch the things Office 365 mail and Gmail miss. With the addition of account takeover prevention and advanced malware detection, Lastline provides a complete security solution to protect your organization from phishing schemes.
Business Email Compromise (BEC) attacks often target cloud email systems like Office 365 mail and Gmail. They start with a spear-phishing attack or spoofed emails targeted at specific executives in order to commit fraud.
These attacks evade detection from email security controls that rely on content scanning or signature-matching. The emails do not contain links to any fraudulent sites or have malicious attachments, which normally trigger alerts.
Instead BEC attackers use publicly available data from social and business media sites to identify reporting relationships as well as names and titles of coworkers, upcoming travel, and so forth. They’ll use this knowledge to create a realistic looking message from a trusted co-worker to initiate a fraudulent transaction, such as a wire transfer.
To block the user impersonation that initiates BEC attacks, Lastline Email Defender-Cloud utilizes a unique machine to see if a similar sender exists in the organization with a different email address. It also verifies the identity of the sender by cross referencing several fields in the email including the sender and the signature at the bottom of the email. It also detects when the sender is using a domain similar to the known domain but with a different source IP, different mail-flow path, and so forth.
Lastline automates the detection, investigation, and response to advanced threats.
See for yourself how Lastline can make a difference.