Advanced threat detection keeps an eye on your infrastructure to protect it from assaults that evade more conventional security measures like firewalls, antivirus software, and intrusion prevention. Sandboxing and user and object behavior analytics are examples of dynamic, proactive security and protection strategies used by advanced threat detection systems and practices (UEBA). Prior to an advanced attack escalating into a breach, the objective is to proactively detect, isolate, and neutralize.

Advanced Threat Detection: Introduction

A new category of security solution known as advanced threat detection has emerged as malware advances to avoid detection by standard antivirus solutions, intrusion prevention systems, firewalls, and other network security solutions. Advanced threat detection tools are made to identify assaults that use persistent remote access and sophisticated malware in an effort to steal critical company data over time. Advanced threat detection solutions frequently include tools like sandboxing, behavioral analysis, automated monitoring, and other detection procedures to find these threats.

How Does Advanced Threat Detection Work?

Advanced threat detection systems will probably use sandboxing approaches to seclude, identify, and address potential advanced or persistent malware threats after they have been discovered. A security technique called sandboxing isolates any files that have been reported as suspicious in a virtual environment that is different from the actual applications, files, and networks of a victim’s machine. Then, using virtual machines to monitor the suspicious files, malware investigators will use this fake sandbox environment to compile a log of the suspicious files’ actions. These records can then be used by malware analysts to determine if the files are malware or not.

Attackers’ Goals

  • User’s Credential – Make it possible for attackers to access systems without breaking in. Attackers can instead easily access resources by using stolen user credentials while masquerading as authorized users.
  • Personal Identifiable Information – Criminals value information such as financial information, identification numbers, or birth dates.
  • Intellectual Property or Sensitive Information – Competitors and adversary nation-states can benefit from knowing this knowledge. Criminals may try to steal this data in order to resell it or exploit it for their own gain.
  • Revenge – This is frequently carried out by irate customers, former employees, or “hacktivists” who aim to punish or defame a business.

Advanced Threat Detection Strategies

  • Establish a large test repository.

Comparing possible threats to suspicious behavior is a key component of advanced threat detection. Your detection results will be more accurate and less likely to miss malware cases the more dependable and representative your behavioral library is. Include data from both known threats and benign activity in your test baselines to make sure they are strong. Your solutions should be tested against malware varieties, network traffic profiles, forensic information gathered from your own systems, and dynamic behaviors when processing events.

  • Incorporate virtuous software behavior

Understanding the behavior of benign software is necessary for building a strong behavioral database. You can more accurately identify malware if you are aware of the processes that typical programs use to execute and how they interact with your system. False positives can also be more reliably excluded.

  • Ongoing data gathering and analysis

As was previously mentioned, your solution will be more effective the more data you gather. By assuring constant data collection and analysis, you may reduce the possibility that malware will be overlooked by making sure that no events elude your systems.

Intelecis’ Advanced Threat Detection and Protection

  • Stop exploit-like actions.

Intelecis keeps an eye on endpoint memory to spot exploitable behavioral patterns like odd process handle requests.

  • Block malware produced from exploits.

Sandboxing, process activity monitoring, and ML-based static analysis are just a few of the multiple layers of malware protection used by Intelecis. Additionally, Intelecis provides threat intelligence and fuzzy hashing.

  • UBA

Intelecis continuously tracks user behavior, creates a behavioral baseline in real-time, and issues warnings when a variation in behavior is found. This change in behavior can be a sign that a user account has been compromised.

  • Deception

Intelecis encourages the use of dummy tokens, such as passwords, network shares, RDP, and data files, which are hidden on protected environment assets. Because APT actors are very trained, they may be able to avoid detection.

  • Find hidden dangers

Intelecis identifies dangers along the assault chain by focusing on the adversary.

  • Precise and exact

With the help of a potent correlation engine, Intelecis‘ attack findings are free from excess noise and have almost no false positives. Security teams can respond to urgent occurrences more quickly as a result of this.

When utilized properly, sophisticated threat detection is a potent weapon in the cybersecurity professionals’ toolbox for preventing malware infestations. Advanced threat prevention works best when used in conjunction with other security layers as part of a comprehensive security solution, as is the case with many cybersecurity tools.